From 3dfe998ae9d2c70cbbd3a2c93d9d17a2145d980d Mon Sep 17 00:00:00 2001
From: Sergey Cherkashin <4erkashin@list.ru>
Date: Fri, 9 Nov 2018 18:51:36 +0300
Subject: [PATCH 1/5] Move python test on testgres and add stress test
---
.travis.yml | 1 +
Makefile | 2 +-
README.md | 11 +-
run_tests.sh | 7 +-
tests/pg_qs_test_runner.py | 69 +-
tests/prepare_stress.sh | 19 +
tests/query_tpcds.sql | 4866 ++++++++++++++++++++++++++++++++++++
tests/test_cases.py | 508 ++--
8 files changed, 5182 insertions(+), 301 deletions(-)
create mode 100755 tests/prepare_stress.sh
create mode 100644 tests/query_tpcds.sql
diff --git a/.travis.yml b/.travis.yml
index dc651bd..3708b14 100644
--- a/.travis.yml
+++ b/.travis.yml
@@ -24,6 +24,7 @@ env:
- PG_VERSION=10
- PG_VERSION=9.6 LEVEL=hardcore
- PG_VERSION=9.6
+ - PG_VERSION=10 LEVEL=stress
matrix:
allow_failures:
diff --git a/Makefile b/Makefile
index 08d24ac..6458a14 100644
--- a/Makefile
+++ b/Makefile
@@ -9,7 +9,7 @@ DATA_built = $(EXTENSION)--$(EXTVERSION).sql
PGFILEDESC = "pg_query_state - facility to track progress of plan execution"
EXTRA_CLEAN = ./isolation_output $(EXTENSION)--$(EXTVERSION).sql \
- Dockerfile ./tests/*.pyc
+ Dockerfile ./tests/*.pyc ./tmp_stress
ifdef USE_PGXS
PG_CONFIG = pg_config
diff --git a/README.md b/README.md
index 34ecdb0..ea16884 100644
--- a/README.md
+++ b/README.md
@@ -34,18 +34,15 @@ Done!
## Tests
Tests using parallel sessions using python 2.7 script:
```
+ export PG_CONFIG=/path/to/pg_config
python tests/pg_qs_test_runner.py [OPTION]...
```
*prerequisite packages*:
-* `psycopg2` version 2.6 or later
+* `testgres` version 1.8.2 or later
* `PyYAML` version 3.11 or later
-
+
*options*:
-* *- -host* --- postgres server host, default value is *localhost*
-* *- -port* --- postgres server port, default value is *5432*
-* *- -database* --- database name, default value is *postgres*
-* *- -user* --- user name, default value is *postgres*
-* *- -password* --- user's password, default value is empty
+* *--stress* --- run stress test using tpc-ds benchmark
## Function pg\_query\_state
```plpgsql
diff --git a/run_tests.sh b/run_tests.sh
index bb7b75c..0053aee 100755
--- a/run_tests.sh
+++ b/run_tests.sh
@@ -8,6 +8,7 @@
# * scan-build
# * hardcore
# * nightmare
+# * stress
#
set -ux
@@ -146,7 +147,11 @@ set +x -e
virtualenv /tmp/env && source /tmp/env/bin/activate &&
pip install PyYAML && pip install psycopg2
set -e #exit virtualenv with error code
-python tests/pg_qs_test_runner.py --port $PGPORT
+if [ "$LEVEL" = "stress" ]; then
+ python tests/pg_qs_test_runner.py --stress
+else
+ python tests/pg_qs_test_runner.py
+fi
deactivate
set -x
diff --git a/tests/pg_qs_test_runner.py b/tests/pg_qs_test_runner.py
index 716719e..dc68dc4 100644
--- a/tests/pg_qs_test_runner.py
+++ b/tests/pg_qs_test_runner.py
@@ -5,17 +5,11 @@
'''
import argparse
-import psycopg2
import sys
from test_cases import *
-
-class PasswordPromptAction(argparse.Action):
- def __call__(self, parser, args, values, option_string=None):
- password = getpass.getpass()
- setattr(args, self.dest, password)
+import testgres
class SetupException(Exception): pass
-class TeardownException(Exception): pass
setup_cmd = [
'drop extension if exists pg_query_state cascade',
@@ -25,17 +19,11 @@ class TeardownException(Exception): pass
'create table foo(c1 integer, c2 text)',
'create table bar(c1 integer, c2 boolean)',
'insert into foo select i, md5(random()::text) from generate_series(1, 1000000) as i',
- 'insert into bar select i, i%2=1 from generate_series(1, 500000) as i',
+ 'insert into bar select i, i%%2=1 from generate_series(1, 500000) as i',
'analyze foo',
'analyze bar',
]
-teardown_cmd = [
- 'drop table foo cascade',
- 'drop table bar cascade',
- 'drop extension pg_query_state cascade',
- ]
-
tests = [
test_deadlock,
test_simple_query,
@@ -50,36 +38,26 @@ class TeardownException(Exception): pass
test_insert_on_conflict,
]
-def setup(con):
+def setup(node):
''' Creates pg_query_state extension, creates tables for tests, fills it with data '''
print 'setting up...'
+ conn = testgres.connection.NodeConnection(node)
try:
- cur = con.cursor()
for cmd in setup_cmd:
- cur.execute(cmd)
- con.commit()
- cur.close()
+ conn.execute(cmd)
+ conn.commit()
+ conn.close()
except Exception, e:
raise SetupException('Setup failed: %s' % e)
print 'done!'
-def teardown(con):
- ''' Drops table and extension '''
- print 'tearing down...'
- try:
- cur = con.cursor()
- for cmd in teardown_cmd:
- cur.execute(cmd)
- con.commit()
- cur.close()
- except Exception, e:
- raise TeardownException('Teardown failed: %s' % e)
- print 'done!'
-
-def main(config):
+def main(args):
''' Main test function '''
- con = psycopg2.connect(**config)
- setup(con)
+ node = testgres.get_new_node()
+ node.init()
+ node.append_conf("shared_preload_libraries='pg_query_state'\n")
+ node.start()
+ setup(node)
for i, test in enumerate(tests):
if test.__doc__:
@@ -87,18 +65,21 @@ def main(config):
else:
descr = 'test case %d' % (i+1)
print ("%s..." % descr),; sys.stdout.flush()
- test(config)
+ test(node)
print 'ok!'
- teardown(con)
- con.close()
+ if args.stress:
+ print 'Start stress test'
+ stress_test(node)
+ print 'Start stress finished successfully'
+ print 'stop'
+
+ node.stop()
+ node.cleanup()
if __name__ == '__main__':
parser = argparse.ArgumentParser(description='Query state of running backends tests')
- parser.add_argument('--host', default='localhost', help='postgres server host')
- parser.add_argument('--port', type=int, default=5432, help='postgres server port')
- parser.add_argument('--user', dest='user', default='postgres', help='user name')
- parser.add_argument('--database', dest='database', default='postgres', help='database name')
- parser.add_argument('--password', dest='password', nargs=0, action=PasswordPromptAction, default='')
+ parser.add_argument('--stress', help='run stress test using tpc-ds benchmark',
+ action="store_true")
args = parser.parse_args()
- main(args.__dict__)
+ main(args)
diff --git a/tests/prepare_stress.sh b/tests/prepare_stress.sh
new file mode 100755
index 0000000..12dbf60
--- /dev/null
+++ b/tests/prepare_stress.sh
@@ -0,0 +1,19 @@
+#!/bin/sh
+mkdir -p tmp_stress
+cd tmp_stress
+rm -rf ./*
+git clone https://github.com/gregrahn/tpcds-kit.git
+cd tpcds-kit/tools
+make -s
+
+#Generate data
+./dsdgen -FORCE -VERBOSE
+mkdir tables -p
+#Prepare data
+for i in `ls *.dat`; do
+ echo "Prepare file " $i
+ sed 's/|$//' $i > tables/$i
+done
+#Generate queries
+./dsqgen -DIRECTORY ../query_templates -INPUT ../query_templates/templates.lst \
+ -VERBOSE Y -QUALIFY Y -DIALECT netezza
diff --git a/tests/query_tpcds.sql b/tests/query_tpcds.sql
new file mode 100644
index 0000000..d619abe
--- /dev/null
+++ b/tests/query_tpcds.sql
@@ -0,0 +1,4866 @@
+-- start query 1 in stream 0 using template query1.tpl
+with customer_total_return as
+(select sr_customer_sk as ctr_customer_sk
+,sr_store_sk as ctr_store_sk
+,sum(SR_FEE) as ctr_total_return
+from store_returns
+,date_dim
+where sr_returned_date_sk = d_date_sk
+and d_year =2000
+group by sr_customer_sk
+,sr_store_sk)
+ select c_customer_id
+from customer_total_return ctr1
+,store
+,customer
+where ctr1.ctr_total_return > (select avg(ctr_total_return)*1.2
+from customer_total_return ctr2
+where ctr1.ctr_store_sk = ctr2.ctr_store_sk)
+and s_store_sk = ctr1.ctr_store_sk
+and s_state = 'TN'
+and ctr1.ctr_customer_sk = c_customer_sk
+order by c_customer_id
+limit 100;
+
+-- end query 1 in stream 0 using template query1.tpl
+-- start query 2 in stream 0 using template query2.tpl
+with wscs as
+ (select sold_date_sk
+ ,sales_price
+ from (select ws_sold_date_sk sold_date_sk
+ ,ws_ext_sales_price sales_price
+ from web_sales
+ union all
+ select cs_sold_date_sk sold_date_sk
+ ,cs_ext_sales_price sales_price
+ from catalog_sales) as sdsp),
+ wswscs as
+ (select d_week_seq,
+ sum(case when (d_day_name='Sunday') then sales_price else null end) sun_sales,
+ sum(case when (d_day_name='Monday') then sales_price else null end) mon_sales,
+ sum(case when (d_day_name='Tuesday') then sales_price else null end) tue_sales,
+ sum(case when (d_day_name='Wednesday') then sales_price else null end) wed_sales,
+ sum(case when (d_day_name='Thursday') then sales_price else null end) thu_sales,
+ sum(case when (d_day_name='Friday') then sales_price else null end) fri_sales,
+ sum(case when (d_day_name='Saturday') then sales_price else null end) sat_sales
+ from wscs
+ ,date_dim
+ where d_date_sk = sold_date_sk
+ group by d_week_seq)
+ select d_week_seq1
+ ,round(sun_sales1/sun_sales2,2)
+ ,round(mon_sales1/mon_sales2,2)
+ ,round(tue_sales1/tue_sales2,2)
+ ,round(wed_sales1/wed_sales2,2)
+ ,round(thu_sales1/thu_sales2,2)
+ ,round(fri_sales1/fri_sales2,2)
+ ,round(sat_sales1/sat_sales2,2)
+ from
+ (select wswscs.d_week_seq d_week_seq1
+ ,sun_sales sun_sales1
+ ,mon_sales mon_sales1
+ ,tue_sales tue_sales1
+ ,wed_sales wed_sales1
+ ,thu_sales thu_sales1
+ ,fri_sales fri_sales1
+ ,sat_sales sat_sales1
+ from wswscs,date_dim
+ where date_dim.d_week_seq = wswscs.d_week_seq and
+ d_year = 1998) y,
+ (select wswscs.d_week_seq d_week_seq2
+ ,sun_sales sun_sales2
+ ,mon_sales mon_sales2
+ ,tue_sales tue_sales2
+ ,wed_sales wed_sales2
+ ,thu_sales thu_sales2
+ ,fri_sales fri_sales2
+ ,sat_sales sat_sales2
+ from wswscs
+ ,date_dim
+ where date_dim.d_week_seq = wswscs.d_week_seq and
+ d_year = 1998+1) z
+ where d_week_seq1=d_week_seq2-53
+ order by d_week_seq1;
+
+-- end query 2 in stream 0 using template query2.tpl
+-- start query 3 in stream 0 using template query3.tpl
+select dt.d_year
+ ,item.i_brand_id brand_id
+ ,item.i_brand brand
+ ,sum(ss_sales_price) sum_agg
+ from date_dim dt
+ ,store_sales
+ ,item
+ where dt.d_date_sk = store_sales.ss_sold_date_sk
+ and store_sales.ss_item_sk = item.i_item_sk
+ and item.i_manufact_id = 816
+ and dt.d_moy=11
+ group by dt.d_year
+ ,item.i_brand
+ ,item.i_brand_id
+ order by dt.d_year
+ ,sum_agg desc
+ ,brand_id
+ limit 100;
+
+-- end query 3 in stream 0 using template query3.tpl
+-- start query 4 in stream 0 using template query4.tpl
+with year_total as (
+ select c_customer_id customer_id
+ ,c_first_name customer_first_name
+ ,c_last_name customer_last_name
+ ,c_preferred_cust_flag customer_preferred_cust_flag
+ ,c_birth_country customer_birth_country
+ ,c_login customer_login
+ ,c_email_address customer_email_address
+ ,d_year dyear
+ ,sum(((ss_ext_list_price-ss_ext_wholesale_cost-ss_ext_discount_amt)+ss_ext_sales_price)/2) year_total
+ ,'s' sale_type
+ from customer
+ ,store_sales
+ ,date_dim
+ where c_customer_sk = ss_customer_sk
+ and ss_sold_date_sk = d_date_sk
+ group by c_customer_id
+ ,c_first_name
+ ,c_last_name
+ ,c_preferred_cust_flag
+ ,c_birth_country
+ ,c_login
+ ,c_email_address
+ ,d_year
+ union all
+ select c_customer_id customer_id
+ ,c_first_name customer_first_name
+ ,c_last_name customer_last_name
+ ,c_preferred_cust_flag customer_preferred_cust_flag
+ ,c_birth_country customer_birth_country
+ ,c_login customer_login
+ ,c_email_address customer_email_address
+ ,d_year dyear
+ ,sum((((cs_ext_list_price-cs_ext_wholesale_cost-cs_ext_discount_amt)+cs_ext_sales_price)/2) ) year_total
+ ,'c' sale_type
+ from customer
+ ,catalog_sales
+ ,date_dim
+ where c_customer_sk = cs_bill_customer_sk
+ and cs_sold_date_sk = d_date_sk
+ group by c_customer_id
+ ,c_first_name
+ ,c_last_name
+ ,c_preferred_cust_flag
+ ,c_birth_country
+ ,c_login
+ ,c_email_address
+ ,d_year
+union all
+ select c_customer_id customer_id
+ ,c_first_name customer_first_name
+ ,c_last_name customer_last_name
+ ,c_preferred_cust_flag customer_preferred_cust_flag
+ ,c_birth_country customer_birth_country
+ ,c_login customer_login
+ ,c_email_address customer_email_address
+ ,d_year dyear
+ ,sum((((ws_ext_list_price-ws_ext_wholesale_cost-ws_ext_discount_amt)+ws_ext_sales_price)/2) ) year_total
+ ,'w' sale_type
+ from customer
+ ,web_sales
+ ,date_dim
+ where c_customer_sk = ws_bill_customer_sk
+ and ws_sold_date_sk = d_date_sk
+ group by c_customer_id
+ ,c_first_name
+ ,c_last_name
+ ,c_preferred_cust_flag
+ ,c_birth_country
+ ,c_login
+ ,c_email_address
+ ,d_year
+ )
+ select
+ t_s_secyear.customer_id
+ ,t_s_secyear.customer_first_name
+ ,t_s_secyear.customer_last_name
+ ,t_s_secyear.customer_birth_country
+ from year_total t_s_firstyear
+ ,year_total t_s_secyear
+ ,year_total t_c_firstyear
+ ,year_total t_c_secyear
+ ,year_total t_w_firstyear
+ ,year_total t_w_secyear
+ where t_s_secyear.customer_id = t_s_firstyear.customer_id
+ and t_s_firstyear.customer_id = t_c_secyear.customer_id
+ and t_s_firstyear.customer_id = t_c_firstyear.customer_id
+ and t_s_firstyear.customer_id = t_w_firstyear.customer_id
+ and t_s_firstyear.customer_id = t_w_secyear.customer_id
+ and t_s_firstyear.sale_type = 's'
+ and t_c_firstyear.sale_type = 'c'
+ and t_w_firstyear.sale_type = 'w'
+ and t_s_secyear.sale_type = 's'
+ and t_c_secyear.sale_type = 'c'
+ and t_w_secyear.sale_type = 'w'
+ and t_s_firstyear.dyear = 1999
+ and t_s_secyear.dyear = 1999+1
+ and t_c_firstyear.dyear = 1999
+ and t_c_secyear.dyear = 1999+1
+ and t_w_firstyear.dyear = 1999
+ and t_w_secyear.dyear = 1999+1
+ and t_s_firstyear.year_total > 0
+ and t_c_firstyear.year_total > 0
+ and t_w_firstyear.year_total > 0
+ and case when t_c_firstyear.year_total > 0 then t_c_secyear.year_total / t_c_firstyear.year_total else null end
+ > case when t_s_firstyear.year_total > 0 then t_s_secyear.year_total / t_s_firstyear.year_total else null end
+ and case when t_c_firstyear.year_total > 0 then t_c_secyear.year_total / t_c_firstyear.year_total else null end
+ > case when t_w_firstyear.year_total > 0 then t_w_secyear.year_total / t_w_firstyear.year_total else null end
+ order by t_s_secyear.customer_id
+ ,t_s_secyear.customer_first_name
+ ,t_s_secyear.customer_last_name
+ ,t_s_secyear.customer_birth_country
+limit 100;
+
+-- end query 4 in stream 0 using template query4.tpl
+-- start query 5 in stream 0 using template query5.tpl
+with ssr as
+ (select s_store_id,
+ sum(sales_price) as sales,
+ sum(profit) as profit,
+ sum(return_amt) as returns,
+ sum(net_loss) as profit_loss
+ from
+ ( select ss_store_sk as store_sk,
+ ss_sold_date_sk as date_sk,
+ ss_ext_sales_price as sales_price,
+ ss_net_profit as profit,
+ cast(0 as decimal(7,2)) as return_amt,
+ cast(0 as decimal(7,2)) as net_loss
+ from store_sales
+ union all
+ select sr_store_sk as store_sk,
+ sr_returned_date_sk as date_sk,
+ cast(0 as decimal(7,2)) as sales_price,
+ cast(0 as decimal(7,2)) as profit,
+ sr_return_amt as return_amt,
+ sr_net_loss as net_loss
+ from store_returns
+ ) salesreturns,
+ date_dim,
+ store
+ where date_sk = d_date_sk
+ and d_date between cast('2000-08-19' as date)
+ and (cast('2000-08-19' as date) + 14 days)
+ and store_sk = s_store_sk
+ group by s_store_id)
+ ,
+ csr as
+ (select cp_catalog_page_id,
+ sum(sales_price) as sales,
+ sum(profit) as profit,
+ sum(return_amt) as returns,
+ sum(net_loss) as profit_loss
+ from
+ ( select cs_catalog_page_sk as page_sk,
+ cs_sold_date_sk as date_sk,
+ cs_ext_sales_price as sales_price,
+ cs_net_profit as profit,
+ cast(0 as decimal(7,2)) as return_amt,
+ cast(0 as decimal(7,2)) as net_loss
+ from catalog_sales
+ union all
+ select cr_catalog_page_sk as page_sk,
+ cr_returned_date_sk as date_sk,
+ cast(0 as decimal(7,2)) as sales_price,
+ cast(0 as decimal(7,2)) as profit,
+ cr_return_amount as return_amt,
+ cr_net_loss as net_loss
+ from catalog_returns
+ ) salesreturns,
+ date_dim,
+ catalog_page
+ where date_sk = d_date_sk
+ and d_date between cast('2000-08-19' as date)
+ and (cast('2000-08-19' as date) + 14 days)
+ and page_sk = cp_catalog_page_sk
+ group by cp_catalog_page_id)
+ ,
+ wsr as
+ (select web_site_id,
+ sum(sales_price) as sales,
+ sum(profit) as profit,
+ sum(return_amt) as returns,
+ sum(net_loss) as profit_loss
+ from
+ ( select ws_web_site_sk as wsr_web_site_sk,
+ ws_sold_date_sk as date_sk,
+ ws_ext_sales_price as sales_price,
+ ws_net_profit as profit,
+ cast(0 as decimal(7,2)) as return_amt,
+ cast(0 as decimal(7,2)) as net_loss
+ from web_sales
+ union all
+ select ws_web_site_sk as wsr_web_site_sk,
+ wr_returned_date_sk as date_sk,
+ cast(0 as decimal(7,2)) as sales_price,
+ cast(0 as decimal(7,2)) as profit,
+ wr_return_amt as return_amt,
+ wr_net_loss as net_loss
+ from web_returns left outer join web_sales on
+ ( wr_item_sk = ws_item_sk
+ and wr_order_number = ws_order_number)
+ ) salesreturns,
+ date_dim,
+ web_site
+ where date_sk = d_date_sk
+ and d_date between cast('2000-08-19' as date)
+ and (cast('2000-08-19' as date) + 14 days)
+ and wsr_web_site_sk = web_site_sk
+ group by web_site_id)
+ select channel
+ , id
+ , sum(sales) as sales
+ , sum(returns) as returns
+ , sum(profit) as profit
+ from
+ (select 'store channel' as channel
+ , 'store' || s_store_id as id
+ , sales
+ , returns
+ , (profit - profit_loss) as profit
+ from ssr
+ union all
+ select 'catalog channel' as channel
+ , 'catalog_page' || cp_catalog_page_id as id
+ , sales
+ , returns
+ , (profit - profit_loss) as profit
+ from csr
+ union all
+ select 'web channel' as channel
+ , 'web_site' || web_site_id as id
+ , sales
+ , returns
+ , (profit - profit_loss) as profit
+ from wsr
+ ) x
+ group by rollup (channel, id)
+ order by channel
+ ,id
+ limit 100;
+
+-- end query 5 in stream 0 using template query5.tpl
+-- start query 6 in stream 0 using template query6.tpl
+select a.ca_state state, count(*) cnt
+ from customer_address a
+ ,customer c
+ ,store_sales s
+ ,date_dim d
+ ,item i
+ where a.ca_address_sk = c.c_current_addr_sk
+ and c.c_customer_sk = s.ss_customer_sk
+ and s.ss_sold_date_sk = d.d_date_sk
+ and s.ss_item_sk = i.i_item_sk
+ and d.d_month_seq =
+ (select distinct (d_month_seq)
+ from date_dim
+ where d_year = 2002
+ and d_moy = 3 )
+ and i.i_current_price > 1.2 *
+ (select avg(j.i_current_price)
+ from item j
+ where j.i_category = i.i_category)
+ group by a.ca_state
+ having count(*) >= 10
+ order by cnt, a.ca_state
+ limit 100;
+
+-- end query 6 in stream 0 using template query6.tpl
+-- start query 7 in stream 0 using template query7.tpl
+select i_item_id,
+ avg(ss_quantity) agg1,
+ avg(ss_list_price) agg2,
+ avg(ss_coupon_amt) agg3,
+ avg(ss_sales_price) agg4
+ from store_sales, customer_demographics, date_dim, item, promotion
+ where ss_sold_date_sk = d_date_sk and
+ ss_item_sk = i_item_sk and
+ ss_cdemo_sk = cd_demo_sk and
+ ss_promo_sk = p_promo_sk and
+ cd_gender = 'F' and
+ cd_marital_status = 'W' and
+ cd_education_status = 'College' and
+ (p_channel_email = 'N' or p_channel_event = 'N') and
+ d_year = 2001
+ group by i_item_id
+ order by i_item_id
+ limit 100;
+
+-- end query 7 in stream 0 using template query7.tpl
+-- start query 8 in stream 0 using template query8.tpl
+select s_store_name
+ ,sum(ss_net_profit)
+ from store_sales
+ ,date_dim
+ ,store,
+ (select ca_zip
+ from (
+ SELECT substr(ca_zip,1,5) ca_zip
+ FROM customer_address
+ WHERE substr(ca_zip,1,5) IN (
+ '47602','16704','35863','28577','83910','36201',
+ '58412','48162','28055','41419','80332',
+ '38607','77817','24891','16226','18410',
+ '21231','59345','13918','51089','20317',
+ '17167','54585','67881','78366','47770',
+ '18360','51717','73108','14440','21800',
+ '89338','45859','65501','34948','25973',
+ '73219','25333','17291','10374','18829',
+ '60736','82620','41351','52094','19326',
+ '25214','54207','40936','21814','79077',
+ '25178','75742','77454','30621','89193',
+ '27369','41232','48567','83041','71948',
+ '37119','68341','14073','16891','62878',
+ '49130','19833','24286','27700','40979',
+ '50412','81504','94835','84844','71954',
+ '39503','57649','18434','24987','12350',
+ '86379','27413','44529','98569','16515',
+ '27287','24255','21094','16005','56436',
+ '91110','68293','56455','54558','10298',
+ '83647','32754','27052','51766','19444',
+ '13869','45645','94791','57631','20712',
+ '37788','41807','46507','21727','71836',
+ '81070','50632','88086','63991','20244',
+ '31655','51782','29818','63792','68605',
+ '94898','36430','57025','20601','82080',
+ '33869','22728','35834','29086','92645',
+ '98584','98072','11652','78093','57553',
+ '43830','71144','53565','18700','90209',
+ '71256','38353','54364','28571','96560',
+ '57839','56355','50679','45266','84680',
+ '34306','34972','48530','30106','15371',
+ '92380','84247','92292','68852','13338',
+ '34594','82602','70073','98069','85066',
+ '47289','11686','98862','26217','47529',
+ '63294','51793','35926','24227','14196',
+ '24594','32489','99060','49472','43432',
+ '49211','14312','88137','47369','56877',
+ '20534','81755','15794','12318','21060',
+ '73134','41255','63073','81003','73873',
+ '66057','51184','51195','45676','92696',
+ '70450','90669','98338','25264','38919',
+ '59226','58581','60298','17895','19489',
+ '52301','80846','95464','68770','51634',
+ '19988','18367','18421','11618','67975',
+ '25494','41352','95430','15734','62585',
+ '97173','33773','10425','75675','53535',
+ '17879','41967','12197','67998','79658',
+ '59130','72592','14851','43933','68101',
+ '50636','25717','71286','24660','58058',
+ '72991','95042','15543','33122','69280',
+ '11912','59386','27642','65177','17672',
+ '33467','64592','36335','54010','18767',
+ '63193','42361','49254','33113','33159',
+ '36479','59080','11855','81963','31016',
+ '49140','29392','41836','32958','53163',
+ '13844','73146','23952','65148','93498',
+ '14530','46131','58454','13376','13378',
+ '83986','12320','17193','59852','46081',
+ '98533','52389','13086','68843','31013',
+ '13261','60560','13443','45533','83583',
+ '11489','58218','19753','22911','25115',
+ '86709','27156','32669','13123','51933',
+ '39214','41331','66943','14155','69998',
+ '49101','70070','35076','14242','73021',
+ '59494','15782','29752','37914','74686',
+ '83086','34473','15751','81084','49230',
+ '91894','60624','17819','28810','63180',
+ '56224','39459','55233','75752','43639',
+ '55349','86057','62361','50788','31830',
+ '58062','18218','85761','60083','45484',
+ '21204','90229','70041','41162','35390',
+ '16364','39500','68908','26689','52868',
+ '81335','40146','11340','61527','61794',
+ '71997','30415','59004','29450','58117',
+ '69952','33562','83833','27385','61860',
+ '96435','48333','23065','32961','84919',
+ '61997','99132','22815','56600','68730',
+ '48017','95694','32919','88217','27116',
+ '28239','58032','18884','16791','21343',
+ '97462','18569','75660','15475')
+ intersect
+ select ca_zip
+ from (SELECT substr(ca_zip,1,5) ca_zip,count(*) cnt
+ FROM customer_address, customer
+ WHERE ca_address_sk = c_current_addr_sk and
+ c_preferred_cust_flag='Y'
+ group by ca_zip
+ having count(*) > 10)A1)A2) V1
+ where ss_store_sk = s_store_sk
+ and ss_sold_date_sk = d_date_sk
+ and d_qoy = 2 and d_year = 1998
+ and (substr(s_zip,1,2) = substr(V1.ca_zip,1,2))
+ group by s_store_name
+ order by s_store_name
+ limit 100;
+
+-- end query 8 in stream 0 using template query8.tpl
+-- start query 9 in stream 0 using template query9.tpl
+select case when (select count(*)
+ from store_sales
+ where ss_quantity between 1 and 20) > 1071
+ then (select avg(ss_ext_tax)
+ from store_sales
+ where ss_quantity between 1 and 20)
+ else (select avg(ss_net_paid_inc_tax)
+ from store_sales
+ where ss_quantity between 1 and 20) end bucket1 ,
+ case when (select count(*)
+ from store_sales
+ where ss_quantity between 21 and 40) > 39161
+ then (select avg(ss_ext_tax)
+ from store_sales
+ where ss_quantity between 21 and 40)
+ else (select avg(ss_net_paid_inc_tax)
+ from store_sales
+ where ss_quantity between 21 and 40) end bucket2,
+ case when (select count(*)
+ from store_sales
+ where ss_quantity between 41 and 60) > 29434
+ then (select avg(ss_ext_tax)
+ from store_sales
+ where ss_quantity between 41 and 60)
+ else (select avg(ss_net_paid_inc_tax)
+ from store_sales
+ where ss_quantity between 41 and 60) end bucket3,
+ case when (select count(*)
+ from store_sales
+ where ss_quantity between 61 and 80) > 6568
+ then (select avg(ss_ext_tax)
+ from store_sales
+ where ss_quantity between 61 and 80)
+ else (select avg(ss_net_paid_inc_tax)
+ from store_sales
+ where ss_quantity between 61 and 80) end bucket4,
+ case when (select count(*)
+ from store_sales
+ where ss_quantity between 81 and 100) > 21216
+ then (select avg(ss_ext_tax)
+ from store_sales
+ where ss_quantity between 81 and 100)
+ else (select avg(ss_net_paid_inc_tax)
+ from store_sales
+ where ss_quantity between 81 and 100) end bucket5
+from reason
+where r_reason_sk = 1
+;
+
+-- end query 9 in stream 0 using template query9.tpl
+-- start query 10 in stream 0 using template query10.tpl
+select
+ cd_gender,
+ cd_marital_status,
+ cd_education_status,
+ count(*) cnt1,
+ cd_purchase_estimate,
+ count(*) cnt2,
+ cd_credit_rating,
+ count(*) cnt3,
+ cd_dep_count,
+ count(*) cnt4,
+ cd_dep_employed_count,
+ count(*) cnt5,
+ cd_dep_college_count,
+ count(*) cnt6
+ from
+ customer c,customer_address ca,customer_demographics
+ where
+ c.c_current_addr_sk = ca.ca_address_sk and
+ ca_county in ('Fairfield County','Campbell County','Washtenaw County','Escambia County','Cleburne County') and
+ cd_demo_sk = c.c_current_cdemo_sk and
+ exists (select *
+ from store_sales,date_dim
+ where c.c_customer_sk = ss_customer_sk and
+ ss_sold_date_sk = d_date_sk and
+ d_year = 2001 and
+ d_moy between 3 and 3+3) and
+ (exists (select *
+ from web_sales,date_dim
+ where c.c_customer_sk = ws_bill_customer_sk and
+ ws_sold_date_sk = d_date_sk and
+ d_year = 2001 and
+ d_moy between 3 ANd 3+3) or
+ exists (select *
+ from catalog_sales,date_dim
+ where c.c_customer_sk = cs_ship_customer_sk and
+ cs_sold_date_sk = d_date_sk and
+ d_year = 2001 and
+ d_moy between 3 and 3+3))
+ group by cd_gender,
+ cd_marital_status,
+ cd_education_status,
+ cd_purchase_estimate,
+ cd_credit_rating,
+ cd_dep_count,
+ cd_dep_employed_count,
+ cd_dep_college_count
+ order by cd_gender,
+ cd_marital_status,
+ cd_education_status,
+ cd_purchase_estimate,
+ cd_credit_rating,
+ cd_dep_count,
+ cd_dep_employed_count,
+ cd_dep_college_count
+limit 100;
+
+-- end query 10 in stream 0 using template query10.tpl
+-- start query 11 in stream 0 using template query11.tpl
+with year_total as (
+ select c_customer_id customer_id
+ ,c_first_name customer_first_name
+ ,c_last_name customer_last_name
+ ,c_preferred_cust_flag customer_preferred_cust_flag
+ ,c_birth_country customer_birth_country
+ ,c_login customer_login
+ ,c_email_address customer_email_address
+ ,d_year dyear
+ ,sum(ss_ext_list_price-ss_ext_discount_amt) year_total
+ ,'s' sale_type
+ from customer
+ ,store_sales
+ ,date_dim
+ where c_customer_sk = ss_customer_sk
+ and ss_sold_date_sk = d_date_sk
+ group by c_customer_id
+ ,c_first_name
+ ,c_last_name
+ ,c_preferred_cust_flag
+ ,c_birth_country
+ ,c_login
+ ,c_email_address
+ ,d_year
+ union all
+ select c_customer_id customer_id
+ ,c_first_name customer_first_name
+ ,c_last_name customer_last_name
+ ,c_preferred_cust_flag customer_preferred_cust_flag
+ ,c_birth_country customer_birth_country
+ ,c_login customer_login
+ ,c_email_address customer_email_address
+ ,d_year dyear
+ ,sum(ws_ext_list_price-ws_ext_discount_amt) year_total
+ ,'w' sale_type
+ from customer
+ ,web_sales
+ ,date_dim
+ where c_customer_sk = ws_bill_customer_sk
+ and ws_sold_date_sk = d_date_sk
+ group by c_customer_id
+ ,c_first_name
+ ,c_last_name
+ ,c_preferred_cust_flag
+ ,c_birth_country
+ ,c_login
+ ,c_email_address
+ ,d_year
+ )
+ select
+ t_s_secyear.customer_id
+ ,t_s_secyear.customer_first_name
+ ,t_s_secyear.customer_last_name
+ ,t_s_secyear.customer_email_address
+ from year_total t_s_firstyear
+ ,year_total t_s_secyear
+ ,year_total t_w_firstyear
+ ,year_total t_w_secyear
+ where t_s_secyear.customer_id = t_s_firstyear.customer_id
+ and t_s_firstyear.customer_id = t_w_secyear.customer_id
+ and t_s_firstyear.customer_id = t_w_firstyear.customer_id
+ and t_s_firstyear.sale_type = 's'
+ and t_w_firstyear.sale_type = 'w'
+ and t_s_secyear.sale_type = 's'
+ and t_w_secyear.sale_type = 'w'
+ and t_s_firstyear.dyear = 1998
+ and t_s_secyear.dyear = 1998+1
+ and t_w_firstyear.dyear = 1998
+ and t_w_secyear.dyear = 1998+1
+ and t_s_firstyear.year_total > 0
+ and t_w_firstyear.year_total > 0
+ and case when t_w_firstyear.year_total > 0 then t_w_secyear.year_total / t_w_firstyear.year_total else 0.0 end
+ > case when t_s_firstyear.year_total > 0 then t_s_secyear.year_total / t_s_firstyear.year_total else 0.0 end
+ order by t_s_secyear.customer_id
+ ,t_s_secyear.customer_first_name
+ ,t_s_secyear.customer_last_name
+ ,t_s_secyear.customer_email_address
+limit 100;
+
+-- end query 11 in stream 0 using template query11.tpl
+-- start query 12 in stream 0 using template query12.tpl
+select i_item_id
+ ,i_item_desc
+ ,i_category
+ ,i_class
+ ,i_current_price
+ ,sum(ws_ext_sales_price) as itemrevenue
+ ,sum(ws_ext_sales_price)*100/sum(sum(ws_ext_sales_price)) over
+ (partition by i_class) as revenueratio
+from
+ web_sales
+ ,item
+ ,date_dim
+where
+ ws_item_sk = i_item_sk
+ and i_category in ('Men', 'Books', 'Electronics')
+ and ws_sold_date_sk = d_date_sk
+ and d_date between cast('2001-06-15' as date)
+ and (cast('2001-06-15' as date) + 30 days)
+group by
+ i_item_id
+ ,i_item_desc
+ ,i_category
+ ,i_class
+ ,i_current_price
+order by
+ i_category
+ ,i_class
+ ,i_item_id
+ ,i_item_desc
+ ,revenueratio
+limit 100;
+
+-- end query 12 in stream 0 using template query12.tpl
+-- start query 13 in stream 0 using template query13.tpl
+select avg(ss_quantity)
+ ,avg(ss_ext_sales_price)
+ ,avg(ss_ext_wholesale_cost)
+ ,sum(ss_ext_wholesale_cost)
+ from store_sales
+ ,store
+ ,customer_demographics
+ ,household_demographics
+ ,customer_address
+ ,date_dim
+ where s_store_sk = ss_store_sk
+ and ss_sold_date_sk = d_date_sk and d_year = 2001
+ and((ss_hdemo_sk=hd_demo_sk
+ and cd_demo_sk = ss_cdemo_sk
+ and cd_marital_status = 'M'
+ and cd_education_status = 'College'
+ and ss_sales_price between 100.00 and 150.00
+ and hd_dep_count = 3
+ )or
+ (ss_hdemo_sk=hd_demo_sk
+ and cd_demo_sk = ss_cdemo_sk
+ and cd_marital_status = 'D'
+ and cd_education_status = 'Primary'
+ and ss_sales_price between 50.00 and 100.00
+ and hd_dep_count = 1
+ ) or
+ (ss_hdemo_sk=hd_demo_sk
+ and cd_demo_sk = ss_cdemo_sk
+ and cd_marital_status = 'W'
+ and cd_education_status = '2 yr Degree'
+ and ss_sales_price between 150.00 and 200.00
+ and hd_dep_count = 1
+ ))
+ and((ss_addr_sk = ca_address_sk
+ and ca_country = 'United States'
+ and ca_state in ('IL', 'TN', 'TX')
+ and ss_net_profit between 100 and 200
+ ) or
+ (ss_addr_sk = ca_address_sk
+ and ca_country = 'United States'
+ and ca_state in ('WY', 'OH', 'ID')
+ and ss_net_profit between 150 and 300
+ ) or
+ (ss_addr_sk = ca_address_sk
+ and ca_country = 'United States'
+ and ca_state in ('MS', 'SC', 'IA')
+ and ss_net_profit between 50 and 250
+ ))
+;
+
+-- end query 13 in stream 0 using template query13.tpl
+-- start query 14 in stream 0 using template query14.tpl
+with cross_items as
+ (select i_item_sk ss_item_sk
+ from item,
+ (select iss.i_brand_id brand_id
+ ,iss.i_class_id class_id
+ ,iss.i_category_id category_id
+ from store_sales
+ ,item iss
+ ,date_dim d1
+ where ss_item_sk = iss.i_item_sk
+ and ss_sold_date_sk = d1.d_date_sk
+ and d1.d_year between 1999 AND 1999 + 2
+ intersect
+ select ics.i_brand_id
+ ,ics.i_class_id
+ ,ics.i_category_id
+ from catalog_sales
+ ,item ics
+ ,date_dim d2
+ where cs_item_sk = ics.i_item_sk
+ and cs_sold_date_sk = d2.d_date_sk
+ and d2.d_year between 1999 AND 1999 + 2
+ intersect
+ select iws.i_brand_id
+ ,iws.i_class_id
+ ,iws.i_category_id
+ from web_sales
+ ,item iws
+ ,date_dim d3
+ where ws_item_sk = iws.i_item_sk
+ and ws_sold_date_sk = d3.d_date_sk
+ and d3.d_year between 1999 AND 1999 + 2)
+ where i_brand_id = brand_id
+ and i_class_id = class_id
+ and i_category_id = category_id
+),
+ avg_sales as
+ (select avg(quantity*list_price) average_sales
+ from (select ss_quantity quantity
+ ,ss_list_price list_price
+ from store_sales
+ ,date_dim
+ where ss_sold_date_sk = d_date_sk
+ and d_year between 1999 and 1999 + 2
+ union all
+ select cs_quantity quantity
+ ,cs_list_price list_price
+ from catalog_sales
+ ,date_dim
+ where cs_sold_date_sk = d_date_sk
+ and d_year between 1999 and 1999 + 2
+ union all
+ select ws_quantity quantity
+ ,ws_list_price list_price
+ from web_sales
+ ,date_dim
+ where ws_sold_date_sk = d_date_sk
+ and d_year between 1999 and 1999 + 2) x)
+ select channel, i_brand_id,i_class_id,i_category_id,sum(sales), sum(number_sales)
+ from(
+ select 'store' channel, i_brand_id,i_class_id
+ ,i_category_id,sum(ss_quantity*ss_list_price) sales
+ , count(*) number_sales
+ from store_sales
+ ,item
+ ,date_dim
+ where ss_item_sk in (select ss_item_sk from cross_items)
+ and ss_item_sk = i_item_sk
+ and ss_sold_date_sk = d_date_sk
+ and d_year = 1999+2
+ and d_moy = 11
+ group by i_brand_id,i_class_id,i_category_id
+ having sum(ss_quantity*ss_list_price) > (select average_sales from avg_sales)
+ union all
+ select 'catalog' channel, i_brand_id,i_class_id,i_category_id, sum(cs_quantity*cs_list_price) sales, count(*) number_sales
+ from catalog_sales
+ ,item
+ ,date_dim
+ where cs_item_sk in (select ss_item_sk from cross_items)
+ and cs_item_sk = i_item_sk
+ and cs_sold_date_sk = d_date_sk
+ and d_year = 1999+2
+ and d_moy = 11
+ group by i_brand_id,i_class_id,i_category_id
+ having sum(cs_quantity*cs_list_price) > (select average_sales from avg_sales)
+ union all
+ select 'web' channel, i_brand_id,i_class_id,i_category_id, sum(ws_quantity*ws_list_price) sales , count(*) number_sales
+ from web_sales
+ ,item
+ ,date_dim
+ where ws_item_sk in (select ss_item_sk from cross_items)
+ and ws_item_sk = i_item_sk
+ and ws_sold_date_sk = d_date_sk
+ and d_year = 1999+2
+ and d_moy = 11
+ group by i_brand_id,i_class_id,i_category_id
+ having sum(ws_quantity*ws_list_price) > (select average_sales from avg_sales)
+ ) y
+ group by rollup (channel, i_brand_id,i_class_id,i_category_id)
+ order by channel,i_brand_id,i_class_id,i_category_id
+ limit 100;
+with cross_items as
+ (select i_item_sk ss_item_sk
+ from item,
+ (select iss.i_brand_id brand_id
+ ,iss.i_class_id class_id
+ ,iss.i_category_id category_id
+ from store_sales
+ ,item iss
+ ,date_dim d1
+ where ss_item_sk = iss.i_item_sk
+ and ss_sold_date_sk = d1.d_date_sk
+ and d1.d_year between 1999 AND 1999 + 2
+ intersect
+ select ics.i_brand_id
+ ,ics.i_class_id
+ ,ics.i_category_id
+ from catalog_sales
+ ,item ics
+ ,date_dim d2
+ where cs_item_sk = ics.i_item_sk
+ and cs_sold_date_sk = d2.d_date_sk
+ and d2.d_year between 1999 AND 1999 + 2
+ intersect
+ select iws.i_brand_id
+ ,iws.i_class_id
+ ,iws.i_category_id
+ from web_sales
+ ,item iws
+ ,date_dim d3
+ where ws_item_sk = iws.i_item_sk
+ and ws_sold_date_sk = d3.d_date_sk
+ and d3.d_year between 1999 AND 1999 + 2) x
+ where i_brand_id = brand_id
+ and i_class_id = class_id
+ and i_category_id = category_id
+),
+ avg_sales as
+(select avg(quantity*list_price) average_sales
+ from (select ss_quantity quantity
+ ,ss_list_price list_price
+ from store_sales
+ ,date_dim
+ where ss_sold_date_sk = d_date_sk
+ and d_year between 1999 and 1999 + 2
+ union all
+ select cs_quantity quantity
+ ,cs_list_price list_price
+ from catalog_sales
+ ,date_dim
+ where cs_sold_date_sk = d_date_sk
+ and d_year between 1999 and 1999 + 2
+ union all
+ select ws_quantity quantity
+ ,ws_list_price list_price
+ from web_sales
+ ,date_dim
+ where ws_sold_date_sk = d_date_sk
+ and d_year between 1999 and 1999 + 2) x)
+ select this_year.channel ty_channel
+ ,this_year.i_brand_id ty_brand
+ ,this_year.i_class_id ty_class
+ ,this_year.i_category_id ty_category
+ ,this_year.sales ty_sales
+ ,this_year.number_sales ty_number_sales
+ ,last_year.channel ly_channel
+ ,last_year.i_brand_id ly_brand
+ ,last_year.i_class_id ly_class
+ ,last_year.i_category_id ly_category
+ ,last_year.sales ly_sales
+ ,last_year.number_sales ly_number_sales
+ from
+ (select 'store' channel, i_brand_id,i_class_id,i_category_id
+ ,sum(ss_quantity*ss_list_price) sales, count(*) number_sales
+ from store_sales
+ ,item
+ ,date_dim
+ where ss_item_sk in (select ss_item_sk from cross_items)
+ and ss_item_sk = i_item_sk
+ and ss_sold_date_sk = d_date_sk
+ and d_week_seq = (select d_week_seq
+ from date_dim
+ where d_year = 1999 + 1
+ and d_moy = 12
+ and d_dom = 3)
+ group by i_brand_id,i_class_id,i_category_id
+ having sum(ss_quantity*ss_list_price) > (select average_sales from avg_sales)) this_year,
+ (select 'store' channel, i_brand_id,i_class_id
+ ,i_category_id, sum(ss_quantity*ss_list_price) sales, count(*) number_sales
+ from store_sales
+ ,item
+ ,date_dim
+ where ss_item_sk in (select ss_item_sk from cross_items)
+ and ss_item_sk = i_item_sk
+ and ss_sold_date_sk = d_date_sk
+ and d_week_seq = (select d_week_seq
+ from date_dim
+ where d_year = 1999
+ and d_moy = 12
+ and d_dom = 3)
+ group by i_brand_id,i_class_id,i_category_id
+ having sum(ss_quantity*ss_list_price) > (select average_sales from avg_sales)) last_year
+ where this_year.i_brand_id= last_year.i_brand_id
+ and this_year.i_class_id = last_year.i_class_id
+ and this_year.i_category_id = last_year.i_category_id
+ order by this_year.channel, this_year.i_brand_id, this_year.i_class_id, this_year.i_category_id
+ limit 100;
+
+-- end query 14 in stream 0 using template query14.tpl
+-- start query 15 in stream 0 using template query15.tpl
+select ca_zip
+ ,sum(cs_sales_price)
+ from catalog_sales
+ ,customer
+ ,customer_address
+ ,date_dim
+ where cs_bill_customer_sk = c_customer_sk
+ and c_current_addr_sk = ca_address_sk
+ and ( substr(ca_zip,1,5) in ('85669', '86197','88274','83405','86475',
+ '85392', '85460', '80348', '81792')
+ or ca_state in ('CA','WA','GA')
+ or cs_sales_price > 500)
+ and cs_sold_date_sk = d_date_sk
+ and d_qoy = 2 and d_year = 2001
+ group by ca_zip
+ order by ca_zip
+ limit 100;
+
+-- end query 15 in stream 0 using template query15.tpl
+-- start query 16 in stream 0 using template query16.tpl
+select
+ count(distinct cs_order_number) as "order count"
+ ,sum(cs_ext_ship_cost) as "total shipping cost"
+ ,sum(cs_net_profit) as "total net profit"
+from
+ catalog_sales cs1
+ ,date_dim
+ ,customer_address
+ ,call_center
+where
+ d_date between '2002-4-01' and
+ (cast('2002-4-01' as date) + 60 days)
+and cs1.cs_ship_date_sk = d_date_sk
+and cs1.cs_ship_addr_sk = ca_address_sk
+and ca_state = 'PA'
+and cs1.cs_call_center_sk = cc_call_center_sk
+and cc_county in ('Williamson County','Williamson County','Williamson County','Williamson County',
+ 'Williamson County'
+)
+and exists (select *
+ from catalog_sales cs2
+ where cs1.cs_order_number = cs2.cs_order_number
+ and cs1.cs_warehouse_sk <> cs2.cs_warehouse_sk)
+and not exists(select *
+ from catalog_returns cr1
+ where cs1.cs_order_number = cr1.cr_order_number)
+order by count(distinct cs_order_number)
+limit 100;
+
+-- end query 16 in stream 0 using template query16.tpl
+-- start query 17 in stream 0 using template query17.tpl
+select i_item_id
+ ,i_item_desc
+ ,s_state
+ ,count(ss_quantity) as store_sales_quantitycount
+ ,avg(ss_quantity) as store_sales_quantityave
+ ,stddev_samp(ss_quantity) as store_sales_quantitystdev
+ ,stddev_samp(ss_quantity)/avg(ss_quantity) as store_sales_quantitycov
+ ,count(sr_return_quantity) as store_returns_quantitycount
+ ,avg(sr_return_quantity) as store_returns_quantityave
+ ,stddev_samp(sr_return_quantity) as store_returns_quantitystdev
+ ,stddev_samp(sr_return_quantity)/avg(sr_return_quantity) as store_returns_quantitycov
+ ,count(cs_quantity) as catalog_sales_quantitycount ,avg(cs_quantity) as catalog_sales_quantityave
+ ,stddev_samp(cs_quantity) as catalog_sales_quantitystdev
+ ,stddev_samp(cs_quantity)/avg(cs_quantity) as catalog_sales_quantitycov
+ from store_sales
+ ,store_returns
+ ,catalog_sales
+ ,date_dim d1
+ ,date_dim d2
+ ,date_dim d3
+ ,store
+ ,item
+ where d1.d_quarter_name = '2001Q1'
+ and d1.d_date_sk = ss_sold_date_sk
+ and i_item_sk = ss_item_sk
+ and s_store_sk = ss_store_sk
+ and ss_customer_sk = sr_customer_sk
+ and ss_item_sk = sr_item_sk
+ and ss_ticket_number = sr_ticket_number
+ and sr_returned_date_sk = d2.d_date_sk
+ and d2.d_quarter_name in ('2001Q1','2001Q2','2001Q3')
+ and sr_customer_sk = cs_bill_customer_sk
+ and sr_item_sk = cs_item_sk
+ and cs_sold_date_sk = d3.d_date_sk
+ and d3.d_quarter_name in ('2001Q1','2001Q2','2001Q3')
+ group by i_item_id
+ ,i_item_desc
+ ,s_state
+ order by i_item_id
+ ,i_item_desc
+ ,s_state
+limit 100;
+
+-- end query 17 in stream 0 using template query17.tpl
+-- start query 18 in stream 0 using template query18.tpl
+select i_item_id,
+ ca_country,
+ ca_state,
+ ca_county,
+ avg( cast(cs_quantity as decimal(12,2))) agg1,
+ avg( cast(cs_list_price as decimal(12,2))) agg2,
+ avg( cast(cs_coupon_amt as decimal(12,2))) agg3,
+ avg( cast(cs_sales_price as decimal(12,2))) agg4,
+ avg( cast(cs_net_profit as decimal(12,2))) agg5,
+ avg( cast(c_birth_year as decimal(12,2))) agg6,
+ avg( cast(cd1.cd_dep_count as decimal(12,2))) agg7
+ from catalog_sales, customer_demographics cd1,
+ customer_demographics cd2, customer, customer_address, date_dim, item
+ where cs_sold_date_sk = d_date_sk and
+ cs_item_sk = i_item_sk and
+ cs_bill_cdemo_sk = cd1.cd_demo_sk and
+ cs_bill_customer_sk = c_customer_sk and
+ cd1.cd_gender = 'F' and
+ cd1.cd_education_status = 'Primary' and
+ c_current_cdemo_sk = cd2.cd_demo_sk and
+ c_current_addr_sk = ca_address_sk and
+ c_birth_month in (1,3,7,11,10,4) and
+ d_year = 2001 and
+ ca_state in ('AL','MO','TN'
+ ,'GA','MT','IN','CA')
+ group by rollup (i_item_id, ca_country, ca_state, ca_county)
+ order by ca_country,
+ ca_state,
+ ca_county,
+ i_item_id
+ limit 100;
+
+-- end query 18 in stream 0 using template query18.tpl
+-- start query 19 in stream 0 using template query19.tpl
+select i_brand_id brand_id, i_brand brand, i_manufact_id, i_manufact,
+ sum(ss_ext_sales_price) ext_price
+ from date_dim, store_sales, item,customer,customer_address,store
+ where d_date_sk = ss_sold_date_sk
+ and ss_item_sk = i_item_sk
+ and i_manager_id=14
+ and d_moy=11
+ and d_year=2002
+ and ss_customer_sk = c_customer_sk
+ and c_current_addr_sk = ca_address_sk
+ and substr(ca_zip,1,5) <> substr(s_zip,1,5)
+ and ss_store_sk = s_store_sk
+ group by i_brand
+ ,i_brand_id
+ ,i_manufact_id
+ ,i_manufact
+ order by ext_price desc
+ ,i_brand
+ ,i_brand_id
+ ,i_manufact_id
+ ,i_manufact
+limit 100 ;
+
+-- end query 19 in stream 0 using template query19.tpl
+-- start query 20 in stream 0 using template query20.tpl
+select i_item_id
+ ,i_item_desc
+ ,i_category
+ ,i_class
+ ,i_current_price
+ ,sum(cs_ext_sales_price) as itemrevenue
+ ,sum(cs_ext_sales_price)*100/sum(sum(cs_ext_sales_price)) over
+ (partition by i_class) as revenueratio
+ from catalog_sales
+ ,item
+ ,date_dim
+ where cs_item_sk = i_item_sk
+ and i_category in ('Books', 'Music', 'Sports')
+ and cs_sold_date_sk = d_date_sk
+ and d_date between cast('2002-06-18' as date)
+ and (cast('2002-06-18' as date) + 30 days)
+ group by i_item_id
+ ,i_item_desc
+ ,i_category
+ ,i_class
+ ,i_current_price
+ order by i_category
+ ,i_class
+ ,i_item_id
+ ,i_item_desc
+ ,revenueratio
+limit 100;
+
+-- end query 20 in stream 0 using template query20.tpl
+-- start query 21 in stream 0 using template query21.tpl
+select *
+ from(select w_warehouse_name
+ ,i_item_id
+ ,sum(case when (cast(d_date as date) < cast ('1999-06-22' as date))
+ then inv_quantity_on_hand
+ else 0 end) as inv_before
+ ,sum(case when (cast(d_date as date) >= cast ('1999-06-22' as date))
+ then inv_quantity_on_hand
+ else 0 end) as inv_after
+ from inventory
+ ,warehouse
+ ,item
+ ,date_dim
+ where i_current_price between 0.99 and 1.49
+ and i_item_sk = inv_item_sk
+ and inv_warehouse_sk = w_warehouse_sk
+ and inv_date_sk = d_date_sk
+ and d_date between (cast ('1999-06-22' as date) - 30 days)
+ and (cast ('1999-06-22' as date) + 30 days)
+ group by w_warehouse_name, i_item_id) x
+ where (case when inv_before > 0
+ then inv_after / inv_before
+ else null
+ end) between 2.0/3.0 and 3.0/2.0
+ order by w_warehouse_name
+ ,i_item_id
+ limit 100;
+
+-- end query 21 in stream 0 using template query21.tpl
+-- start query 22 in stream 0 using template query22.tpl
+select i_product_name
+ ,i_brand
+ ,i_class
+ ,i_category
+ ,avg(inv_quantity_on_hand) qoh
+ from inventory
+ ,date_dim
+ ,item
+ where inv_date_sk=d_date_sk
+ and inv_item_sk=i_item_sk
+ and d_month_seq between 1200 and 1200 + 11
+ group by rollup(i_product_name
+ ,i_brand
+ ,i_class
+ ,i_category)
+order by qoh, i_product_name, i_brand, i_class, i_category
+limit 100;
+
+-- end query 22 in stream 0 using template query22.tpl
+-- start query 23 in stream 0 using template query23.tpl
+with frequent_ss_items as
+ (select substr(i_item_desc,1,30) itemdesc,i_item_sk item_sk,d_date solddate,count(*) cnt
+ from store_sales
+ ,date_dim
+ ,item
+ where ss_sold_date_sk = d_date_sk
+ and ss_item_sk = i_item_sk
+ and d_year in (2000,2000+1,2000+2,2000+3)
+ group by substr(i_item_desc,1,30),i_item_sk,d_date
+ having count(*) >4),
+ max_store_sales as
+ (select max(csales) tpcds_cmax
+ from (select c_customer_sk,sum(ss_quantity*ss_sales_price) csales
+ from store_sales
+ ,customer
+ ,date_dim
+ where ss_customer_sk = c_customer_sk
+ and ss_sold_date_sk = d_date_sk
+ and d_year in (2000,2000+1,2000+2,2000+3)
+ group by c_customer_sk)),
+ best_ss_customer as
+ (select c_customer_sk,sum(ss_quantity*ss_sales_price) ssales
+ from store_sales
+ ,customer
+ where ss_customer_sk = c_customer_sk
+ group by c_customer_sk
+ having sum(ss_quantity*ss_sales_price) > (95/100.0) * (select
+ *
+from
+ max_store_sales))
+ select sum(sales)
+ from (select cs_quantity*cs_list_price sales
+ from catalog_sales
+ ,date_dim
+ where d_year = 2000
+ and d_moy = 7
+ and cs_sold_date_sk = d_date_sk
+ and cs_item_sk in (select item_sk from frequent_ss_items)
+ and cs_bill_customer_sk in (select c_customer_sk from best_ss_customer)
+ union all
+ select ws_quantity*ws_list_price sales
+ from web_sales
+ ,date_dim
+ where d_year = 2000
+ and d_moy = 7
+ and ws_sold_date_sk = d_date_sk
+ and ws_item_sk in (select item_sk from frequent_ss_items)
+ and ws_bill_customer_sk in (select c_customer_sk from best_ss_customer))
+ limit 100;
+with frequent_ss_items as
+ (select substr(i_item_desc,1,30) itemdesc,i_item_sk item_sk,d_date solddate,count(*) cnt
+ from store_sales
+ ,date_dim
+ ,item
+ where ss_sold_date_sk = d_date_sk
+ and ss_item_sk = i_item_sk
+ and d_year in (2000,2000 + 1,2000 + 2,2000 + 3)
+ group by substr(i_item_desc,1,30),i_item_sk,d_date
+ having count(*) >4),
+ max_store_sales as
+ (select max(csales) tpcds_cmax
+ from (select c_customer_sk,sum(ss_quantity*ss_sales_price) csales
+ from store_sales
+ ,customer
+ ,date_dim
+ where ss_customer_sk = c_customer_sk
+ and ss_sold_date_sk = d_date_sk
+ and d_year in (2000,2000+1,2000+2,2000+3)
+ group by c_customer_sk)),
+ best_ss_customer as
+ (select c_customer_sk,sum(ss_quantity*ss_sales_price) ssales
+ from store_sales
+ ,customer
+ where ss_customer_sk = c_customer_sk
+ group by c_customer_sk
+ having sum(ss_quantity*ss_sales_price) > (95/100.0) * (select
+ *
+ from max_store_sales))
+ select c_last_name,c_first_name,sales
+ from (select c_last_name,c_first_name,sum(cs_quantity*cs_list_price) sales
+ from catalog_sales
+ ,customer
+ ,date_dim
+ where d_year = 2000
+ and d_moy = 7
+ and cs_sold_date_sk = d_date_sk
+ and cs_item_sk in (select item_sk from frequent_ss_items)
+ and cs_bill_customer_sk in (select c_customer_sk from best_ss_customer)
+ and cs_bill_customer_sk = c_customer_sk
+ group by c_last_name,c_first_name
+ union all
+ select c_last_name,c_first_name,sum(ws_quantity*ws_list_price) sales
+ from web_sales
+ ,customer
+ ,date_dim
+ where d_year = 2000
+ and d_moy = 7
+ and ws_sold_date_sk = d_date_sk
+ and ws_item_sk in (select item_sk from frequent_ss_items)
+ and ws_bill_customer_sk in (select c_customer_sk from best_ss_customer)
+ and ws_bill_customer_sk = c_customer_sk
+ group by c_last_name,c_first_name)
+ order by c_last_name,c_first_name,sales
+ limit 100;
+
+-- end query 23 in stream 0 using template query23.tpl
+-- start query 24 in stream 0 using template query24.tpl
+with ssales as
+(select c_last_name
+ ,c_first_name
+ ,s_store_name
+ ,ca_state
+ ,s_state
+ ,i_color
+ ,i_current_price
+ ,i_manager_id
+ ,i_units
+ ,i_size
+ ,sum(ss_net_paid) netpaid
+from store_sales
+ ,store_returns
+ ,store
+ ,item
+ ,customer
+ ,customer_address
+where ss_ticket_number = sr_ticket_number
+ and ss_item_sk = sr_item_sk
+ and ss_customer_sk = c_customer_sk
+ and ss_item_sk = i_item_sk
+ and ss_store_sk = s_store_sk
+ and c_current_addr_sk = ca_address_sk
+ and c_birth_country <> upper(ca_country)
+ and s_zip = ca_zip
+and s_market_id=5
+group by c_last_name
+ ,c_first_name
+ ,s_store_name
+ ,ca_state
+ ,s_state
+ ,i_color
+ ,i_current_price
+ ,i_manager_id
+ ,i_units
+ ,i_size)
+select c_last_name
+ ,c_first_name
+ ,s_store_name
+ ,sum(netpaid) paid
+from ssales
+where i_color = 'aquamarine'
+group by c_last_name
+ ,c_first_name
+ ,s_store_name
+having sum(netpaid) > (select 0.05*avg(netpaid)
+ from ssales)
+order by c_last_name
+ ,c_first_name
+ ,s_store_name
+;
+with ssales as
+(select c_last_name
+ ,c_first_name
+ ,s_store_name
+ ,ca_state
+ ,s_state
+ ,i_color
+ ,i_current_price
+ ,i_manager_id
+ ,i_units
+ ,i_size
+ ,sum(ss_net_paid) netpaid
+from store_sales
+ ,store_returns
+ ,store
+ ,item
+ ,customer
+ ,customer_address
+where ss_ticket_number = sr_ticket_number
+ and ss_item_sk = sr_item_sk
+ and ss_customer_sk = c_customer_sk
+ and ss_item_sk = i_item_sk
+ and ss_store_sk = s_store_sk
+ and c_current_addr_sk = ca_address_sk
+ and c_birth_country <> upper(ca_country)
+ and s_zip = ca_zip
+ and s_market_id = 5
+group by c_last_name
+ ,c_first_name
+ ,s_store_name
+ ,ca_state
+ ,s_state
+ ,i_color
+ ,i_current_price
+ ,i_manager_id
+ ,i_units
+ ,i_size)
+select c_last_name
+ ,c_first_name
+ ,s_store_name
+ ,sum(netpaid) paid
+from ssales
+where i_color = 'seashell'
+group by c_last_name
+ ,c_first_name
+ ,s_store_name
+having sum(netpaid) > (select 0.05*avg(netpaid)
+ from ssales)
+order by c_last_name
+ ,c_first_name
+ ,s_store_name
+;
+
+-- end query 24 in stream 0 using template query24.tpl
+-- start query 25 in stream 0 using template query25.tpl
+select
+ i_item_id
+ ,i_item_desc
+ ,s_store_id
+ ,s_store_name
+ ,max(ss_net_profit) as store_sales_profit
+ ,max(sr_net_loss) as store_returns_loss
+ ,max(cs_net_profit) as catalog_sales_profit
+ from
+ store_sales
+ ,store_returns
+ ,catalog_sales
+ ,date_dim d1
+ ,date_dim d2
+ ,date_dim d3
+ ,store
+ ,item
+ where
+ d1.d_moy = 4
+ and d1.d_year = 1999
+ and d1.d_date_sk = ss_sold_date_sk
+ and i_item_sk = ss_item_sk
+ and s_store_sk = ss_store_sk
+ and ss_customer_sk = sr_customer_sk
+ and ss_item_sk = sr_item_sk
+ and ss_ticket_number = sr_ticket_number
+ and sr_returned_date_sk = d2.d_date_sk
+ and d2.d_moy between 4 and 10
+ and d2.d_year = 1999
+ and sr_customer_sk = cs_bill_customer_sk
+ and sr_item_sk = cs_item_sk
+ and cs_sold_date_sk = d3.d_date_sk
+ and d3.d_moy between 4 and 10
+ and d3.d_year = 1999
+ group by
+ i_item_id
+ ,i_item_desc
+ ,s_store_id
+ ,s_store_name
+ order by
+ i_item_id
+ ,i_item_desc
+ ,s_store_id
+ ,s_store_name
+ limit 100;
+
+-- end query 25 in stream 0 using template query25.tpl
+-- start query 26 in stream 0 using template query26.tpl
+select i_item_id,
+ avg(cs_quantity) agg1,
+ avg(cs_list_price) agg2,
+ avg(cs_coupon_amt) agg3,
+ avg(cs_sales_price) agg4
+ from catalog_sales, customer_demographics, date_dim, item, promotion
+ where cs_sold_date_sk = d_date_sk and
+ cs_item_sk = i_item_sk and
+ cs_bill_cdemo_sk = cd_demo_sk and
+ cs_promo_sk = p_promo_sk and
+ cd_gender = 'M' and
+ cd_marital_status = 'W' and
+ cd_education_status = 'Unknown' and
+ (p_channel_email = 'N' or p_channel_event = 'N') and
+ d_year = 2002
+ group by i_item_id
+ order by i_item_id
+ limit 100;
+
+-- end query 26 in stream 0 using template query26.tpl
+-- start query 27 in stream 0 using template query27.tpl
+select i_item_id,
+ s_state, grouping(s_state) g_state,
+ avg(ss_quantity) agg1,
+ avg(ss_list_price) agg2,
+ avg(ss_coupon_amt) agg3,
+ avg(ss_sales_price) agg4
+ from store_sales, customer_demographics, date_dim, store, item
+ where ss_sold_date_sk = d_date_sk and
+ ss_item_sk = i_item_sk and
+ ss_store_sk = s_store_sk and
+ ss_cdemo_sk = cd_demo_sk and
+ cd_gender = 'M' and
+ cd_marital_status = 'W' and
+ cd_education_status = 'Secondary' and
+ d_year = 1999 and
+ s_state in ('TN','TN', 'TN', 'TN', 'TN', 'TN')
+ group by rollup (i_item_id, s_state)
+ order by i_item_id
+ ,s_state
+ limit 100;
+
+-- end query 27 in stream 0 using template query27.tpl
+-- start query 28 in stream 0 using template query28.tpl
+select *
+from (select avg(ss_list_price) B1_LP
+ ,count(ss_list_price) B1_CNT
+ ,count(distinct ss_list_price) B1_CNTD
+ from store_sales
+ where ss_quantity between 0 and 5
+ and (ss_list_price between 107 and 107+10
+ or ss_coupon_amt between 1319 and 1319+1000
+ or ss_wholesale_cost between 60 and 60+20)) B1,
+ (select avg(ss_list_price) B2_LP
+ ,count(ss_list_price) B2_CNT
+ ,count(distinct ss_list_price) B2_CNTD
+ from store_sales
+ where ss_quantity between 6 and 10
+ and (ss_list_price between 23 and 23+10
+ or ss_coupon_amt between 825 and 825+1000
+ or ss_wholesale_cost between 43 and 43+20)) B2,
+ (select avg(ss_list_price) B3_LP
+ ,count(ss_list_price) B3_CNT
+ ,count(distinct ss_list_price) B3_CNTD
+ from store_sales
+ where ss_quantity between 11 and 15
+ and (ss_list_price between 74 and 74+10
+ or ss_coupon_amt between 4381 and 4381+1000
+ or ss_wholesale_cost between 57 and 57+20)) B3,
+ (select avg(ss_list_price) B4_LP
+ ,count(ss_list_price) B4_CNT
+ ,count(distinct ss_list_price) B4_CNTD
+ from store_sales
+ where ss_quantity between 16 and 20
+ and (ss_list_price between 89 and 89+10
+ or ss_coupon_amt between 3117 and 3117+1000
+ or ss_wholesale_cost between 68 and 68+20)) B4,
+ (select avg(ss_list_price) B5_LP
+ ,count(ss_list_price) B5_CNT
+ ,count(distinct ss_list_price) B5_CNTD
+ from store_sales
+ where ss_quantity between 21 and 25
+ and (ss_list_price between 58 and 58+10
+ or ss_coupon_amt between 9402 and 9402+1000
+ or ss_wholesale_cost between 38 and 38+20)) B5,
+ (select avg(ss_list_price) B6_LP
+ ,count(ss_list_price) B6_CNT
+ ,count(distinct ss_list_price) B6_CNTD
+ from store_sales
+ where ss_quantity between 26 and 30
+ and (ss_list_price between 64 and 64+10
+ or ss_coupon_amt between 5792 and 5792+1000
+ or ss_wholesale_cost between 73 and 73+20)) B6
+limit 100;
+
+-- end query 28 in stream 0 using template query28.tpl
+-- start query 29 in stream 0 using template query29.tpl
+select
+ i_item_id
+ ,i_item_desc
+ ,s_store_id
+ ,s_store_name
+ ,max(ss_quantity) as store_sales_quantity
+ ,max(sr_return_quantity) as store_returns_quantity
+ ,max(cs_quantity) as catalog_sales_quantity
+ from
+ store_sales
+ ,store_returns
+ ,catalog_sales
+ ,date_dim d1
+ ,date_dim d2
+ ,date_dim d3
+ ,store
+ ,item
+ where
+ d1.d_moy = 4
+ and d1.d_year = 1998
+ and d1.d_date_sk = ss_sold_date_sk
+ and i_item_sk = ss_item_sk
+ and s_store_sk = ss_store_sk
+ and ss_customer_sk = sr_customer_sk
+ and ss_item_sk = sr_item_sk
+ and ss_ticket_number = sr_ticket_number
+ and sr_returned_date_sk = d2.d_date_sk
+ and d2.d_moy between 4 and 4 + 3
+ and d2.d_year = 1998
+ and sr_customer_sk = cs_bill_customer_sk
+ and sr_item_sk = cs_item_sk
+ and cs_sold_date_sk = d3.d_date_sk
+ and d3.d_year in (1998,1998+1,1998+2)
+ group by
+ i_item_id
+ ,i_item_desc
+ ,s_store_id
+ ,s_store_name
+ order by
+ i_item_id
+ ,i_item_desc
+ ,s_store_id
+ ,s_store_name
+ limit 100;
+
+-- end query 29 in stream 0 using template query29.tpl
+-- start query 30 in stream 0 using template query30.tpl
+with customer_total_return as
+ (select wr_returning_customer_sk as ctr_customer_sk
+ ,ca_state as ctr_state,
+ sum(wr_return_amt) as ctr_total_return
+ from web_returns
+ ,date_dim
+ ,customer_address
+ where wr_returned_date_sk = d_date_sk
+ and d_year =2000
+ and wr_returning_addr_sk = ca_address_sk
+ group by wr_returning_customer_sk
+ ,ca_state)
+ select c_customer_id,c_salutation,c_first_name,c_last_name,c_preferred_cust_flag
+ ,c_birth_day,c_birth_month,c_birth_year,c_birth_country,c_login,c_email_address
+ ,c_last_review_date_sk,ctr_total_return
+ from customer_total_return ctr1
+ ,customer_address
+ ,customer
+ where ctr1.ctr_total_return > (select avg(ctr_total_return)*1.2
+ from customer_total_return ctr2
+ where ctr1.ctr_state = ctr2.ctr_state)
+ and ca_address_sk = c_current_addr_sk
+ and ca_state = 'AR'
+ and ctr1.ctr_customer_sk = c_customer_sk
+ order by c_customer_id,c_salutation,c_first_name,c_last_name,c_preferred_cust_flag
+ ,c_birth_day,c_birth_month,c_birth_year,c_birth_country,c_login,c_email_address
+ ,c_last_review_date_sk,ctr_total_return
+limit 100;
+
+-- end query 30 in stream 0 using template query30.tpl
+-- start query 31 in stream 0 using template query31.tpl
+with ss as
+ (select ca_county,d_qoy, d_year,sum(ss_ext_sales_price) as store_sales
+ from store_sales,date_dim,customer_address
+ where ss_sold_date_sk = d_date_sk
+ and ss_addr_sk=ca_address_sk
+ group by ca_county,d_qoy, d_year),
+ ws as
+ (select ca_county,d_qoy, d_year,sum(ws_ext_sales_price) as web_sales
+ from web_sales,date_dim,customer_address
+ where ws_sold_date_sk = d_date_sk
+ and ws_bill_addr_sk=ca_address_sk
+ group by ca_county,d_qoy, d_year)
+ select
+ ss1.ca_county
+ ,ss1.d_year
+ ,ws2.web_sales/ws1.web_sales web_q1_q2_increase
+ ,ss2.store_sales/ss1.store_sales store_q1_q2_increase
+ ,ws3.web_sales/ws2.web_sales web_q2_q3_increase
+ ,ss3.store_sales/ss2.store_sales store_q2_q3_increase
+ from
+ ss ss1
+ ,ss ss2
+ ,ss ss3
+ ,ws ws1
+ ,ws ws2
+ ,ws ws3
+ where
+ ss1.d_qoy = 1
+ and ss1.d_year = 1999
+ and ss1.ca_county = ss2.ca_county
+ and ss2.d_qoy = 2
+ and ss2.d_year = 1999
+ and ss2.ca_county = ss3.ca_county
+ and ss3.d_qoy = 3
+ and ss3.d_year = 1999
+ and ss1.ca_county = ws1.ca_county
+ and ws1.d_qoy = 1
+ and ws1.d_year = 1999
+ and ws1.ca_county = ws2.ca_county
+ and ws2.d_qoy = 2
+ and ws2.d_year = 1999
+ and ws1.ca_county = ws3.ca_county
+ and ws3.d_qoy = 3
+ and ws3.d_year =1999
+ and case when ws1.web_sales > 0 then ws2.web_sales/ws1.web_sales else null end
+ > case when ss1.store_sales > 0 then ss2.store_sales/ss1.store_sales else null end
+ and case when ws2.web_sales > 0 then ws3.web_sales/ws2.web_sales else null end
+ > case when ss2.store_sales > 0 then ss3.store_sales/ss2.store_sales else null end
+ order by store_q2_q3_increase;
+
+-- end query 31 in stream 0 using template query31.tpl
+-- start query 32 in stream 0 using template query32.tpl
+select sum(cs_ext_discount_amt) as "excess discount amount"
+from
+ catalog_sales
+ ,item
+ ,date_dim
+where
+i_manufact_id = 722
+and i_item_sk = cs_item_sk
+and d_date between '2001-03-09' and
+ (cast('2001-03-09' as date) + 90 days)
+and d_date_sk = cs_sold_date_sk
+and cs_ext_discount_amt
+ > (
+ select
+ 1.3 * avg(cs_ext_discount_amt)
+ from
+ catalog_sales
+ ,date_dim
+ where
+ cs_item_sk = i_item_sk
+ and d_date between '2001-03-09' and
+ (cast('2001-03-09' as date) + 90 days)
+ and d_date_sk = cs_sold_date_sk
+ )
+limit 100;
+
+-- end query 32 in stream 0 using template query32.tpl
+-- start query 33 in stream 0 using template query33.tpl
+with ss as (
+ select
+ i_manufact_id,sum(ss_ext_sales_price) total_sales
+ from
+ store_sales,
+ date_dim,
+ customer_address,
+ item
+ where
+ i_manufact_id in (select
+ i_manufact_id
+from
+ item
+where i_category in ('Books'))
+ and ss_item_sk = i_item_sk
+ and ss_sold_date_sk = d_date_sk
+ and d_year = 2001
+ and d_moy = 3
+ and ss_addr_sk = ca_address_sk
+ and ca_gmt_offset = -5
+ group by i_manufact_id),
+ cs as (
+ select
+ i_manufact_id,sum(cs_ext_sales_price) total_sales
+ from
+ catalog_sales,
+ date_dim,
+ customer_address,
+ item
+ where
+ i_manufact_id in (select
+ i_manufact_id
+from
+ item
+where i_category in ('Books'))
+ and cs_item_sk = i_item_sk
+ and cs_sold_date_sk = d_date_sk
+ and d_year = 2001
+ and d_moy = 3
+ and cs_bill_addr_sk = ca_address_sk
+ and ca_gmt_offset = -5
+ group by i_manufact_id),
+ ws as (
+ select
+ i_manufact_id,sum(ws_ext_sales_price) total_sales
+ from
+ web_sales,
+ date_dim,
+ customer_address,
+ item
+ where
+ i_manufact_id in (select
+ i_manufact_id
+from
+ item
+where i_category in ('Books'))
+ and ws_item_sk = i_item_sk
+ and ws_sold_date_sk = d_date_sk
+ and d_year = 2001
+ and d_moy = 3
+ and ws_bill_addr_sk = ca_address_sk
+ and ca_gmt_offset = -5
+ group by i_manufact_id)
+ select i_manufact_id ,sum(total_sales) total_sales
+ from (select * from ss
+ union all
+ select * from cs
+ union all
+ select * from ws) tmp1
+ group by i_manufact_id
+ order by total_sales
+limit 100;
+
+-- end query 33 in stream 0 using template query33.tpl
+-- start query 34 in stream 0 using template query34.tpl
+select c_last_name
+ ,c_first_name
+ ,c_salutation
+ ,c_preferred_cust_flag
+ ,ss_ticket_number
+ ,cnt from
+ (select ss_ticket_number
+ ,ss_customer_sk
+ ,count(*) cnt
+ from store_sales,date_dim,store,household_demographics
+ where store_sales.ss_sold_date_sk = date_dim.d_date_sk
+ and store_sales.ss_store_sk = store.s_store_sk
+ and store_sales.ss_hdemo_sk = household_demographics.hd_demo_sk
+ and (date_dim.d_dom between 1 and 3 or date_dim.d_dom between 25 and 28)
+ and (household_demographics.hd_buy_potential = '1001-5000' or
+ household_demographics.hd_buy_potential = '0-500')
+ and household_demographics.hd_vehicle_count > 0
+ and (case when household_demographics.hd_vehicle_count > 0
+ then household_demographics.hd_dep_count/ household_demographics.hd_vehicle_count
+ else null
+ end) > 1.2
+ and date_dim.d_year in (2000,2000+1,2000+2)
+ and store.s_county in ('Williamson County','Williamson County','Williamson County','Williamson County',
+ 'Williamson County','Williamson County','Williamson County','Williamson County')
+ group by ss_ticket_number,ss_customer_sk) dn,customer
+ where ss_customer_sk = c_customer_sk
+ and cnt between 15 and 20
+ order by c_last_name,c_first_name,c_salutation,c_preferred_cust_flag desc, ss_ticket_number;
+
+-- end query 34 in stream 0 using template query34.tpl
+-- start query 35 in stream 0 using template query35.tpl
+select
+ ca_state,
+ cd_gender,
+ cd_marital_status,
+ cd_dep_count,
+ count(*) cnt1,
+ avg(cd_dep_count),
+ stddev_samp(cd_dep_count),
+ sum(cd_dep_count),
+ cd_dep_employed_count,
+ count(*) cnt2,
+ avg(cd_dep_employed_count),
+ stddev_samp(cd_dep_employed_count),
+ sum(cd_dep_employed_count),
+ cd_dep_college_count,
+ count(*) cnt3,
+ avg(cd_dep_college_count),
+ stddev_samp(cd_dep_college_count),
+ sum(cd_dep_college_count)
+ from
+ customer c,customer_address ca,customer_demographics
+ where
+ c.c_current_addr_sk = ca.ca_address_sk and
+ cd_demo_sk = c.c_current_cdemo_sk and
+ exists (select *
+ from store_sales,date_dim
+ where c.c_customer_sk = ss_customer_sk and
+ ss_sold_date_sk = d_date_sk and
+ d_year = 1999 and
+ d_qoy < 4) and
+ (exists (select *
+ from web_sales,date_dim
+ where c.c_customer_sk = ws_bill_customer_sk and
+ ws_sold_date_sk = d_date_sk and
+ d_year = 1999 and
+ d_qoy < 4) or
+ exists (select *
+ from catalog_sales,date_dim
+ where c.c_customer_sk = cs_ship_customer_sk and
+ cs_sold_date_sk = d_date_sk and
+ d_year = 1999 and
+ d_qoy < 4))
+ group by ca_state,
+ cd_gender,
+ cd_marital_status,
+ cd_dep_count,
+ cd_dep_employed_count,
+ cd_dep_college_count
+ order by ca_state,
+ cd_gender,
+ cd_marital_status,
+ cd_dep_count,
+ cd_dep_employed_count,
+ cd_dep_college_count
+ limit 100;
+
+-- end query 35 in stream 0 using template query35.tpl
+-- start query 36 in stream 0 using template query36.tpl
+select
+ sum(ss_net_profit)/sum(ss_ext_sales_price) as gross_margin
+ ,i_category
+ ,i_class
+ ,grouping(i_category)+grouping(i_class) as lochierarchy
+ ,rank() over (
+ partition by grouping(i_category)+grouping(i_class),
+ case when grouping(i_class) = 0 then i_category end
+ order by sum(ss_net_profit)/sum(ss_ext_sales_price) asc) as rank_within_parent
+ from
+ store_sales
+ ,date_dim d1
+ ,item
+ ,store
+ where
+ d1.d_year = 2000
+ and d1.d_date_sk = ss_sold_date_sk
+ and i_item_sk = ss_item_sk
+ and s_store_sk = ss_store_sk
+ and s_state in ('TN','TN','TN','TN',
+ 'TN','TN','TN','TN')
+ group by rollup(i_category,i_class)
+ order by
+ lochierarchy desc
+ ,case when lochierarchy = 0 then i_category end
+ ,rank_within_parent
+ limit 100;
+
+-- end query 36 in stream 0 using template query36.tpl
+-- start query 37 in stream 0 using template query37.tpl
+select i_item_id
+ ,i_item_desc
+ ,i_current_price
+ from item, inventory, date_dim, catalog_sales
+ where i_current_price between 29 and 29 + 30
+ and inv_item_sk = i_item_sk
+ and d_date_sk=inv_date_sk
+ and d_date between cast('2002-03-29' as date) and (cast('2002-03-29' as date) + 60 days)
+ and i_manufact_id in (705,742,777,944)
+ and inv_quantity_on_hand between 100 and 500
+ and cs_item_sk = i_item_sk
+ group by i_item_id,i_item_desc,i_current_price
+ order by i_item_id
+ limit 100;
+
+-- end query 37 in stream 0 using template query37.tpl
+-- start query 38 in stream 0 using template query38.tpl
+select count(*) from (
+ select distinct c_last_name, c_first_name, d_date
+ from store_sales, date_dim, customer
+ where store_sales.ss_sold_date_sk = date_dim.d_date_sk
+ and store_sales.ss_customer_sk = customer.c_customer_sk
+ and d_month_seq between 1189 and 1189 + 11
+ intersect
+ select distinct c_last_name, c_first_name, d_date
+ from catalog_sales, date_dim, customer
+ where catalog_sales.cs_sold_date_sk = date_dim.d_date_sk
+ and catalog_sales.cs_bill_customer_sk = customer.c_customer_sk
+ and d_month_seq between 1189 and 1189 + 11
+ intersect
+ select distinct c_last_name, c_first_name, d_date
+ from web_sales, date_dim, customer
+ where web_sales.ws_sold_date_sk = date_dim.d_date_sk
+ and web_sales.ws_bill_customer_sk = customer.c_customer_sk
+ and d_month_seq between 1189 and 1189 + 11
+) hot_cust
+limit 100;
+
+-- end query 38 in stream 0 using template query38.tpl
+-- start query 39 in stream 0 using template query39.tpl
+with inv as
+(select w_warehouse_name,w_warehouse_sk,i_item_sk,d_moy
+ ,stdev,mean, case mean when 0 then null else stdev/mean end cov
+ from(select w_warehouse_name,w_warehouse_sk,i_item_sk,d_moy
+ ,stddev_samp(inv_quantity_on_hand) stdev,avg(inv_quantity_on_hand) mean
+ from inventory
+ ,item
+ ,warehouse
+ ,date_dim
+ where inv_item_sk = i_item_sk
+ and inv_warehouse_sk = w_warehouse_sk
+ and inv_date_sk = d_date_sk
+ and d_year =2000
+ group by w_warehouse_name,w_warehouse_sk,i_item_sk,d_moy) foo
+ where case mean when 0 then 0 else stdev/mean end > 1)
+select inv1.w_warehouse_sk,inv1.i_item_sk,inv1.d_moy,inv1.mean, inv1.cov
+ ,inv2.w_warehouse_sk,inv2.i_item_sk,inv2.d_moy,inv2.mean, inv2.cov
+from inv inv1,inv inv2
+where inv1.i_item_sk = inv2.i_item_sk
+ and inv1.w_warehouse_sk = inv2.w_warehouse_sk
+ and inv1.d_moy=1
+ and inv2.d_moy=1+1
+order by inv1.w_warehouse_sk,inv1.i_item_sk,inv1.d_moy,inv1.mean,inv1.cov
+ ,inv2.d_moy,inv2.mean, inv2.cov
+;
+with inv as
+(select w_warehouse_name,w_warehouse_sk,i_item_sk,d_moy
+ ,stdev,mean, case mean when 0 then null else stdev/mean end cov
+ from(select w_warehouse_name,w_warehouse_sk,i_item_sk,d_moy
+ ,stddev_samp(inv_quantity_on_hand) stdev,avg(inv_quantity_on_hand) mean
+ from inventory
+ ,item
+ ,warehouse
+ ,date_dim
+ where inv_item_sk = i_item_sk
+ and inv_warehouse_sk = w_warehouse_sk
+ and inv_date_sk = d_date_sk
+ and d_year =2000
+ group by w_warehouse_name,w_warehouse_sk,i_item_sk,d_moy) foo
+ where case mean when 0 then 0 else stdev/mean end > 1)
+select inv1.w_warehouse_sk,inv1.i_item_sk,inv1.d_moy,inv1.mean, inv1.cov
+ ,inv2.w_warehouse_sk,inv2.i_item_sk,inv2.d_moy,inv2.mean, inv2.cov
+from inv inv1,inv inv2
+where inv1.i_item_sk = inv2.i_item_sk
+ and inv1.w_warehouse_sk = inv2.w_warehouse_sk
+ and inv1.d_moy=1
+ and inv2.d_moy=1+1
+ and inv1.cov > 1.5
+order by inv1.w_warehouse_sk,inv1.i_item_sk,inv1.d_moy,inv1.mean,inv1.cov
+ ,inv2.d_moy,inv2.mean, inv2.cov
+;
+
+-- end query 39 in stream 0 using template query39.tpl
+-- start query 40 in stream 0 using template query40.tpl
+select
+ w_state
+ ,i_item_id
+ ,sum(case when (cast(d_date as date) < cast ('2001-05-02' as date))
+ then cs_sales_price - coalesce(cr_refunded_cash,0) else 0 end) as sales_before
+ ,sum(case when (cast(d_date as date) >= cast ('2001-05-02' as date))
+ then cs_sales_price - coalesce(cr_refunded_cash,0) else 0 end) as sales_after
+ from
+ catalog_sales left outer join catalog_returns on
+ (cs_order_number = cr_order_number
+ and cs_item_sk = cr_item_sk)
+ ,warehouse
+ ,item
+ ,date_dim
+ where
+ i_current_price between 0.99 and 1.49
+ and i_item_sk = cs_item_sk
+ and cs_warehouse_sk = w_warehouse_sk
+ and cs_sold_date_sk = d_date_sk
+ and d_date between (cast ('2001-05-02' as date) - 30 days)
+ and (cast ('2001-05-02' as date) + 30 days)
+ group by
+ w_state,i_item_id
+ order by w_state,i_item_id
+limit 100;
+
+-- end query 40 in stream 0 using template query40.tpl
+-- start query 41 in stream 0 using template query41.tpl
+select distinct(i_product_name)
+ from item i1
+ where i_manufact_id between 704 and 704+40
+ and (select count(*) as item_cnt
+ from item
+ where (i_manufact = i1.i_manufact and
+ ((i_category = 'Women' and
+ (i_color = 'forest' or i_color = 'lime') and
+ (i_units = 'Pallet' or i_units = 'Pound') and
+ (i_size = 'economy' or i_size = 'small')
+ ) or
+ (i_category = 'Women' and
+ (i_color = 'navy' or i_color = 'slate') and
+ (i_units = 'Gross' or i_units = 'Bunch') and
+ (i_size = 'extra large' or i_size = 'petite')
+ ) or
+ (i_category = 'Men' and
+ (i_color = 'powder' or i_color = 'sky') and
+ (i_units = 'Dozen' or i_units = 'Lb') and
+ (i_size = 'N/A' or i_size = 'large')
+ ) or
+ (i_category = 'Men' and
+ (i_color = 'maroon' or i_color = 'smoke') and
+ (i_units = 'Ounce' or i_units = 'Case') and
+ (i_size = 'economy' or i_size = 'small')
+ ))) or
+ (i_manufact = i1.i_manufact and
+ ((i_category = 'Women' and
+ (i_color = 'dark' or i_color = 'aquamarine') and
+ (i_units = 'Ton' or i_units = 'Tbl') and
+ (i_size = 'economy' or i_size = 'small')
+ ) or
+ (i_category = 'Women' and
+ (i_color = 'frosted' or i_color = 'plum') and
+ (i_units = 'Dram' or i_units = 'Box') and
+ (i_size = 'extra large' or i_size = 'petite')
+ ) or
+ (i_category = 'Men' and
+ (i_color = 'papaya' or i_color = 'peach') and
+ (i_units = 'Bundle' or i_units = 'Carton') and
+ (i_size = 'N/A' or i_size = 'large')
+ ) or
+ (i_category = 'Men' and
+ (i_color = 'firebrick' or i_color = 'sienna') and
+ (i_units = 'Cup' or i_units = 'Each') and
+ (i_size = 'economy' or i_size = 'small')
+ )))) > 0
+ order by i_product_name
+ limit 100;
+
+-- end query 41 in stream 0 using template query41.tpl
+-- start query 42 in stream 0 using template query42.tpl
+select dt.d_year
+ ,item.i_category_id
+ ,item.i_category
+ ,sum(ss_ext_sales_price)
+ from date_dim dt
+ ,store_sales
+ ,item
+ where dt.d_date_sk = store_sales.ss_sold_date_sk
+ and store_sales.ss_item_sk = item.i_item_sk
+ and item.i_manager_id = 1
+ and dt.d_moy=11
+ and dt.d_year=1998
+ group by dt.d_year
+ ,item.i_category_id
+ ,item.i_category
+ order by sum(ss_ext_sales_price) desc,dt.d_year
+ ,item.i_category_id
+ ,item.i_category
+limit 100 ;
+
+-- end query 42 in stream 0 using template query42.tpl
+-- start query 43 in stream 0 using template query43.tpl
+select s_store_name, s_store_id,
+ sum(case when (d_day_name='Sunday') then ss_sales_price else null end) sun_sales,
+ sum(case when (d_day_name='Monday') then ss_sales_price else null end) mon_sales,
+ sum(case when (d_day_name='Tuesday') then ss_sales_price else null end) tue_sales,
+ sum(case when (d_day_name='Wednesday') then ss_sales_price else null end) wed_sales,
+ sum(case when (d_day_name='Thursday') then ss_sales_price else null end) thu_sales,
+ sum(case when (d_day_name='Friday') then ss_sales_price else null end) fri_sales,
+ sum(case when (d_day_name='Saturday') then ss_sales_price else null end) sat_sales
+ from date_dim, store_sales, store
+ where d_date_sk = ss_sold_date_sk and
+ s_store_sk = ss_store_sk and
+ s_gmt_offset = -5 and
+ d_year = 2000
+ group by s_store_name, s_store_id
+ order by s_store_name, s_store_id,sun_sales,mon_sales,tue_sales,wed_sales,thu_sales,fri_sales,sat_sales
+ limit 100;
+
+-- end query 43 in stream 0 using template query43.tpl
+-- start query 44 in stream 0 using template query44.tpl
+select asceding.rnk, i1.i_product_name best_performing, i2.i_product_name worst_performing
+from(select *
+ from (select item_sk,rank() over (order by rank_col asc) rnk
+ from (select ss_item_sk item_sk,avg(ss_net_profit) rank_col
+ from store_sales ss1
+ where ss_store_sk = 4
+ group by ss_item_sk
+ having avg(ss_net_profit) > 0.9*(select avg(ss_net_profit) rank_col
+ from store_sales
+ where ss_store_sk = 4
+ and ss_hdemo_sk is null
+ group by ss_store_sk))V1)V11
+ where rnk < 11) asceding,
+ (select *
+ from (select item_sk,rank() over (order by rank_col desc) rnk
+ from (select ss_item_sk item_sk,avg(ss_net_profit) rank_col
+ from store_sales ss1
+ where ss_store_sk = 4
+ group by ss_item_sk
+ having avg(ss_net_profit) > 0.9*(select avg(ss_net_profit) rank_col
+ from store_sales
+ where ss_store_sk = 4
+ and ss_hdemo_sk is null
+ group by ss_store_sk))V2)V21
+ where rnk < 11) descending,
+item i1,
+item i2
+where asceding.rnk = descending.rnk
+ and i1.i_item_sk=asceding.item_sk
+ and i2.i_item_sk=descending.item_sk
+order by asceding.rnk
+limit 100;
+
+-- end query 44 in stream 0 using template query44.tpl
+-- start query 45 in stream 0 using template query45.tpl
+select ca_zip, ca_city, sum(ws_sales_price)
+ from web_sales, customer, customer_address, date_dim, item
+ where ws_bill_customer_sk = c_customer_sk
+ and c_current_addr_sk = ca_address_sk
+ and ws_item_sk = i_item_sk
+ and ( substr(ca_zip,1,5) in ('85669', '86197','88274','83405','86475', '85392', '85460', '80348', '81792')
+ or
+ i_item_id in (select i_item_id
+ from item
+ where i_item_sk in (2, 3, 5, 7, 11, 13, 17, 19, 23, 29)
+ )
+ )
+ and ws_sold_date_sk = d_date_sk
+ and d_qoy = 1 and d_year = 2000
+ group by ca_zip, ca_city
+ order by ca_zip, ca_city
+ limit 100;
+
+-- end query 45 in stream 0 using template query45.tpl
+-- start query 46 in stream 0 using template query46.tpl
+select c_last_name
+ ,c_first_name
+ ,ca_city
+ ,bought_city
+ ,ss_ticket_number
+ ,amt,profit
+ from
+ (select ss_ticket_number
+ ,ss_customer_sk
+ ,ca_city bought_city
+ ,sum(ss_coupon_amt) amt
+ ,sum(ss_net_profit) profit
+ from store_sales,date_dim,store,household_demographics,customer_address
+ where store_sales.ss_sold_date_sk = date_dim.d_date_sk
+ and store_sales.ss_store_sk = store.s_store_sk
+ and store_sales.ss_hdemo_sk = household_demographics.hd_demo_sk
+ and store_sales.ss_addr_sk = customer_address.ca_address_sk
+ and (household_demographics.hd_dep_count = 8 or
+ household_demographics.hd_vehicle_count= 0)
+ and date_dim.d_dow in (6,0)
+ and date_dim.d_year in (2000,2000+1,2000+2)
+ and store.s_city in ('Midway','Fairview','Fairview','Midway','Fairview')
+ group by ss_ticket_number,ss_customer_sk,ss_addr_sk,ca_city) dn,customer,customer_address current_addr
+ where ss_customer_sk = c_customer_sk
+ and customer.c_current_addr_sk = current_addr.ca_address_sk
+ and current_addr.ca_city <> bought_city
+ order by c_last_name
+ ,c_first_name
+ ,ca_city
+ ,bought_city
+ ,ss_ticket_number
+ limit 100;
+
+-- end query 46 in stream 0 using template query46.tpl
+-- start query 47 in stream 0 using template query47.tpl
+with v1 as(
+ select i_category, i_brand,
+ s_store_name, s_company_name,
+ d_year, d_moy,
+ sum(ss_sales_price) sum_sales,
+ avg(sum(ss_sales_price)) over
+ (partition by i_category, i_brand,
+ s_store_name, s_company_name, d_year)
+ avg_monthly_sales,
+ rank() over
+ (partition by i_category, i_brand,
+ s_store_name, s_company_name
+ order by d_year, d_moy) rn
+ from item, store_sales, date_dim, store
+ where ss_item_sk = i_item_sk and
+ ss_sold_date_sk = d_date_sk and
+ ss_store_sk = s_store_sk and
+ (
+ d_year = 2000 or
+ ( d_year = 2000-1 and d_moy =12) or
+ ( d_year = 2000+1 and d_moy =1)
+ )
+ group by i_category, i_brand,
+ s_store_name, s_company_name,
+ d_year, d_moy),
+ v2 as(
+ select v1.s_store_name, v1.s_company_name
+ ,v1.d_year
+ ,v1.avg_monthly_sales
+ ,v1.sum_sales, v1_lag.sum_sales psum, v1_lead.sum_sales nsum
+ from v1, v1 v1_lag, v1 v1_lead
+ where v1.i_category = v1_lag.i_category and
+ v1.i_category = v1_lead.i_category and
+ v1.i_brand = v1_lag.i_brand and
+ v1.i_brand = v1_lead.i_brand and
+ v1.s_store_name = v1_lag.s_store_name and
+ v1.s_store_name = v1_lead.s_store_name and
+ v1.s_company_name = v1_lag.s_company_name and
+ v1.s_company_name = v1_lead.s_company_name and
+ v1.rn = v1_lag.rn + 1 and
+ v1.rn = v1_lead.rn - 1)
+ select *
+ from v2
+ where d_year = 2000 and
+ avg_monthly_sales > 0 and
+ case when avg_monthly_sales > 0 then abs(sum_sales - avg_monthly_sales) / avg_monthly_sales else null end > 0.1
+ order by sum_sales - avg_monthly_sales, nsum
+ limit 100;
+
+-- end query 47 in stream 0 using template query47.tpl
+-- start query 48 in stream 0 using template query48.tpl
+select sum (ss_quantity)
+ from store_sales, store, customer_demographics, customer_address, date_dim
+ where s_store_sk = ss_store_sk
+ and ss_sold_date_sk = d_date_sk and d_year = 2001
+ and
+ (
+ (
+ cd_demo_sk = ss_cdemo_sk
+ and
+ cd_marital_status = 'S'
+ and
+ cd_education_status = 'Secondary'
+ and
+ ss_sales_price between 100.00 and 150.00
+ )
+ or
+ (
+ cd_demo_sk = ss_cdemo_sk
+ and
+ cd_marital_status = 'M'
+ and
+ cd_education_status = '2 yr Degree'
+ and
+ ss_sales_price between 50.00 and 100.00
+ )
+ or
+ (
+ cd_demo_sk = ss_cdemo_sk
+ and
+ cd_marital_status = 'D'
+ and
+ cd_education_status = 'Advanced Degree'
+ and
+ ss_sales_price between 150.00 and 200.00
+ )
+ )
+ and
+ (
+ (
+ ss_addr_sk = ca_address_sk
+ and
+ ca_country = 'United States'
+ and
+ ca_state in ('ND', 'NY', 'SD')
+ and ss_net_profit between 0 and 2000
+ )
+ or
+ (ss_addr_sk = ca_address_sk
+ and
+ ca_country = 'United States'
+ and
+ ca_state in ('MD', 'GA', 'KS')
+ and ss_net_profit between 150 and 3000
+ )
+ or
+ (ss_addr_sk = ca_address_sk
+ and
+ ca_country = 'United States'
+ and
+ ca_state in ('CO', 'MN', 'NC')
+ and ss_net_profit between 50 and 25000
+ )
+ )
+;
+
+-- end query 48 in stream 0 using template query48.tpl
+-- start query 49 in stream 0 using template query49.tpl
+select channel, item, return_ratio, return_rank, currency_rank from
+ (select
+ 'web' as channel
+ ,web.item
+ ,web.return_ratio
+ ,web.return_rank
+ ,web.currency_rank
+ from (
+ select
+ item
+ ,return_ratio
+ ,currency_ratio
+ ,rank() over (order by return_ratio) as return_rank
+ ,rank() over (order by currency_ratio) as currency_rank
+ from
+ ( select ws.ws_item_sk as item
+ ,(cast(sum(coalesce(wr.wr_return_quantity,0)) as decimal(15,4))/
+ cast(sum(coalesce(ws.ws_quantity,0)) as decimal(15,4) )) as return_ratio
+ ,(cast(sum(coalesce(wr.wr_return_amt,0)) as decimal(15,4))/
+ cast(sum(coalesce(ws.ws_net_paid,0)) as decimal(15,4) )) as currency_ratio
+ from
+ web_sales ws left outer join web_returns wr
+ on (ws.ws_order_number = wr.wr_order_number and
+ ws.ws_item_sk = wr.wr_item_sk)
+ ,date_dim
+ where
+ wr.wr_return_amt > 10000
+ and ws.ws_net_profit > 1
+ and ws.ws_net_paid > 0
+ and ws.ws_quantity > 0
+ and ws_sold_date_sk = d_date_sk
+ and d_year = 1998
+ and d_moy = 11
+ group by ws.ws_item_sk
+ ) in_web
+ ) web
+ where
+ (
+ web.return_rank <= 10
+ or
+ web.currency_rank <= 10
+ )
+ union
+ select
+ 'catalog' as channel
+ ,catalog.item
+ ,catalog.return_ratio
+ ,catalog.return_rank
+ ,catalog.currency_rank
+ from (
+ select
+ item
+ ,return_ratio
+ ,currency_ratio
+ ,rank() over (order by return_ratio) as return_rank
+ ,rank() over (order by currency_ratio) as currency_rank
+ from
+ ( select
+ cs.cs_item_sk as item
+ ,(cast(sum(coalesce(cr.cr_return_quantity,0)) as decimal(15,4))/
+ cast(sum(coalesce(cs.cs_quantity,0)) as decimal(15,4) )) as return_ratio
+ ,(cast(sum(coalesce(cr.cr_return_amount,0)) as decimal(15,4))/
+ cast(sum(coalesce(cs.cs_net_paid,0)) as decimal(15,4) )) as currency_ratio
+ from
+ catalog_sales cs left outer join catalog_returns cr
+ on (cs.cs_order_number = cr.cr_order_number and
+ cs.cs_item_sk = cr.cr_item_sk)
+ ,date_dim
+ where
+ cr.cr_return_amount > 10000
+ and cs.cs_net_profit > 1
+ and cs.cs_net_paid > 0
+ and cs.cs_quantity > 0
+ and cs_sold_date_sk = d_date_sk
+ and d_year = 1998
+ and d_moy = 11
+ group by cs.cs_item_sk
+ ) in_cat
+ ) catalog
+ where
+ (
+ catalog.return_rank <= 10
+ or
+ catalog.currency_rank <=10
+ )
+ union
+ select
+ 'store' as channel
+ ,store.item
+ ,store.return_ratio
+ ,store.return_rank
+ ,store.currency_rank
+ from (
+ select
+ item
+ ,return_ratio
+ ,currency_ratio
+ ,rank() over (order by return_ratio) as return_rank
+ ,rank() over (order by currency_ratio) as currency_rank
+ from
+ ( select sts.ss_item_sk as item
+ ,(cast(sum(coalesce(sr.sr_return_quantity,0)) as decimal(15,4))/cast(sum(coalesce(sts.ss_quantity,0)) as decimal(15,4) )) as return_ratio
+ ,(cast(sum(coalesce(sr.sr_return_amt,0)) as decimal(15,4))/cast(sum(coalesce(sts.ss_net_paid,0)) as decimal(15,4) )) as currency_ratio
+ from
+ store_sales sts left outer join store_returns sr
+ on (sts.ss_ticket_number = sr.sr_ticket_number and sts.ss_item_sk = sr.sr_item_sk)
+ ,date_dim
+ where
+ sr.sr_return_amt > 10000
+ and sts.ss_net_profit > 1
+ and sts.ss_net_paid > 0
+ and sts.ss_quantity > 0
+ and ss_sold_date_sk = d_date_sk
+ and d_year = 1998
+ and d_moy = 11
+ group by sts.ss_item_sk
+ ) in_store
+ ) store
+ where (
+ store.return_rank <= 10
+ or
+ store.currency_rank <= 10
+ )
+ )
+ order by 1,4,5,2
+ limit 100;
+
+-- end query 49 in stream 0 using template query49.tpl
+-- start query 50 in stream 0 using template query50.tpl
+select
+ s_store_name
+ ,s_company_id
+ ,s_street_number
+ ,s_street_name
+ ,s_street_type
+ ,s_suite_number
+ ,s_city
+ ,s_county
+ ,s_state
+ ,s_zip
+ ,sum(case when (sr_returned_date_sk - ss_sold_date_sk <= 30 ) then 1 else 0 end) as "30 days"
+ ,sum(case when (sr_returned_date_sk - ss_sold_date_sk > 30) and
+ (sr_returned_date_sk - ss_sold_date_sk <= 60) then 1 else 0 end ) as "31-60 days"
+ ,sum(case when (sr_returned_date_sk - ss_sold_date_sk > 60) and
+ (sr_returned_date_sk - ss_sold_date_sk <= 90) then 1 else 0 end) as "61-90 days"
+ ,sum(case when (sr_returned_date_sk - ss_sold_date_sk > 90) and
+ (sr_returned_date_sk - ss_sold_date_sk <= 120) then 1 else 0 end) as "91-120 days"
+ ,sum(case when (sr_returned_date_sk - ss_sold_date_sk > 120) then 1 else 0 end) as ">120 days"
+from
+ store_sales
+ ,store_returns
+ ,store
+ ,date_dim d1
+ ,date_dim d2
+where
+ d2.d_year = 2001
+and d2.d_moy = 8
+and ss_ticket_number = sr_ticket_number
+and ss_item_sk = sr_item_sk
+and ss_sold_date_sk = d1.d_date_sk
+and sr_returned_date_sk = d2.d_date_sk
+and ss_customer_sk = sr_customer_sk
+and ss_store_sk = s_store_sk
+group by
+ s_store_name
+ ,s_company_id
+ ,s_street_number
+ ,s_street_name
+ ,s_street_type
+ ,s_suite_number
+ ,s_city
+ ,s_county
+ ,s_state
+ ,s_zip
+order by s_store_name
+ ,s_company_id
+ ,s_street_number
+ ,s_street_name
+ ,s_street_type
+ ,s_suite_number
+ ,s_city
+ ,s_county
+ ,s_state
+ ,s_zip
+limit 100;
+
+-- end query 50 in stream 0 using template query50.tpl
+-- start query 51 in stream 0 using template query51.tpl
+WITH web_v1 as (
+select
+ ws_item_sk item_sk, d_date,
+ sum(sum(ws_sales_price))
+ over (partition by ws_item_sk order by d_date rows between unbounded preceding and current row) cume_sales
+from web_sales
+ ,date_dim
+where ws_sold_date_sk=d_date_sk
+ and d_month_seq between 1212 and 1212+11
+ and ws_item_sk is not NULL
+group by ws_item_sk, d_date),
+store_v1 as (
+select
+ ss_item_sk item_sk, d_date,
+ sum(sum(ss_sales_price))
+ over (partition by ss_item_sk order by d_date rows between unbounded preceding and current row) cume_sales
+from store_sales
+ ,date_dim
+where ss_sold_date_sk=d_date_sk
+ and d_month_seq between 1212 and 1212+11
+ and ss_item_sk is not NULL
+group by ss_item_sk, d_date)
+ select *
+from (select item_sk
+ ,d_date
+ ,web_sales
+ ,store_sales
+ ,max(web_sales)
+ over (partition by item_sk order by d_date rows between unbounded preceding and current row) web_cumulative
+ ,max(store_sales)
+ over (partition by item_sk order by d_date rows between unbounded preceding and current row) store_cumulative
+ from (select case when web.item_sk is not null then web.item_sk else store.item_sk end item_sk
+ ,case when web.d_date is not null then web.d_date else store.d_date end d_date
+ ,web.cume_sales web_sales
+ ,store.cume_sales store_sales
+ from web_v1 web full outer join store_v1 store on (web.item_sk = store.item_sk
+ and web.d_date = store.d_date)
+ )x )y
+where web_cumulative > store_cumulative
+order by item_sk
+ ,d_date
+limit 100;
+
+-- end query 51 in stream 0 using template query51.tpl
+-- start query 52 in stream 0 using template query52.tpl
+select dt.d_year
+ ,item.i_brand_id brand_id
+ ,item.i_brand brand
+ ,sum(ss_ext_sales_price) ext_price
+ from date_dim dt
+ ,store_sales
+ ,item
+ where dt.d_date_sk = store_sales.ss_sold_date_sk
+ and store_sales.ss_item_sk = item.i_item_sk
+ and item.i_manager_id = 1
+ and dt.d_moy=12
+ and dt.d_year=2000
+ group by dt.d_year
+ ,item.i_brand
+ ,item.i_brand_id
+ order by dt.d_year
+ ,ext_price desc
+ ,brand_id
+limit 100 ;
+
+-- end query 52 in stream 0 using template query52.tpl
+-- start query 53 in stream 0 using template query53.tpl
+select * from
+(select i_manufact_id,
+sum(ss_sales_price) sum_sales,
+avg(sum(ss_sales_price)) over (partition by i_manufact_id) avg_quarterly_sales
+from item, store_sales, date_dim, store
+where ss_item_sk = i_item_sk and
+ss_sold_date_sk = d_date_sk and
+ss_store_sk = s_store_sk and
+d_month_seq in (1186,1186+1,1186+2,1186+3,1186+4,1186+5,1186+6,1186+7,1186+8,1186+9,1186+10,1186+11) and
+((i_category in ('Books','Children','Electronics') and
+i_class in ('personal','portable','reference','self-help') and
+i_brand in ('scholaramalgamalg #14','scholaramalgamalg #7',
+ 'exportiunivamalg #9','scholaramalgamalg #9'))
+or(i_category in ('Women','Music','Men') and
+i_class in ('accessories','classical','fragrances','pants') and
+i_brand in ('amalgimporto #1','edu packscholar #1','exportiimporto #1',
+ 'importoamalg #1')))
+group by i_manufact_id, d_qoy ) tmp1
+where case when avg_quarterly_sales > 0
+ then abs (sum_sales - avg_quarterly_sales)/ avg_quarterly_sales
+ else null end > 0.1
+order by avg_quarterly_sales,
+ sum_sales,
+ i_manufact_id
+limit 100;
+
+-- end query 53 in stream 0 using template query53.tpl
+-- start query 54 in stream 0 using template query54.tpl
+with my_customers as (
+ select distinct c_customer_sk
+ , c_current_addr_sk
+ from
+ ( select cs_sold_date_sk sold_date_sk,
+ cs_bill_customer_sk customer_sk,
+ cs_item_sk item_sk
+ from catalog_sales
+ union all
+ select ws_sold_date_sk sold_date_sk,
+ ws_bill_customer_sk customer_sk,
+ ws_item_sk item_sk
+ from web_sales
+ ) cs_or_ws_sales,
+ item,
+ date_dim,
+ customer
+ where sold_date_sk = d_date_sk
+ and item_sk = i_item_sk
+ and i_category = 'Music'
+ and i_class = 'country'
+ and c_customer_sk = cs_or_ws_sales.customer_sk
+ and d_moy = 1
+ and d_year = 1999
+ )
+ , my_revenue as (
+ select c_customer_sk,
+ sum(ss_ext_sales_price) as revenue
+ from my_customers,
+ store_sales,
+ customer_address,
+ store,
+ date_dim
+ where c_current_addr_sk = ca_address_sk
+ and ca_county = s_county
+ and ca_state = s_state
+ and ss_sold_date_sk = d_date_sk
+ and c_customer_sk = ss_customer_sk
+ and d_month_seq between (select distinct d_month_seq+1
+ from date_dim where d_year = 1999 and d_moy = 1)
+ and (select distinct d_month_seq+3
+ from date_dim where d_year = 1999 and d_moy = 1)
+ group by c_customer_sk
+ )
+ , segments as
+ (select cast((revenue/50) as int) as segment
+ from my_revenue
+ )
+ select segment, count(*) as num_customers, segment*50 as segment_base
+ from segments
+ group by segment
+ order by segment, num_customers
+ limit 100;
+
+-- end query 54 in stream 0 using template query54.tpl
+-- start query 55 in stream 0 using template query55.tpl
+select i_brand_id brand_id, i_brand brand,
+ sum(ss_ext_sales_price) ext_price
+ from date_dim, store_sales, item
+ where d_date_sk = ss_sold_date_sk
+ and ss_item_sk = i_item_sk
+ and i_manager_id=52
+ and d_moy=11
+ and d_year=2000
+ group by i_brand, i_brand_id
+ order by ext_price desc, i_brand_id
+limit 100 ;
+
+-- end query 55 in stream 0 using template query55.tpl
+-- start query 56 in stream 0 using template query56.tpl
+with ss as (
+ select i_item_id,sum(ss_ext_sales_price) total_sales
+ from
+ store_sales,
+ date_dim,
+ customer_address,
+ item
+ where i_item_id in (select
+ i_item_id
+from item
+where i_color in ('powder','orchid','pink'))
+ and ss_item_sk = i_item_sk
+ and ss_sold_date_sk = d_date_sk
+ and d_year = 2000
+ and d_moy = 3
+ and ss_addr_sk = ca_address_sk
+ and ca_gmt_offset = -6
+ group by i_item_id),
+ cs as (
+ select i_item_id,sum(cs_ext_sales_price) total_sales
+ from
+ catalog_sales,
+ date_dim,
+ customer_address,
+ item
+ where
+ i_item_id in (select
+ i_item_id
+from item
+where i_color in ('powder','orchid','pink'))
+ and cs_item_sk = i_item_sk
+ and cs_sold_date_sk = d_date_sk
+ and d_year = 2000
+ and d_moy = 3
+ and cs_bill_addr_sk = ca_address_sk
+ and ca_gmt_offset = -6
+ group by i_item_id),
+ ws as (
+ select i_item_id,sum(ws_ext_sales_price) total_sales
+ from
+ web_sales,
+ date_dim,
+ customer_address,
+ item
+ where
+ i_item_id in (select
+ i_item_id
+from item
+where i_color in ('powder','orchid','pink'))
+ and ws_item_sk = i_item_sk
+ and ws_sold_date_sk = d_date_sk
+ and d_year = 2000
+ and d_moy = 3
+ and ws_bill_addr_sk = ca_address_sk
+ and ca_gmt_offset = -6
+ group by i_item_id)
+ select i_item_id ,sum(total_sales) total_sales
+ from (select * from ss
+ union all
+ select * from cs
+ union all
+ select * from ws) tmp1
+ group by i_item_id
+ order by total_sales,
+ i_item_id
+ limit 100;
+
+-- end query 56 in stream 0 using template query56.tpl
+-- start query 57 in stream 0 using template query57.tpl
+with v1 as(
+ select i_category, i_brand,
+ cc_name,
+ d_year, d_moy,
+ sum(cs_sales_price) sum_sales,
+ avg(sum(cs_sales_price)) over
+ (partition by i_category, i_brand,
+ cc_name, d_year)
+ avg_monthly_sales,
+ rank() over
+ (partition by i_category, i_brand,
+ cc_name
+ order by d_year, d_moy) rn
+ from item, catalog_sales, date_dim, call_center
+ where cs_item_sk = i_item_sk and
+ cs_sold_date_sk = d_date_sk and
+ cc_call_center_sk= cs_call_center_sk and
+ (
+ d_year = 2001 or
+ ( d_year = 2001-1 and d_moy =12) or
+ ( d_year = 2001+1 and d_moy =1)
+ )
+ group by i_category, i_brand,
+ cc_name , d_year, d_moy),
+ v2 as(
+ select v1.i_category, v1.i_brand, v1.cc_name
+ ,v1.d_year
+ ,v1.avg_monthly_sales
+ ,v1.sum_sales, v1_lag.sum_sales psum, v1_lead.sum_sales nsum
+ from v1, v1 v1_lag, v1 v1_lead
+ where v1.i_category = v1_lag.i_category and
+ v1.i_category = v1_lead.i_category and
+ v1.i_brand = v1_lag.i_brand and
+ v1.i_brand = v1_lead.i_brand and
+ v1. cc_name = v1_lag. cc_name and
+ v1. cc_name = v1_lead. cc_name and
+ v1.rn = v1_lag.rn + 1 and
+ v1.rn = v1_lead.rn - 1)
+ select *
+ from v2
+ where d_year = 2001 and
+ avg_monthly_sales > 0 and
+ case when avg_monthly_sales > 0 then abs(sum_sales - avg_monthly_sales) / avg_monthly_sales else null end > 0.1
+ order by sum_sales - avg_monthly_sales, avg_monthly_sales
+ limit 100;
+
+-- end query 57 in stream 0 using template query57.tpl
+-- start query 58 in stream 0 using template query58.tpl
+with ss_items as
+ (select i_item_id item_id
+ ,sum(ss_ext_sales_price) ss_item_rev
+ from store_sales
+ ,item
+ ,date_dim
+ where ss_item_sk = i_item_sk
+ and d_date in (select d_date
+ from date_dim
+ where d_week_seq = (select d_week_seq
+ from date_dim
+ where d_date = '2001-06-16'))
+ and ss_sold_date_sk = d_date_sk
+ group by i_item_id),
+ cs_items as
+ (select i_item_id item_id
+ ,sum(cs_ext_sales_price) cs_item_rev
+ from catalog_sales
+ ,item
+ ,date_dim
+ where cs_item_sk = i_item_sk
+ and d_date in (select d_date
+ from date_dim
+ where d_week_seq = (select d_week_seq
+ from date_dim
+ where d_date = '2001-06-16'))
+ and cs_sold_date_sk = d_date_sk
+ group by i_item_id),
+ ws_items as
+ (select i_item_id item_id
+ ,sum(ws_ext_sales_price) ws_item_rev
+ from web_sales
+ ,item
+ ,date_dim
+ where ws_item_sk = i_item_sk
+ and d_date in (select d_date
+ from date_dim
+ where d_week_seq =(select d_week_seq
+ from date_dim
+ where d_date = '2001-06-16'))
+ and ws_sold_date_sk = d_date_sk
+ group by i_item_id)
+ select ss_items.item_id
+ ,ss_item_rev
+ ,ss_item_rev/((ss_item_rev+cs_item_rev+ws_item_rev)/3) * 100 ss_dev
+ ,cs_item_rev
+ ,cs_item_rev/((ss_item_rev+cs_item_rev+ws_item_rev)/3) * 100 cs_dev
+ ,ws_item_rev
+ ,ws_item_rev/((ss_item_rev+cs_item_rev+ws_item_rev)/3) * 100 ws_dev
+ ,(ss_item_rev+cs_item_rev+ws_item_rev)/3 average
+ from ss_items,cs_items,ws_items
+ where ss_items.item_id=cs_items.item_id
+ and ss_items.item_id=ws_items.item_id
+ and ss_item_rev between 0.9 * cs_item_rev and 1.1 * cs_item_rev
+ and ss_item_rev between 0.9 * ws_item_rev and 1.1 * ws_item_rev
+ and cs_item_rev between 0.9 * ss_item_rev and 1.1 * ss_item_rev
+ and cs_item_rev between 0.9 * ws_item_rev and 1.1 * ws_item_rev
+ and ws_item_rev between 0.9 * ss_item_rev and 1.1 * ss_item_rev
+ and ws_item_rev between 0.9 * cs_item_rev and 1.1 * cs_item_rev
+ order by item_id
+ ,ss_item_rev
+ limit 100;
+
+-- end query 58 in stream 0 using template query58.tpl
+-- start query 59 in stream 0 using template query59.tpl
+with wss as
+ (select d_week_seq,
+ ss_store_sk,
+ sum(case when (d_day_name='Sunday') then ss_sales_price else null end) sun_sales,
+ sum(case when (d_day_name='Monday') then ss_sales_price else null end) mon_sales,
+ sum(case when (d_day_name='Tuesday') then ss_sales_price else null end) tue_sales,
+ sum(case when (d_day_name='Wednesday') then ss_sales_price else null end) wed_sales,
+ sum(case when (d_day_name='Thursday') then ss_sales_price else null end) thu_sales,
+ sum(case when (d_day_name='Friday') then ss_sales_price else null end) fri_sales,
+ sum(case when (d_day_name='Saturday') then ss_sales_price else null end) sat_sales
+ from store_sales,date_dim
+ where d_date_sk = ss_sold_date_sk
+ group by d_week_seq,ss_store_sk
+ )
+ select s_store_name1,s_store_id1,d_week_seq1
+ ,sun_sales1/sun_sales2,mon_sales1/mon_sales2
+ ,tue_sales1/tue_sales2,wed_sales1/wed_sales2,thu_sales1/thu_sales2
+ ,fri_sales1/fri_sales2,sat_sales1/sat_sales2
+ from
+ (select s_store_name s_store_name1,wss.d_week_seq d_week_seq1
+ ,s_store_id s_store_id1,sun_sales sun_sales1
+ ,mon_sales mon_sales1,tue_sales tue_sales1
+ ,wed_sales wed_sales1,thu_sales thu_sales1
+ ,fri_sales fri_sales1,sat_sales sat_sales1
+ from wss,store,date_dim d
+ where d.d_week_seq = wss.d_week_seq and
+ ss_store_sk = s_store_sk and
+ d_month_seq between 1195 and 1195 + 11) y,
+ (select s_store_name s_store_name2,wss.d_week_seq d_week_seq2
+ ,s_store_id s_store_id2,sun_sales sun_sales2
+ ,mon_sales mon_sales2,tue_sales tue_sales2
+ ,wed_sales wed_sales2,thu_sales thu_sales2
+ ,fri_sales fri_sales2,sat_sales sat_sales2
+ from wss,store,date_dim d
+ where d.d_week_seq = wss.d_week_seq and
+ ss_store_sk = s_store_sk and
+ d_month_seq between 1195+ 12 and 1195 + 23) x
+ where s_store_id1=s_store_id2
+ and d_week_seq1=d_week_seq2-52
+ order by s_store_name1,s_store_id1,d_week_seq1
+limit 100;
+
+-- end query 59 in stream 0 using template query59.tpl
+-- start query 60 in stream 0 using template query60.tpl
+with ss as (
+ select
+ i_item_id,sum(ss_ext_sales_price) total_sales
+ from
+ store_sales,
+ date_dim,
+ customer_address,
+ item
+ where
+ i_item_id in (select
+ i_item_id
+from
+ item
+where i_category in ('Jewelry'))
+ and ss_item_sk = i_item_sk
+ and ss_sold_date_sk = d_date_sk
+ and d_year = 2000
+ and d_moy = 10
+ and ss_addr_sk = ca_address_sk
+ and ca_gmt_offset = -5
+ group by i_item_id),
+ cs as (
+ select
+ i_item_id,sum(cs_ext_sales_price) total_sales
+ from
+ catalog_sales,
+ date_dim,
+ customer_address,
+ item
+ where
+ i_item_id in (select
+ i_item_id
+from
+ item
+where i_category in ('Jewelry'))
+ and cs_item_sk = i_item_sk
+ and cs_sold_date_sk = d_date_sk
+ and d_year = 2000
+ and d_moy = 10
+ and cs_bill_addr_sk = ca_address_sk
+ and ca_gmt_offset = -5
+ group by i_item_id),
+ ws as (
+ select
+ i_item_id,sum(ws_ext_sales_price) total_sales
+ from
+ web_sales,
+ date_dim,
+ customer_address,
+ item
+ where
+ i_item_id in (select
+ i_item_id
+from
+ item
+where i_category in ('Jewelry'))
+ and ws_item_sk = i_item_sk
+ and ws_sold_date_sk = d_date_sk
+ and d_year = 2000
+ and d_moy = 10
+ and ws_bill_addr_sk = ca_address_sk
+ and ca_gmt_offset = -5
+ group by i_item_id)
+ select
+ i_item_id
+,sum(total_sales) total_sales
+ from (select * from ss
+ union all
+ select * from cs
+ union all
+ select * from ws) tmp1
+ group by i_item_id
+ order by i_item_id
+ ,total_sales
+ limit 100;
+
+-- end query 60 in stream 0 using template query60.tpl
+-- start query 61 in stream 0 using template query61.tpl
+select promotions,total,cast(promotions as decimal(15,4))/cast(total as decimal(15,4))*100
+from
+ (select sum(ss_ext_sales_price) promotions
+ from store_sales
+ ,store
+ ,promotion
+ ,date_dim
+ ,customer
+ ,customer_address
+ ,item
+ where ss_sold_date_sk = d_date_sk
+ and ss_store_sk = s_store_sk
+ and ss_promo_sk = p_promo_sk
+ and ss_customer_sk= c_customer_sk
+ and ca_address_sk = c_current_addr_sk
+ and ss_item_sk = i_item_sk
+ and ca_gmt_offset = -7
+ and i_category = 'Home'
+ and (p_channel_dmail = 'Y' or p_channel_email = 'Y' or p_channel_tv = 'Y')
+ and s_gmt_offset = -7
+ and d_year = 2000
+ and d_moy = 12) promotional_sales,
+ (select sum(ss_ext_sales_price) total
+ from store_sales
+ ,store
+ ,date_dim
+ ,customer
+ ,customer_address
+ ,item
+ where ss_sold_date_sk = d_date_sk
+ and ss_store_sk = s_store_sk
+ and ss_customer_sk= c_customer_sk
+ and ca_address_sk = c_current_addr_sk
+ and ss_item_sk = i_item_sk
+ and ca_gmt_offset = -7
+ and i_category = 'Home'
+ and s_gmt_offset = -7
+ and d_year = 2000
+ and d_moy = 12) all_sales
+order by promotions, total
+limit 100;
+
+-- end query 61 in stream 0 using template query61.tpl
+-- start query 62 in stream 0 using template query62.tpl
+select
+ substr(w_warehouse_name,1,20)
+ ,sm_type
+ ,web_name
+ ,sum(case when (ws_ship_date_sk - ws_sold_date_sk <= 30 ) then 1 else 0 end) as "30 days"
+ ,sum(case when (ws_ship_date_sk - ws_sold_date_sk > 30) and
+ (ws_ship_date_sk - ws_sold_date_sk <= 60) then 1 else 0 end ) as "31-60 days"
+ ,sum(case when (ws_ship_date_sk - ws_sold_date_sk > 60) and
+ (ws_ship_date_sk - ws_sold_date_sk <= 90) then 1 else 0 end) as "61-90 days"
+ ,sum(case when (ws_ship_date_sk - ws_sold_date_sk > 90) and
+ (ws_ship_date_sk - ws_sold_date_sk <= 120) then 1 else 0 end) as "91-120 days"
+ ,sum(case when (ws_ship_date_sk - ws_sold_date_sk > 120) then 1 else 0 end) as ">120 days"
+from
+ web_sales
+ ,warehouse
+ ,ship_mode
+ ,web_site
+ ,date_dim
+where
+ d_month_seq between 1223 and 1223 + 11
+and ws_ship_date_sk = d_date_sk
+and ws_warehouse_sk = w_warehouse_sk
+and ws_ship_mode_sk = sm_ship_mode_sk
+and ws_web_site_sk = web_site_sk
+group by
+ substr(w_warehouse_name,1,20)
+ ,sm_type
+ ,web_name
+order by substr(w_warehouse_name,1,20)
+ ,sm_type
+ ,web_name
+limit 100;
+
+-- end query 62 in stream 0 using template query62.tpl
+-- start query 63 in stream 0 using template query63.tpl
+select *
+from (select i_manager_id
+ ,sum(ss_sales_price) sum_sales
+ ,avg(sum(ss_sales_price)) over (partition by i_manager_id) avg_monthly_sales
+ from item
+ ,store_sales
+ ,date_dim
+ ,store
+ where ss_item_sk = i_item_sk
+ and ss_sold_date_sk = d_date_sk
+ and ss_store_sk = s_store_sk
+ and d_month_seq in (1222,1222+1,1222+2,1222+3,1222+4,1222+5,1222+6,1222+7,1222+8,1222+9,1222+10,1222+11)
+ and (( i_category in ('Books','Children','Electronics')
+ and i_class in ('personal','portable','reference','self-help')
+ and i_brand in ('scholaramalgamalg #14','scholaramalgamalg #7',
+ 'exportiunivamalg #9','scholaramalgamalg #9'))
+ or( i_category in ('Women','Music','Men')
+ and i_class in ('accessories','classical','fragrances','pants')
+ and i_brand in ('amalgimporto #1','edu packscholar #1','exportiimporto #1',
+ 'importoamalg #1')))
+group by i_manager_id, d_moy) tmp1
+where case when avg_monthly_sales > 0 then abs (sum_sales - avg_monthly_sales) / avg_monthly_sales else null end > 0.1
+order by i_manager_id
+ ,avg_monthly_sales
+ ,sum_sales
+limit 100;
+
+-- end query 63 in stream 0 using template query63.tpl
+-- start query 64 in stream 0 using template query64.tpl
+with cs_ui as
+ (select cs_item_sk
+ ,sum(cs_ext_list_price) as sale,sum(cr_refunded_cash+cr_reversed_charge+cr_store_credit) as refund
+ from catalog_sales
+ ,catalog_returns
+ where cs_item_sk = cr_item_sk
+ and cs_order_number = cr_order_number
+ group by cs_item_sk
+ having sum(cs_ext_list_price)>2*sum(cr_refunded_cash+cr_reversed_charge+cr_store_credit)),
+cross_sales as
+ (select i_product_name product_name
+ ,i_item_sk item_sk
+ ,s_store_name store_name
+ ,s_zip store_zip
+ ,ad1.ca_street_number b_street_number
+ ,ad1.ca_street_name b_street_name
+ ,ad1.ca_city b_city
+ ,ad1.ca_zip b_zip
+ ,ad2.ca_street_number c_street_number
+ ,ad2.ca_street_name c_street_name
+ ,ad2.ca_city c_city
+ ,ad2.ca_zip c_zip
+ ,d1.d_year as syear
+ ,d2.d_year as fsyear
+ ,d3.d_year s2year
+ ,count(*) cnt
+ ,sum(ss_wholesale_cost) s1
+ ,sum(ss_list_price) s2
+ ,sum(ss_coupon_amt) s3
+ FROM store_sales
+ ,store_returns
+ ,cs_ui
+ ,date_dim d1
+ ,date_dim d2
+ ,date_dim d3
+ ,store
+ ,customer
+ ,customer_demographics cd1
+ ,customer_demographics cd2
+ ,promotion
+ ,household_demographics hd1
+ ,household_demographics hd2
+ ,customer_address ad1
+ ,customer_address ad2
+ ,income_band ib1
+ ,income_band ib2
+ ,item
+ WHERE ss_store_sk = s_store_sk AND
+ ss_sold_date_sk = d1.d_date_sk AND
+ ss_customer_sk = c_customer_sk AND
+ ss_cdemo_sk= cd1.cd_demo_sk AND
+ ss_hdemo_sk = hd1.hd_demo_sk AND
+ ss_addr_sk = ad1.ca_address_sk and
+ ss_item_sk = i_item_sk and
+ ss_item_sk = sr_item_sk and
+ ss_ticket_number = sr_ticket_number and
+ ss_item_sk = cs_ui.cs_item_sk and
+ c_current_cdemo_sk = cd2.cd_demo_sk AND
+ c_current_hdemo_sk = hd2.hd_demo_sk AND
+ c_current_addr_sk = ad2.ca_address_sk and
+ c_first_sales_date_sk = d2.d_date_sk and
+ c_first_shipto_date_sk = d3.d_date_sk and
+ ss_promo_sk = p_promo_sk and
+ hd1.hd_income_band_sk = ib1.ib_income_band_sk and
+ hd2.hd_income_band_sk = ib2.ib_income_band_sk and
+ cd1.cd_marital_status <> cd2.cd_marital_status and
+ i_color in ('orange','lace','lawn','misty','blush','pink') and
+ i_current_price between 48 and 48 + 10 and
+ i_current_price between 48 + 1 and 48 + 15
+group by i_product_name
+ ,i_item_sk
+ ,s_store_name
+ ,s_zip
+ ,ad1.ca_street_number
+ ,ad1.ca_street_name
+ ,ad1.ca_city
+ ,ad1.ca_zip
+ ,ad2.ca_street_number
+ ,ad2.ca_street_name
+ ,ad2.ca_city
+ ,ad2.ca_zip
+ ,d1.d_year
+ ,d2.d_year
+ ,d3.d_year
+)
+select cs1.product_name
+ ,cs1.store_name
+ ,cs1.store_zip
+ ,cs1.b_street_number
+ ,cs1.b_street_name
+ ,cs1.b_city
+ ,cs1.b_zip
+ ,cs1.c_street_number
+ ,cs1.c_street_name
+ ,cs1.c_city
+ ,cs1.c_zip
+ ,cs1.syear
+ ,cs1.cnt
+ ,cs1.s1 as s11
+ ,cs1.s2 as s21
+ ,cs1.s3 as s31
+ ,cs2.s1 as s12
+ ,cs2.s2 as s22
+ ,cs2.s3 as s32
+ ,cs2.syear
+ ,cs2.cnt
+from cross_sales cs1,cross_sales cs2
+where cs1.item_sk=cs2.item_sk and
+ cs1.syear = 1999 and
+ cs2.syear = 1999 + 1 and
+ cs2.cnt <= cs1.cnt and
+ cs1.store_name = cs2.store_name and
+ cs1.store_zip = cs2.store_zip
+order by cs1.product_name
+ ,cs1.store_name
+ ,cs2.cnt
+ ,cs1.s1
+ ,cs2.s1;
+
+-- end query 64 in stream 0 using template query64.tpl
+-- start query 65 in stream 0 using template query65.tpl
+select
+ s_store_name,
+ i_item_desc,
+ sc.revenue,
+ i_current_price,
+ i_wholesale_cost,
+ i_brand
+ from store, item,
+ (select ss_store_sk, avg(revenue) as ave
+ from
+ (select ss_store_sk, ss_item_sk,
+ sum(ss_sales_price) as revenue
+ from store_sales, date_dim
+ where ss_sold_date_sk = d_date_sk and d_month_seq between 1176 and 1176+11
+ group by ss_store_sk, ss_item_sk) sa
+ group by ss_store_sk) sb,
+ (select ss_store_sk, ss_item_sk, sum(ss_sales_price) as revenue
+ from store_sales, date_dim
+ where ss_sold_date_sk = d_date_sk and d_month_seq between 1176 and 1176+11
+ group by ss_store_sk, ss_item_sk) sc
+ where sb.ss_store_sk = sc.ss_store_sk and
+ sc.revenue <= 0.1 * sb.ave and
+ s_store_sk = sc.ss_store_sk and
+ i_item_sk = sc.ss_item_sk
+ order by s_store_name, i_item_desc
+limit 100;
+
+-- end query 65 in stream 0 using template query65.tpl
+-- start query 66 in stream 0 using template query66.tpl
+select
+ w_warehouse_name
+ ,w_warehouse_sq_ft
+ ,w_city
+ ,w_county
+ ,w_state
+ ,w_country
+ ,ship_carriers
+ ,year
+ ,sum(jan_sales) as jan_sales
+ ,sum(feb_sales) as feb_sales
+ ,sum(mar_sales) as mar_sales
+ ,sum(apr_sales) as apr_sales
+ ,sum(may_sales) as may_sales
+ ,sum(jun_sales) as jun_sales
+ ,sum(jul_sales) as jul_sales
+ ,sum(aug_sales) as aug_sales
+ ,sum(sep_sales) as sep_sales
+ ,sum(oct_sales) as oct_sales
+ ,sum(nov_sales) as nov_sales
+ ,sum(dec_sales) as dec_sales
+ ,sum(jan_sales/w_warehouse_sq_ft) as jan_sales_per_sq_foot
+ ,sum(feb_sales/w_warehouse_sq_ft) as feb_sales_per_sq_foot
+ ,sum(mar_sales/w_warehouse_sq_ft) as mar_sales_per_sq_foot
+ ,sum(apr_sales/w_warehouse_sq_ft) as apr_sales_per_sq_foot
+ ,sum(may_sales/w_warehouse_sq_ft) as may_sales_per_sq_foot
+ ,sum(jun_sales/w_warehouse_sq_ft) as jun_sales_per_sq_foot
+ ,sum(jul_sales/w_warehouse_sq_ft) as jul_sales_per_sq_foot
+ ,sum(aug_sales/w_warehouse_sq_ft) as aug_sales_per_sq_foot
+ ,sum(sep_sales/w_warehouse_sq_ft) as sep_sales_per_sq_foot
+ ,sum(oct_sales/w_warehouse_sq_ft) as oct_sales_per_sq_foot
+ ,sum(nov_sales/w_warehouse_sq_ft) as nov_sales_per_sq_foot
+ ,sum(dec_sales/w_warehouse_sq_ft) as dec_sales_per_sq_foot
+ ,sum(jan_net) as jan_net
+ ,sum(feb_net) as feb_net
+ ,sum(mar_net) as mar_net
+ ,sum(apr_net) as apr_net
+ ,sum(may_net) as may_net
+ ,sum(jun_net) as jun_net
+ ,sum(jul_net) as jul_net
+ ,sum(aug_net) as aug_net
+ ,sum(sep_net) as sep_net
+ ,sum(oct_net) as oct_net
+ ,sum(nov_net) as nov_net
+ ,sum(dec_net) as dec_net
+ from (
+ select
+ w_warehouse_name
+ ,w_warehouse_sq_ft
+ ,w_city
+ ,w_county
+ ,w_state
+ ,w_country
+ ,'ORIENTAL' || ',' || 'BOXBUNDLES' as ship_carriers
+ ,d_year as year
+ ,sum(case when d_moy = 1
+ then ws_ext_sales_price* ws_quantity else 0 end) as jan_sales
+ ,sum(case when d_moy = 2
+ then ws_ext_sales_price* ws_quantity else 0 end) as feb_sales
+ ,sum(case when d_moy = 3
+ then ws_ext_sales_price* ws_quantity else 0 end) as mar_sales
+ ,sum(case when d_moy = 4
+ then ws_ext_sales_price* ws_quantity else 0 end) as apr_sales
+ ,sum(case when d_moy = 5
+ then ws_ext_sales_price* ws_quantity else 0 end) as may_sales
+ ,sum(case when d_moy = 6
+ then ws_ext_sales_price* ws_quantity else 0 end) as jun_sales
+ ,sum(case when d_moy = 7
+ then ws_ext_sales_price* ws_quantity else 0 end) as jul_sales
+ ,sum(case when d_moy = 8
+ then ws_ext_sales_price* ws_quantity else 0 end) as aug_sales
+ ,sum(case when d_moy = 9
+ then ws_ext_sales_price* ws_quantity else 0 end) as sep_sales
+ ,sum(case when d_moy = 10
+ then ws_ext_sales_price* ws_quantity else 0 end) as oct_sales
+ ,sum(case when d_moy = 11
+ then ws_ext_sales_price* ws_quantity else 0 end) as nov_sales
+ ,sum(case when d_moy = 12
+ then ws_ext_sales_price* ws_quantity else 0 end) as dec_sales
+ ,sum(case when d_moy = 1
+ then ws_net_paid_inc_ship * ws_quantity else 0 end) as jan_net
+ ,sum(case when d_moy = 2
+ then ws_net_paid_inc_ship * ws_quantity else 0 end) as feb_net
+ ,sum(case when d_moy = 3
+ then ws_net_paid_inc_ship * ws_quantity else 0 end) as mar_net
+ ,sum(case when d_moy = 4
+ then ws_net_paid_inc_ship * ws_quantity else 0 end) as apr_net
+ ,sum(case when d_moy = 5
+ then ws_net_paid_inc_ship * ws_quantity else 0 end) as may_net
+ ,sum(case when d_moy = 6
+ then ws_net_paid_inc_ship * ws_quantity else 0 end) as jun_net
+ ,sum(case when d_moy = 7
+ then ws_net_paid_inc_ship * ws_quantity else 0 end) as jul_net
+ ,sum(case when d_moy = 8
+ then ws_net_paid_inc_ship * ws_quantity else 0 end) as aug_net
+ ,sum(case when d_moy = 9
+ then ws_net_paid_inc_ship * ws_quantity else 0 end) as sep_net
+ ,sum(case when d_moy = 10
+ then ws_net_paid_inc_ship * ws_quantity else 0 end) as oct_net
+ ,sum(case when d_moy = 11
+ then ws_net_paid_inc_ship * ws_quantity else 0 end) as nov_net
+ ,sum(case when d_moy = 12
+ then ws_net_paid_inc_ship * ws_quantity else 0 end) as dec_net
+ from
+ web_sales
+ ,warehouse
+ ,date_dim
+ ,time_dim
+ ,ship_mode
+ where
+ ws_warehouse_sk = w_warehouse_sk
+ and ws_sold_date_sk = d_date_sk
+ and ws_sold_time_sk = t_time_sk
+ and ws_ship_mode_sk = sm_ship_mode_sk
+ and d_year = 2001
+ and t_time between 42970 and 42970+28800
+ and sm_carrier in ('ORIENTAL','BOXBUNDLES')
+ group by
+ w_warehouse_name
+ ,w_warehouse_sq_ft
+ ,w_city
+ ,w_county
+ ,w_state
+ ,w_country
+ ,d_year
+ union all
+ select
+ w_warehouse_name
+ ,w_warehouse_sq_ft
+ ,w_city
+ ,w_county
+ ,w_state
+ ,w_country
+ ,'ORIENTAL' || ',' || 'BOXBUNDLES' as ship_carriers
+ ,d_year as year
+ ,sum(case when d_moy = 1
+ then cs_ext_list_price* cs_quantity else 0 end) as jan_sales
+ ,sum(case when d_moy = 2
+ then cs_ext_list_price* cs_quantity else 0 end) as feb_sales
+ ,sum(case when d_moy = 3
+ then cs_ext_list_price* cs_quantity else 0 end) as mar_sales
+ ,sum(case when d_moy = 4
+ then cs_ext_list_price* cs_quantity else 0 end) as apr_sales
+ ,sum(case when d_moy = 5
+ then cs_ext_list_price* cs_quantity else 0 end) as may_sales
+ ,sum(case when d_moy = 6
+ then cs_ext_list_price* cs_quantity else 0 end) as jun_sales
+ ,sum(case when d_moy = 7
+ then cs_ext_list_price* cs_quantity else 0 end) as jul_sales
+ ,sum(case when d_moy = 8
+ then cs_ext_list_price* cs_quantity else 0 end) as aug_sales
+ ,sum(case when d_moy = 9
+ then cs_ext_list_price* cs_quantity else 0 end) as sep_sales
+ ,sum(case when d_moy = 10
+ then cs_ext_list_price* cs_quantity else 0 end) as oct_sales
+ ,sum(case when d_moy = 11
+ then cs_ext_list_price* cs_quantity else 0 end) as nov_sales
+ ,sum(case when d_moy = 12
+ then cs_ext_list_price* cs_quantity else 0 end) as dec_sales
+ ,sum(case when d_moy = 1
+ then cs_net_paid * cs_quantity else 0 end) as jan_net
+ ,sum(case when d_moy = 2
+ then cs_net_paid * cs_quantity else 0 end) as feb_net
+ ,sum(case when d_moy = 3
+ then cs_net_paid * cs_quantity else 0 end) as mar_net
+ ,sum(case when d_moy = 4
+ then cs_net_paid * cs_quantity else 0 end) as apr_net
+ ,sum(case when d_moy = 5
+ then cs_net_paid * cs_quantity else 0 end) as may_net
+ ,sum(case when d_moy = 6
+ then cs_net_paid * cs_quantity else 0 end) as jun_net
+ ,sum(case when d_moy = 7
+ then cs_net_paid * cs_quantity else 0 end) as jul_net
+ ,sum(case when d_moy = 8
+ then cs_net_paid * cs_quantity else 0 end) as aug_net
+ ,sum(case when d_moy = 9
+ then cs_net_paid * cs_quantity else 0 end) as sep_net
+ ,sum(case when d_moy = 10
+ then cs_net_paid * cs_quantity else 0 end) as oct_net
+ ,sum(case when d_moy = 11
+ then cs_net_paid * cs_quantity else 0 end) as nov_net
+ ,sum(case when d_moy = 12
+ then cs_net_paid * cs_quantity else 0 end) as dec_net
+ from
+ catalog_sales
+ ,warehouse
+ ,date_dim
+ ,time_dim
+ ,ship_mode
+ where
+ cs_warehouse_sk = w_warehouse_sk
+ and cs_sold_date_sk = d_date_sk
+ and cs_sold_time_sk = t_time_sk
+ and cs_ship_mode_sk = sm_ship_mode_sk
+ and d_year = 2001
+ and t_time between 42970 AND 42970+28800
+ and sm_carrier in ('ORIENTAL','BOXBUNDLES')
+ group by
+ w_warehouse_name
+ ,w_warehouse_sq_ft
+ ,w_city
+ ,w_county
+ ,w_state
+ ,w_country
+ ,d_year
+ ) x
+ group by
+ w_warehouse_name
+ ,w_warehouse_sq_ft
+ ,w_city
+ ,w_county
+ ,w_state
+ ,w_country
+ ,ship_carriers
+ ,year
+ order by w_warehouse_name
+ limit 100;
+
+-- end query 66 in stream 0 using template query66.tpl
+-- start query 67 in stream 0 using template query67.tpl
+select *
+from (select i_category
+ ,i_class
+ ,i_brand
+ ,i_product_name
+ ,d_year
+ ,d_qoy
+ ,d_moy
+ ,s_store_id
+ ,sumsales
+ ,rank() over (partition by i_category order by sumsales desc) rk
+ from (select i_category
+ ,i_class
+ ,i_brand
+ ,i_product_name
+ ,d_year
+ ,d_qoy
+ ,d_moy
+ ,s_store_id
+ ,sum(coalesce(ss_sales_price*ss_quantity,0)) sumsales
+ from store_sales
+ ,date_dim
+ ,store
+ ,item
+ where ss_sold_date_sk=d_date_sk
+ and ss_item_sk=i_item_sk
+ and ss_store_sk = s_store_sk
+ and d_month_seq between 1217 and 1217+11
+ group by rollup(i_category, i_class, i_brand, i_product_name, d_year, d_qoy, d_moy,s_store_id))dw1) dw2
+where rk <= 100
+order by i_category
+ ,i_class
+ ,i_brand
+ ,i_product_name
+ ,d_year
+ ,d_qoy
+ ,d_moy
+ ,s_store_id
+ ,sumsales
+ ,rk
+limit 100;
+
+-- end query 67 in stream 0 using template query67.tpl
+-- start query 68 in stream 0 using template query68.tpl
+select c_last_name
+ ,c_first_name
+ ,ca_city
+ ,bought_city
+ ,ss_ticket_number
+ ,extended_price
+ ,extended_tax
+ ,list_price
+ from (select ss_ticket_number
+ ,ss_customer_sk
+ ,ca_city bought_city
+ ,sum(ss_ext_sales_price) extended_price
+ ,sum(ss_ext_list_price) list_price
+ ,sum(ss_ext_tax) extended_tax
+ from store_sales
+ ,date_dim
+ ,store
+ ,household_demographics
+ ,customer_address
+ where store_sales.ss_sold_date_sk = date_dim.d_date_sk
+ and store_sales.ss_store_sk = store.s_store_sk
+ and store_sales.ss_hdemo_sk = household_demographics.hd_demo_sk
+ and store_sales.ss_addr_sk = customer_address.ca_address_sk
+ and date_dim.d_dom between 1 and 2
+ and (household_demographics.hd_dep_count = 3 or
+ household_demographics.hd_vehicle_count= 4)
+ and date_dim.d_year in (1998,1998+1,1998+2)
+ and store.s_city in ('Fairview','Midway')
+ group by ss_ticket_number
+ ,ss_customer_sk
+ ,ss_addr_sk,ca_city) dn
+ ,customer
+ ,customer_address current_addr
+ where ss_customer_sk = c_customer_sk
+ and customer.c_current_addr_sk = current_addr.ca_address_sk
+ and current_addr.ca_city <> bought_city
+ order by c_last_name
+ ,ss_ticket_number
+ limit 100;
+
+-- end query 68 in stream 0 using template query68.tpl
+-- start query 69 in stream 0 using template query69.tpl
+select
+ cd_gender,
+ cd_marital_status,
+ cd_education_status,
+ count(*) cnt1,
+ cd_purchase_estimate,
+ count(*) cnt2,
+ cd_credit_rating,
+ count(*) cnt3
+ from
+ customer c,customer_address ca,customer_demographics
+ where
+ c.c_current_addr_sk = ca.ca_address_sk and
+ ca_state in ('IL','TX','ME') and
+ cd_demo_sk = c.c_current_cdemo_sk and
+ exists (select *
+ from store_sales,date_dim
+ where c.c_customer_sk = ss_customer_sk and
+ ss_sold_date_sk = d_date_sk and
+ d_year = 2002 and
+ d_moy between 1 and 1+2) and
+ (not exists (select *
+ from web_sales,date_dim
+ where c.c_customer_sk = ws_bill_customer_sk and
+ ws_sold_date_sk = d_date_sk and
+ d_year = 2002 and
+ d_moy between 1 and 1+2) and
+ not exists (select *
+ from catalog_sales,date_dim
+ where c.c_customer_sk = cs_ship_customer_sk and
+ cs_sold_date_sk = d_date_sk and
+ d_year = 2002 and
+ d_moy between 1 and 1+2))
+ group by cd_gender,
+ cd_marital_status,
+ cd_education_status,
+ cd_purchase_estimate,
+ cd_credit_rating
+ order by cd_gender,
+ cd_marital_status,
+ cd_education_status,
+ cd_purchase_estimate,
+ cd_credit_rating
+ limit 100;
+
+-- end query 69 in stream 0 using template query69.tpl
+-- start query 70 in stream 0 using template query70.tpl
+select
+ sum(ss_net_profit) as total_sum
+ ,s_state
+ ,s_county
+ ,grouping(s_state)+grouping(s_county) as lochierarchy
+ ,rank() over (
+ partition by grouping(s_state)+grouping(s_county),
+ case when grouping(s_county) = 0 then s_state end
+ order by sum(ss_net_profit) desc) as rank_within_parent
+ from
+ store_sales
+ ,date_dim d1
+ ,store
+ where
+ d1.d_month_seq between 1220 and 1220+11
+ and d1.d_date_sk = ss_sold_date_sk
+ and s_store_sk = ss_store_sk
+ and s_state in
+ ( select s_state
+ from (select s_state as s_state,
+ rank() over ( partition by s_state order by sum(ss_net_profit) desc) as ranking
+ from store_sales, store, date_dim
+ where d_month_seq between 1220 and 1220+11
+ and d_date_sk = ss_sold_date_sk
+ and s_store_sk = ss_store_sk
+ group by s_state
+ ) tmp1
+ where ranking <= 5
+ )
+ group by rollup(s_state,s_county)
+ order by
+ lochierarchy desc
+ ,case when lochierarchy = 0 then s_state end
+ ,rank_within_parent
+ limit 100;
+
+-- end query 70 in stream 0 using template query70.tpl
+-- start query 71 in stream 0 using template query71.tpl
+select i_brand_id brand_id, i_brand brand,t_hour,t_minute,
+ sum(ext_price) ext_price
+ from item, (select ws_ext_sales_price as ext_price,
+ ws_sold_date_sk as sold_date_sk,
+ ws_item_sk as sold_item_sk,
+ ws_sold_time_sk as time_sk
+ from web_sales,date_dim
+ where d_date_sk = ws_sold_date_sk
+ and d_moy=12
+ and d_year=2002
+ union all
+ select cs_ext_sales_price as ext_price,
+ cs_sold_date_sk as sold_date_sk,
+ cs_item_sk as sold_item_sk,
+ cs_sold_time_sk as time_sk
+ from catalog_sales,date_dim
+ where d_date_sk = cs_sold_date_sk
+ and d_moy=12
+ and d_year=2002
+ union all
+ select ss_ext_sales_price as ext_price,
+ ss_sold_date_sk as sold_date_sk,
+ ss_item_sk as sold_item_sk,
+ ss_sold_time_sk as time_sk
+ from store_sales,date_dim
+ where d_date_sk = ss_sold_date_sk
+ and d_moy=12
+ and d_year=2002
+ ) tmp,time_dim
+ where
+ sold_item_sk = i_item_sk
+ and i_manager_id=1
+ and time_sk = t_time_sk
+ and (t_meal_time = 'breakfast' or t_meal_time = 'dinner')
+ group by i_brand, i_brand_id,t_hour,t_minute
+ order by ext_price desc, i_brand_id
+ ;
+
+-- end query 71 in stream 0 using template query71.tpl
+-- start query 72 in stream 0 using template query72.tpl
+select i_item_desc
+ ,w_warehouse_name
+ ,d1.d_week_seq
+ ,sum(case when p_promo_sk is null then 1 else 0 end) no_promo
+ ,sum(case when p_promo_sk is not null then 1 else 0 end) promo
+ ,count(*) total_cnt
+from catalog_sales
+join inventory on (cs_item_sk = inv_item_sk)
+join warehouse on (w_warehouse_sk=inv_warehouse_sk)
+join item on (i_item_sk = cs_item_sk)
+join customer_demographics on (cs_bill_cdemo_sk = cd_demo_sk)
+join household_demographics on (cs_bill_hdemo_sk = hd_demo_sk)
+join date_dim d1 on (cs_sold_date_sk = d1.d_date_sk)
+join date_dim d2 on (inv_date_sk = d2.d_date_sk)
+join date_dim d3 on (cs_ship_date_sk = d3.d_date_sk)
+left outer join promotion on (cs_promo_sk=p_promo_sk)
+left outer join catalog_returns on (cr_item_sk = cs_item_sk and cr_order_number = cs_order_number)
+where d1.d_week_seq = d2.d_week_seq
+ and inv_quantity_on_hand < cs_quantity
+ and d3.d_date > d1.d_date + 5
+ and hd_buy_potential = '1001-5000'
+ and d1.d_year = 1998
+ and cd_marital_status = 'S'
+group by i_item_desc,w_warehouse_name,d1.d_week_seq
+order by total_cnt desc, i_item_desc, w_warehouse_name, d_week_seq
+limit 100;
+
+-- end query 72 in stream 0 using template query72.tpl
+-- start query 73 in stream 0 using template query73.tpl
+select c_last_name
+ ,c_first_name
+ ,c_salutation
+ ,c_preferred_cust_flag
+ ,ss_ticket_number
+ ,cnt from
+ (select ss_ticket_number
+ ,ss_customer_sk
+ ,count(*) cnt
+ from store_sales,date_dim,store,household_demographics
+ where store_sales.ss_sold_date_sk = date_dim.d_date_sk
+ and store_sales.ss_store_sk = store.s_store_sk
+ and store_sales.ss_hdemo_sk = household_demographics.hd_demo_sk
+ and date_dim.d_dom between 1 and 2
+ and (household_demographics.hd_buy_potential = '1001-5000' or
+ household_demographics.hd_buy_potential = '5001-10000')
+ and household_demographics.hd_vehicle_count > 0
+ and case when household_demographics.hd_vehicle_count > 0 then
+ household_demographics.hd_dep_count/ household_demographics.hd_vehicle_count else null end > 1
+ and date_dim.d_year in (2000,2000+1,2000+2)
+ and store.s_county in ('Williamson County','Williamson County','Williamson County','Williamson County')
+ group by ss_ticket_number,ss_customer_sk) dj,customer
+ where ss_customer_sk = c_customer_sk
+ and cnt between 1 and 5
+ order by cnt desc, c_last_name asc;
+
+-- end query 73 in stream 0 using template query73.tpl
+-- start query 74 in stream 0 using template query74.tpl
+with year_total as (
+ select c_customer_id customer_id
+ ,c_first_name customer_first_name
+ ,c_last_name customer_last_name
+ ,d_year as year
+ ,max(ss_net_paid) year_total
+ ,'s' sale_type
+ from customer
+ ,store_sales
+ ,date_dim
+ where c_customer_sk = ss_customer_sk
+ and ss_sold_date_sk = d_date_sk
+ and d_year in (1999,1999+1)
+ group by c_customer_id
+ ,c_first_name
+ ,c_last_name
+ ,d_year
+ union all
+ select c_customer_id customer_id
+ ,c_first_name customer_first_name
+ ,c_last_name customer_last_name
+ ,d_year as year
+ ,max(ws_net_paid) year_total
+ ,'w' sale_type
+ from customer
+ ,web_sales
+ ,date_dim
+ where c_customer_sk = ws_bill_customer_sk
+ and ws_sold_date_sk = d_date_sk
+ and d_year in (1999,1999+1)
+ group by c_customer_id
+ ,c_first_name
+ ,c_last_name
+ ,d_year
+ )
+ select
+ t_s_secyear.customer_id, t_s_secyear.customer_first_name, t_s_secyear.customer_last_name
+ from year_total t_s_firstyear
+ ,year_total t_s_secyear
+ ,year_total t_w_firstyear
+ ,year_total t_w_secyear
+ where t_s_secyear.customer_id = t_s_firstyear.customer_id
+ and t_s_firstyear.customer_id = t_w_secyear.customer_id
+ and t_s_firstyear.customer_id = t_w_firstyear.customer_id
+ and t_s_firstyear.sale_type = 's'
+ and t_w_firstyear.sale_type = 'w'
+ and t_s_secyear.sale_type = 's'
+ and t_w_secyear.sale_type = 'w'
+ and t_s_firstyear.year = 1999
+ and t_s_secyear.year = 1999+1
+ and t_w_firstyear.year = 1999
+ and t_w_secyear.year = 1999+1
+ and t_s_firstyear.year_total > 0
+ and t_w_firstyear.year_total > 0
+ and case when t_w_firstyear.year_total > 0 then t_w_secyear.year_total / t_w_firstyear.year_total else null end
+ > case when t_s_firstyear.year_total > 0 then t_s_secyear.year_total / t_s_firstyear.year_total else null end
+ order by 1,3,2
+limit 100;
+
+-- end query 74 in stream 0 using template query74.tpl
+-- start query 75 in stream 0 using template query75.tpl
+WITH all_sales AS (
+ SELECT d_year
+ ,i_brand_id
+ ,i_class_id
+ ,i_category_id
+ ,i_manufact_id
+ ,SUM(sales_cnt) AS sales_cnt
+ ,SUM(sales_amt) AS sales_amt
+ FROM (SELECT d_year
+ ,i_brand_id
+ ,i_class_id
+ ,i_category_id
+ ,i_manufact_id
+ ,cs_quantity - COALESCE(cr_return_quantity,0) AS sales_cnt
+ ,cs_ext_sales_price - COALESCE(cr_return_amount,0.0) AS sales_amt
+ FROM catalog_sales JOIN item ON i_item_sk=cs_item_sk
+ JOIN date_dim ON d_date_sk=cs_sold_date_sk
+ LEFT JOIN catalog_returns ON (cs_order_number=cr_order_number
+ AND cs_item_sk=cr_item_sk)
+ WHERE i_category='Sports'
+ UNION
+ SELECT d_year
+ ,i_brand_id
+ ,i_class_id
+ ,i_category_id
+ ,i_manufact_id
+ ,ss_quantity - COALESCE(sr_return_quantity,0) AS sales_cnt
+ ,ss_ext_sales_price - COALESCE(sr_return_amt,0.0) AS sales_amt
+ FROM store_sales JOIN item ON i_item_sk=ss_item_sk
+ JOIN date_dim ON d_date_sk=ss_sold_date_sk
+ LEFT JOIN store_returns ON (ss_ticket_number=sr_ticket_number
+ AND ss_item_sk=sr_item_sk)
+ WHERE i_category='Sports'
+ UNION
+ SELECT d_year
+ ,i_brand_id
+ ,i_class_id
+ ,i_category_id
+ ,i_manufact_id
+ ,ws_quantity - COALESCE(wr_return_quantity,0) AS sales_cnt
+ ,ws_ext_sales_price - COALESCE(wr_return_amt,0.0) AS sales_amt
+ FROM web_sales JOIN item ON i_item_sk=ws_item_sk
+ JOIN date_dim ON d_date_sk=ws_sold_date_sk
+ LEFT JOIN web_returns ON (ws_order_number=wr_order_number
+ AND ws_item_sk=wr_item_sk)
+ WHERE i_category='Sports') sales_detail
+ GROUP BY d_year, i_brand_id, i_class_id, i_category_id, i_manufact_id)
+ SELECT prev_yr.d_year AS prev_year
+ ,curr_yr.d_year AS year
+ ,curr_yr.i_brand_id
+ ,curr_yr.i_class_id
+ ,curr_yr.i_category_id
+ ,curr_yr.i_manufact_id
+ ,prev_yr.sales_cnt AS prev_yr_cnt
+ ,curr_yr.sales_cnt AS curr_yr_cnt
+ ,curr_yr.sales_cnt-prev_yr.sales_cnt AS sales_cnt_diff
+ ,curr_yr.sales_amt-prev_yr.sales_amt AS sales_amt_diff
+ FROM all_sales curr_yr, all_sales prev_yr
+ WHERE curr_yr.i_brand_id=prev_yr.i_brand_id
+ AND curr_yr.i_class_id=prev_yr.i_class_id
+ AND curr_yr.i_category_id=prev_yr.i_category_id
+ AND curr_yr.i_manufact_id=prev_yr.i_manufact_id
+ AND curr_yr.d_year=2002
+ AND prev_yr.d_year=2002-1
+ AND CAST(curr_yr.sales_cnt AS DECIMAL(17,2))/CAST(prev_yr.sales_cnt AS DECIMAL(17,2))<0.9
+ ORDER BY sales_cnt_diff,sales_amt_diff
+ limit 100;
+
+-- end query 75 in stream 0 using template query75.tpl
+-- start query 76 in stream 0 using template query76.tpl
+select channel, col_name, d_year, d_qoy, i_category, COUNT(*) sales_cnt, SUM(ext_sales_price) sales_amt FROM (
+ SELECT 'store' as channel, 'ss_customer_sk' col_name, d_year, d_qoy, i_category, ss_ext_sales_price ext_sales_price
+ FROM store_sales, item, date_dim
+ WHERE ss_customer_sk IS NULL
+ AND ss_sold_date_sk=d_date_sk
+ AND ss_item_sk=i_item_sk
+ UNION ALL
+ SELECT 'web' as channel, 'ws_promo_sk' col_name, d_year, d_qoy, i_category, ws_ext_sales_price ext_sales_price
+ FROM web_sales, item, date_dim
+ WHERE ws_promo_sk IS NULL
+ AND ws_sold_date_sk=d_date_sk
+ AND ws_item_sk=i_item_sk
+ UNION ALL
+ SELECT 'catalog' as channel, 'cs_bill_customer_sk' col_name, d_year, d_qoy, i_category, cs_ext_sales_price ext_sales_price
+ FROM catalog_sales, item, date_dim
+ WHERE cs_bill_customer_sk IS NULL
+ AND cs_sold_date_sk=d_date_sk
+ AND cs_item_sk=i_item_sk) foo
+GROUP BY channel, col_name, d_year, d_qoy, i_category
+ORDER BY channel, col_name, d_year, d_qoy, i_category
+limit 100;
+
+-- end query 76 in stream 0 using template query76.tpl
+-- start query 77 in stream 0 using template query77.tpl
+with ss as
+ (select s_store_sk,
+ sum(ss_ext_sales_price) as sales,
+ sum(ss_net_profit) as profit
+ from store_sales,
+ date_dim,
+ store
+ where ss_sold_date_sk = d_date_sk
+ and d_date between cast('2000-08-10' as date)
+ and (cast('2000-08-10' as date) + 30 days)
+ and ss_store_sk = s_store_sk
+ group by s_store_sk)
+ ,
+ sr as
+ (select s_store_sk,
+ sum(sr_return_amt) as returns,
+ sum(sr_net_loss) as profit_loss
+ from store_returns,
+ date_dim,
+ store
+ where sr_returned_date_sk = d_date_sk
+ and d_date between cast('2000-08-10' as date)
+ and (cast('2000-08-10' as date) + 30 days)
+ and sr_store_sk = s_store_sk
+ group by s_store_sk),
+ cs as
+ (select cs_call_center_sk,
+ sum(cs_ext_sales_price) as sales,
+ sum(cs_net_profit) as profit
+ from catalog_sales,
+ date_dim
+ where cs_sold_date_sk = d_date_sk
+ and d_date between cast('2000-08-10' as date)
+ and (cast('2000-08-10' as date) + 30 days)
+ group by cs_call_center_sk
+ ),
+ cr as
+ (select cr_call_center_sk,
+ sum(cr_return_amount) as returns,
+ sum(cr_net_loss) as profit_loss
+ from catalog_returns,
+ date_dim
+ where cr_returned_date_sk = d_date_sk
+ and d_date between cast('2000-08-10' as date)
+ and (cast('2000-08-10' as date) + 30 days)
+ group by cr_call_center_sk
+ ),
+ ws as
+ ( select wp_web_page_sk,
+ sum(ws_ext_sales_price) as sales,
+ sum(ws_net_profit) as profit
+ from web_sales,
+ date_dim,
+ web_page
+ where ws_sold_date_sk = d_date_sk
+ and d_date between cast('2000-08-10' as date)
+ and (cast('2000-08-10' as date) + 30 days)
+ and ws_web_page_sk = wp_web_page_sk
+ group by wp_web_page_sk),
+ wr as
+ (select wp_web_page_sk,
+ sum(wr_return_amt) as returns,
+ sum(wr_net_loss) as profit_loss
+ from web_returns,
+ date_dim,
+ web_page
+ where wr_returned_date_sk = d_date_sk
+ and d_date between cast('2000-08-10' as date)
+ and (cast('2000-08-10' as date) + 30 days)
+ and wr_web_page_sk = wp_web_page_sk
+ group by wp_web_page_sk)
+ select channel
+ , id
+ , sum(sales) as sales
+ , sum(returns) as returns
+ , sum(profit) as profit
+ from
+ (select 'store channel' as channel
+ , ss.s_store_sk as id
+ , sales
+ , coalesce(returns, 0) as returns
+ , (profit - coalesce(profit_loss,0)) as profit
+ from ss left join sr
+ on ss.s_store_sk = sr.s_store_sk
+ union all
+ select 'catalog channel' as channel
+ , cs_call_center_sk as id
+ , sales
+ , returns
+ , (profit - profit_loss) as profit
+ from cs
+ , cr
+ union all
+ select 'web channel' as channel
+ , ws.wp_web_page_sk as id
+ , sales
+ , coalesce(returns, 0) returns
+ , (profit - coalesce(profit_loss,0)) as profit
+ from ws left join wr
+ on ws.wp_web_page_sk = wr.wp_web_page_sk
+ ) x
+ group by rollup (channel, id)
+ order by channel
+ ,id
+ limit 100;
+
+-- end query 77 in stream 0 using template query77.tpl
+-- start query 78 in stream 0 using template query78.tpl
+with ws as
+ (select d_year AS ws_sold_year, ws_item_sk,
+ ws_bill_customer_sk ws_customer_sk,
+ sum(ws_quantity) ws_qty,
+ sum(ws_wholesale_cost) ws_wc,
+ sum(ws_sales_price) ws_sp
+ from web_sales
+ left join web_returns on wr_order_number=ws_order_number and ws_item_sk=wr_item_sk
+ join date_dim on ws_sold_date_sk = d_date_sk
+ where wr_order_number is null
+ group by d_year, ws_item_sk, ws_bill_customer_sk
+ ),
+cs as
+ (select d_year AS cs_sold_year, cs_item_sk,
+ cs_bill_customer_sk cs_customer_sk,
+ sum(cs_quantity) cs_qty,
+ sum(cs_wholesale_cost) cs_wc,
+ sum(cs_sales_price) cs_sp
+ from catalog_sales
+ left join catalog_returns on cr_order_number=cs_order_number and cs_item_sk=cr_item_sk
+ join date_dim on cs_sold_date_sk = d_date_sk
+ where cr_order_number is null
+ group by d_year, cs_item_sk, cs_bill_customer_sk
+ ),
+ss as
+ (select d_year AS ss_sold_year, ss_item_sk,
+ ss_customer_sk,
+ sum(ss_quantity) ss_qty,
+ sum(ss_wholesale_cost) ss_wc,
+ sum(ss_sales_price) ss_sp
+ from store_sales
+ left join store_returns on sr_ticket_number=ss_ticket_number and ss_item_sk=sr_item_sk
+ join date_dim on ss_sold_date_sk = d_date_sk
+ where sr_ticket_number is null
+ group by d_year, ss_item_sk, ss_customer_sk
+ )
+ select
+ss_customer_sk,
+round(ss_qty/(coalesce(ws_qty,0)+coalesce(cs_qty,0)),2) ratio,
+ss_qty store_qty, ss_wc store_wholesale_cost, ss_sp store_sales_price,
+coalesce(ws_qty,0)+coalesce(cs_qty,0) other_chan_qty,
+coalesce(ws_wc,0)+coalesce(cs_wc,0) other_chan_wholesale_cost,
+coalesce(ws_sp,0)+coalesce(cs_sp,0) other_chan_sales_price
+from ss
+left join ws on (ws_sold_year=ss_sold_year and ws_item_sk=ss_item_sk and ws_customer_sk=ss_customer_sk)
+left join cs on (cs_sold_year=ss_sold_year and cs_item_sk=ss_item_sk and cs_customer_sk=ss_customer_sk)
+where (coalesce(ws_qty,0)>0 or coalesce(cs_qty, 0)>0) and ss_sold_year=1998
+order by
+ ss_customer_sk,
+ ss_qty desc, ss_wc desc, ss_sp desc,
+ other_chan_qty,
+ other_chan_wholesale_cost,
+ other_chan_sales_price,
+ ratio
+limit 100;
+
+-- end query 78 in stream 0 using template query78.tpl
+-- start query 79 in stream 0 using template query79.tpl
+select
+ c_last_name,c_first_name,substr(s_city,1,30),ss_ticket_number,amt,profit
+ from
+ (select ss_ticket_number
+ ,ss_customer_sk
+ ,store.s_city
+ ,sum(ss_coupon_amt) amt
+ ,sum(ss_net_profit) profit
+ from store_sales,date_dim,store,household_demographics
+ where store_sales.ss_sold_date_sk = date_dim.d_date_sk
+ and store_sales.ss_store_sk = store.s_store_sk
+ and store_sales.ss_hdemo_sk = household_demographics.hd_demo_sk
+ and (household_demographics.hd_dep_count = 7 or household_demographics.hd_vehicle_count > -1)
+ and date_dim.d_dow = 1
+ and date_dim.d_year in (2000,2000+1,2000+2)
+ and store.s_number_employees between 200 and 295
+ group by ss_ticket_number,ss_customer_sk,ss_addr_sk,store.s_city) ms,customer
+ where ss_customer_sk = c_customer_sk
+ order by c_last_name,c_first_name,substr(s_city,1,30), profit
+limit 100;
+
+-- end query 79 in stream 0 using template query79.tpl
+-- start query 80 in stream 0 using template query80.tpl
+with ssr as
+ (select s_store_id as store_id,
+ sum(ss_ext_sales_price) as sales,
+ sum(coalesce(sr_return_amt, 0)) as returns,
+ sum(ss_net_profit - coalesce(sr_net_loss, 0)) as profit
+ from store_sales left outer join store_returns on
+ (ss_item_sk = sr_item_sk and ss_ticket_number = sr_ticket_number),
+ date_dim,
+ store,
+ item,
+ promotion
+ where ss_sold_date_sk = d_date_sk
+ and d_date between cast('2002-08-14' as date)
+ and (cast('2002-08-14' as date) + 30 days)
+ and ss_store_sk = s_store_sk
+ and ss_item_sk = i_item_sk
+ and i_current_price > 50
+ and ss_promo_sk = p_promo_sk
+ and p_channel_tv = 'N'
+ group by s_store_id)
+ ,
+ csr as
+ (select cp_catalog_page_id as catalog_page_id,
+ sum(cs_ext_sales_price) as sales,
+ sum(coalesce(cr_return_amount, 0)) as returns,
+ sum(cs_net_profit - coalesce(cr_net_loss, 0)) as profit
+ from catalog_sales left outer join catalog_returns on
+ (cs_item_sk = cr_item_sk and cs_order_number = cr_order_number),
+ date_dim,
+ catalog_page,
+ item,
+ promotion
+ where cs_sold_date_sk = d_date_sk
+ and d_date between cast('2002-08-14' as date)
+ and (cast('2002-08-14' as date) + 30 days)
+ and cs_catalog_page_sk = cp_catalog_page_sk
+ and cs_item_sk = i_item_sk
+ and i_current_price > 50
+ and cs_promo_sk = p_promo_sk
+ and p_channel_tv = 'N'
+group by cp_catalog_page_id)
+ ,
+ wsr as
+ (select web_site_id,
+ sum(ws_ext_sales_price) as sales,
+ sum(coalesce(wr_return_amt, 0)) as returns,
+ sum(ws_net_profit - coalesce(wr_net_loss, 0)) as profit
+ from web_sales left outer join web_returns on
+ (ws_item_sk = wr_item_sk and ws_order_number = wr_order_number),
+ date_dim,
+ web_site,
+ item,
+ promotion
+ where ws_sold_date_sk = d_date_sk
+ and d_date between cast('2002-08-14' as date)
+ and (cast('2002-08-14' as date) + 30 days)
+ and ws_web_site_sk = web_site_sk
+ and ws_item_sk = i_item_sk
+ and i_current_price > 50
+ and ws_promo_sk = p_promo_sk
+ and p_channel_tv = 'N'
+group by web_site_id)
+ select channel
+ , id
+ , sum(sales) as sales
+ , sum(returns) as returns
+ , sum(profit) as profit
+ from
+ (select 'store channel' as channel
+ , 'store' || store_id as id
+ , sales
+ , returns
+ , profit
+ from ssr
+ union all
+ select 'catalog channel' as channel
+ , 'catalog_page' || catalog_page_id as id
+ , sales
+ , returns
+ , profit
+ from csr
+ union all
+ select 'web channel' as channel
+ , 'web_site' || web_site_id as id
+ , sales
+ , returns
+ , profit
+ from wsr
+ ) x
+ group by rollup (channel, id)
+ order by channel
+ ,id
+ limit 100;
+
+-- end query 80 in stream 0 using template query80.tpl
+-- start query 81 in stream 0 using template query81.tpl
+with customer_total_return as
+ (select cr_returning_customer_sk as ctr_customer_sk
+ ,ca_state as ctr_state,
+ sum(cr_return_amt_inc_tax) as ctr_total_return
+ from catalog_returns
+ ,date_dim
+ ,customer_address
+ where cr_returned_date_sk = d_date_sk
+ and d_year =2001
+ and cr_returning_addr_sk = ca_address_sk
+ group by cr_returning_customer_sk
+ ,ca_state )
+ select c_customer_id,c_salutation,c_first_name,c_last_name,ca_street_number,ca_street_name
+ ,ca_street_type,ca_suite_number,ca_city,ca_county,ca_state,ca_zip,ca_country,ca_gmt_offset
+ ,ca_location_type,ctr_total_return
+ from customer_total_return ctr1
+ ,customer_address
+ ,customer
+ where ctr1.ctr_total_return > (select avg(ctr_total_return)*1.2
+ from customer_total_return ctr2
+ where ctr1.ctr_state = ctr2.ctr_state)
+ and ca_address_sk = c_current_addr_sk
+ and ca_state = 'TN'
+ and ctr1.ctr_customer_sk = c_customer_sk
+ order by c_customer_id,c_salutation,c_first_name,c_last_name,ca_street_number,ca_street_name
+ ,ca_street_type,ca_suite_number,ca_city,ca_county,ca_state,ca_zip,ca_country,ca_gmt_offset
+ ,ca_location_type,ctr_total_return
+ limit 100;
+
+-- end query 81 in stream 0 using template query81.tpl
+-- start query 82 in stream 0 using template query82.tpl
+select i_item_id
+ ,i_item_desc
+ ,i_current_price
+ from item, inventory, date_dim, store_sales
+ where i_current_price between 58 and 58+30
+ and inv_item_sk = i_item_sk
+ and d_date_sk=inv_date_sk
+ and d_date between cast('2001-01-13' as date) and (cast('2001-01-13' as date) + 60 days)
+ and i_manufact_id in (259,559,580,485)
+ and inv_quantity_on_hand between 100 and 500
+ and ss_item_sk = i_item_sk
+ group by i_item_id,i_item_desc,i_current_price
+ order by i_item_id
+ limit 100;
+
+-- end query 82 in stream 0 using template query82.tpl
+-- start query 83 in stream 0 using template query83.tpl
+with sr_items as
+ (select i_item_id item_id,
+ sum(sr_return_quantity) sr_item_qty
+ from store_returns,
+ item,
+ date_dim
+ where sr_item_sk = i_item_sk
+ and d_date in
+ (select d_date
+ from date_dim
+ where d_week_seq in
+ (select d_week_seq
+ from date_dim
+ where d_date in ('2001-07-13','2001-09-10','2001-11-16')))
+ and sr_returned_date_sk = d_date_sk
+ group by i_item_id),
+ cr_items as
+ (select i_item_id item_id,
+ sum(cr_return_quantity) cr_item_qty
+ from catalog_returns,
+ item,
+ date_dim
+ where cr_item_sk = i_item_sk
+ and d_date in
+ (select d_date
+ from date_dim
+ where d_week_seq in
+ (select d_week_seq
+ from date_dim
+ where d_date in ('2001-07-13','2001-09-10','2001-11-16')))
+ and cr_returned_date_sk = d_date_sk
+ group by i_item_id),
+ wr_items as
+ (select i_item_id item_id,
+ sum(wr_return_quantity) wr_item_qty
+ from web_returns,
+ item,
+ date_dim
+ where wr_item_sk = i_item_sk
+ and d_date in
+ (select d_date
+ from date_dim
+ where d_week_seq in
+ (select d_week_seq
+ from date_dim
+ where d_date in ('2001-07-13','2001-09-10','2001-11-16')))
+ and wr_returned_date_sk = d_date_sk
+ group by i_item_id)
+ select sr_items.item_id
+ ,sr_item_qty
+ ,sr_item_qty/(sr_item_qty+cr_item_qty+wr_item_qty)/3.0 * 100 sr_dev
+ ,cr_item_qty
+ ,cr_item_qty/(sr_item_qty+cr_item_qty+wr_item_qty)/3.0 * 100 cr_dev
+ ,wr_item_qty
+ ,wr_item_qty/(sr_item_qty+cr_item_qty+wr_item_qty)/3.0 * 100 wr_dev
+ ,(sr_item_qty+cr_item_qty+wr_item_qty)/3.0 average
+ from sr_items
+ ,cr_items
+ ,wr_items
+ where sr_items.item_id=cr_items.item_id
+ and sr_items.item_id=wr_items.item_id
+ order by sr_items.item_id
+ ,sr_item_qty
+ limit 100;
+
+-- end query 83 in stream 0 using template query83.tpl
+-- start query 84 in stream 0 using template query84.tpl
+select c_customer_id as customer_id
+ , coalesce(c_last_name,'') || ', ' || coalesce(c_first_name,'') as customername
+ from customer
+ ,customer_address
+ ,customer_demographics
+ ,household_demographics
+ ,income_band
+ ,store_returns
+ where ca_city = 'Woodland'
+ and c_current_addr_sk = ca_address_sk
+ and ib_lower_bound >= 60306
+ and ib_upper_bound <= 60306 + 50000
+ and ib_income_band_sk = hd_income_band_sk
+ and cd_demo_sk = c_current_cdemo_sk
+ and hd_demo_sk = c_current_hdemo_sk
+ and sr_cdemo_sk = cd_demo_sk
+ order by c_customer_id
+ limit 100;
+
+-- end query 84 in stream 0 using template query84.tpl
+-- start query 85 in stream 0 using template query85.tpl
+select substr(r_reason_desc,1,20)
+ ,avg(ws_quantity)
+ ,avg(wr_refunded_cash)
+ ,avg(wr_fee)
+ from web_sales, web_returns, web_page, customer_demographics cd1,
+ customer_demographics cd2, customer_address, date_dim, reason
+ where ws_web_page_sk = wp_web_page_sk
+ and ws_item_sk = wr_item_sk
+ and ws_order_number = wr_order_number
+ and ws_sold_date_sk = d_date_sk and d_year = 1998
+ and cd1.cd_demo_sk = wr_refunded_cdemo_sk
+ and cd2.cd_demo_sk = wr_returning_cdemo_sk
+ and ca_address_sk = wr_refunded_addr_sk
+ and r_reason_sk = wr_reason_sk
+ and
+ (
+ (
+ cd1.cd_marital_status = 'D'
+ and
+ cd1.cd_marital_status = cd2.cd_marital_status
+ and
+ cd1.cd_education_status = 'Primary'
+ and
+ cd1.cd_education_status = cd2.cd_education_status
+ and
+ ws_sales_price between 100.00 and 150.00
+ )
+ or
+ (
+ cd1.cd_marital_status = 'S'
+ and
+ cd1.cd_marital_status = cd2.cd_marital_status
+ and
+ cd1.cd_education_status = 'College'
+ and
+ cd1.cd_education_status = cd2.cd_education_status
+ and
+ ws_sales_price between 50.00 and 100.00
+ )
+ or
+ (
+ cd1.cd_marital_status = 'U'
+ and
+ cd1.cd_marital_status = cd2.cd_marital_status
+ and
+ cd1.cd_education_status = 'Advanced Degree'
+ and
+ cd1.cd_education_status = cd2.cd_education_status
+ and
+ ws_sales_price between 150.00 and 200.00
+ )
+ )
+ and
+ (
+ (
+ ca_country = 'United States'
+ and
+ ca_state in ('NC', 'TX', 'IA')
+ and ws_net_profit between 100 and 200
+ )
+ or
+ (
+ ca_country = 'United States'
+ and
+ ca_state in ('WI', 'WV', 'GA')
+ and ws_net_profit between 150 and 300
+ )
+ or
+ (
+ ca_country = 'United States'
+ and
+ ca_state in ('OK', 'VA', 'KY')
+ and ws_net_profit between 50 and 250
+ )
+ )
+group by r_reason_desc
+order by substr(r_reason_desc,1,20)
+ ,avg(ws_quantity)
+ ,avg(wr_refunded_cash)
+ ,avg(wr_fee)
+limit 100;
+
+-- end query 85 in stream 0 using template query85.tpl
+-- start query 86 in stream 0 using template query86.tpl
+select
+ sum(ws_net_paid) as total_sum
+ ,i_category
+ ,i_class
+ ,grouping(i_category)+grouping(i_class) as lochierarchy
+ ,rank() over (
+ partition by grouping(i_category)+grouping(i_class),
+ case when grouping(i_class) = 0 then i_category end
+ order by sum(ws_net_paid) desc) as rank_within_parent
+ from
+ web_sales
+ ,date_dim d1
+ ,item
+ where
+ d1.d_month_seq between 1186 and 1186+11
+ and d1.d_date_sk = ws_sold_date_sk
+ and i_item_sk = ws_item_sk
+ group by rollup(i_category,i_class)
+ order by
+ lochierarchy desc,
+ case when lochierarchy = 0 then i_category end,
+ rank_within_parent
+ limit 100;
+
+-- end query 86 in stream 0 using template query86.tpl
+-- start query 87 in stream 0 using template query87.tpl
+select count(*)
+from ((select distinct c_last_name, c_first_name, d_date
+ from store_sales, date_dim, customer
+ where store_sales.ss_sold_date_sk = date_dim.d_date_sk
+ and store_sales.ss_customer_sk = customer.c_customer_sk
+ and d_month_seq between 1202 and 1202+11)
+ except
+ (select distinct c_last_name, c_first_name, d_date
+ from catalog_sales, date_dim, customer
+ where catalog_sales.cs_sold_date_sk = date_dim.d_date_sk
+ and catalog_sales.cs_bill_customer_sk = customer.c_customer_sk
+ and d_month_seq between 1202 and 1202+11)
+ except
+ (select distinct c_last_name, c_first_name, d_date
+ from web_sales, date_dim, customer
+ where web_sales.ws_sold_date_sk = date_dim.d_date_sk
+ and web_sales.ws_bill_customer_sk = customer.c_customer_sk
+ and d_month_seq between 1202 and 1202+11)
+) cool_cust
+;
+
+-- end query 87 in stream 0 using template query87.tpl
+-- start query 88 in stream 0 using template query88.tpl
+select *
+from
+ (select count(*) h8_30_to_9
+ from store_sales, household_demographics , time_dim, store
+ where ss_sold_time_sk = time_dim.t_time_sk
+ and ss_hdemo_sk = household_demographics.hd_demo_sk
+ and ss_store_sk = s_store_sk
+ and time_dim.t_hour = 8
+ and time_dim.t_minute >= 30
+ and ((household_demographics.hd_dep_count = 0 and household_demographics.hd_vehicle_count<=0+2) or
+ (household_demographics.hd_dep_count = -1 and household_demographics.hd_vehicle_count<=-1+2) or
+ (household_demographics.hd_dep_count = 3 and household_demographics.hd_vehicle_count<=3+2))
+ and store.s_store_name = 'ese') s1,
+ (select count(*) h9_to_9_30
+ from store_sales, household_demographics , time_dim, store
+ where ss_sold_time_sk = time_dim.t_time_sk
+ and ss_hdemo_sk = household_demographics.hd_demo_sk
+ and ss_store_sk = s_store_sk
+ and time_dim.t_hour = 9
+ and time_dim.t_minute < 30
+ and ((household_demographics.hd_dep_count = 0 and household_demographics.hd_vehicle_count<=0+2) or
+ (household_demographics.hd_dep_count = -1 and household_demographics.hd_vehicle_count<=-1+2) or
+ (household_demographics.hd_dep_count = 3 and household_demographics.hd_vehicle_count<=3+2))
+ and store.s_store_name = 'ese') s2,
+ (select count(*) h9_30_to_10
+ from store_sales, household_demographics , time_dim, store
+ where ss_sold_time_sk = time_dim.t_time_sk
+ and ss_hdemo_sk = household_demographics.hd_demo_sk
+ and ss_store_sk = s_store_sk
+ and time_dim.t_hour = 9
+ and time_dim.t_minute >= 30
+ and ((household_demographics.hd_dep_count = 0 and household_demographics.hd_vehicle_count<=0+2) or
+ (household_demographics.hd_dep_count = -1 and household_demographics.hd_vehicle_count<=-1+2) or
+ (household_demographics.hd_dep_count = 3 and household_demographics.hd_vehicle_count<=3+2))
+ and store.s_store_name = 'ese') s3,
+ (select count(*) h10_to_10_30
+ from store_sales, household_demographics , time_dim, store
+ where ss_sold_time_sk = time_dim.t_time_sk
+ and ss_hdemo_sk = household_demographics.hd_demo_sk
+ and ss_store_sk = s_store_sk
+ and time_dim.t_hour = 10
+ and time_dim.t_minute < 30
+ and ((household_demographics.hd_dep_count = 0 and household_demographics.hd_vehicle_count<=0+2) or
+ (household_demographics.hd_dep_count = -1 and household_demographics.hd_vehicle_count<=-1+2) or
+ (household_demographics.hd_dep_count = 3 and household_demographics.hd_vehicle_count<=3+2))
+ and store.s_store_name = 'ese') s4,
+ (select count(*) h10_30_to_11
+ from store_sales, household_demographics , time_dim, store
+ where ss_sold_time_sk = time_dim.t_time_sk
+ and ss_hdemo_sk = household_demographics.hd_demo_sk
+ and ss_store_sk = s_store_sk
+ and time_dim.t_hour = 10
+ and time_dim.t_minute >= 30
+ and ((household_demographics.hd_dep_count = 0 and household_demographics.hd_vehicle_count<=0+2) or
+ (household_demographics.hd_dep_count = -1 and household_demographics.hd_vehicle_count<=-1+2) or
+ (household_demographics.hd_dep_count = 3 and household_demographics.hd_vehicle_count<=3+2))
+ and store.s_store_name = 'ese') s5,
+ (select count(*) h11_to_11_30
+ from store_sales, household_demographics , time_dim, store
+ where ss_sold_time_sk = time_dim.t_time_sk
+ and ss_hdemo_sk = household_demographics.hd_demo_sk
+ and ss_store_sk = s_store_sk
+ and time_dim.t_hour = 11
+ and time_dim.t_minute < 30
+ and ((household_demographics.hd_dep_count = 0 and household_demographics.hd_vehicle_count<=0+2) or
+ (household_demographics.hd_dep_count = -1 and household_demographics.hd_vehicle_count<=-1+2) or
+ (household_demographics.hd_dep_count = 3 and household_demographics.hd_vehicle_count<=3+2))
+ and store.s_store_name = 'ese') s6,
+ (select count(*) h11_30_to_12
+ from store_sales, household_demographics , time_dim, store
+ where ss_sold_time_sk = time_dim.t_time_sk
+ and ss_hdemo_sk = household_demographics.hd_demo_sk
+ and ss_store_sk = s_store_sk
+ and time_dim.t_hour = 11
+ and time_dim.t_minute >= 30
+ and ((household_demographics.hd_dep_count = 0 and household_demographics.hd_vehicle_count<=0+2) or
+ (household_demographics.hd_dep_count = -1 and household_demographics.hd_vehicle_count<=-1+2) or
+ (household_demographics.hd_dep_count = 3 and household_demographics.hd_vehicle_count<=3+2))
+ and store.s_store_name = 'ese') s7,
+ (select count(*) h12_to_12_30
+ from store_sales, household_demographics , time_dim, store
+ where ss_sold_time_sk = time_dim.t_time_sk
+ and ss_hdemo_sk = household_demographics.hd_demo_sk
+ and ss_store_sk = s_store_sk
+ and time_dim.t_hour = 12
+ and time_dim.t_minute < 30
+ and ((household_demographics.hd_dep_count = 0 and household_demographics.hd_vehicle_count<=0+2) or
+ (household_demographics.hd_dep_count = -1 and household_demographics.hd_vehicle_count<=-1+2) or
+ (household_demographics.hd_dep_count = 3 and household_demographics.hd_vehicle_count<=3+2))
+ and store.s_store_name = 'ese') s8
+;
+
+-- end query 88 in stream 0 using template query88.tpl
+-- start query 89 in stream 0 using template query89.tpl
+select *
+from(
+select i_category, i_class, i_brand,
+ s_store_name, s_company_name,
+ d_moy,
+ sum(ss_sales_price) sum_sales,
+ avg(sum(ss_sales_price)) over
+ (partition by i_category, i_brand, s_store_name, s_company_name)
+ avg_monthly_sales
+from item, store_sales, date_dim, store
+where ss_item_sk = i_item_sk and
+ ss_sold_date_sk = d_date_sk and
+ ss_store_sk = s_store_sk and
+ d_year in (2001) and
+ ((i_category in ('Books','Children','Electronics') and
+ i_class in ('history','school-uniforms','audio')
+ )
+ or (i_category in ('Men','Sports','Shoes') and
+ i_class in ('pants','tennis','womens')
+ ))
+group by i_category, i_class, i_brand,
+ s_store_name, s_company_name, d_moy) tmp1
+where case when (avg_monthly_sales <> 0) then (abs(sum_sales - avg_monthly_sales) / avg_monthly_sales) else null end > 0.1
+order by sum_sales - avg_monthly_sales, s_store_name
+limit 100;
+
+-- end query 89 in stream 0 using template query89.tpl
+-- start query 90 in stream 0 using template query90.tpl
+select cast(amc as decimal(15,4))/cast(pmc as decimal(15,4)) am_pm_ratio
+ from ( select count(*) amc
+ from web_sales, household_demographics , time_dim, web_page
+ where ws_sold_time_sk = time_dim.t_time_sk
+ and ws_ship_hdemo_sk = household_demographics.hd_demo_sk
+ and ws_web_page_sk = web_page.wp_web_page_sk
+ and time_dim.t_hour between 12 and 12+1
+ and household_demographics.hd_dep_count = 6
+ and web_page.wp_char_count between 5000 and 5200) at,
+ ( select count(*) pmc
+ from web_sales, household_demographics , time_dim, web_page
+ where ws_sold_time_sk = time_dim.t_time_sk
+ and ws_ship_hdemo_sk = household_demographics.hd_demo_sk
+ and ws_web_page_sk = web_page.wp_web_page_sk
+ and time_dim.t_hour between 14 and 14+1
+ and household_demographics.hd_dep_count = 6
+ and web_page.wp_char_count between 5000 and 5200) pt
+ order by am_pm_ratio
+ limit 100;
+
+-- end query 90 in stream 0 using template query90.tpl
+-- start query 91 in stream 0 using template query91.tpl
+select
+ cc_call_center_id Call_Center,
+ cc_name Call_Center_Name,
+ cc_manager Manager,
+ sum(cr_net_loss) Returns_Loss
+from
+ call_center,
+ catalog_returns,
+ date_dim,
+ customer,
+ customer_address,
+ customer_demographics,
+ household_demographics
+where
+ cr_call_center_sk = cc_call_center_sk
+and cr_returned_date_sk = d_date_sk
+and cr_returning_customer_sk= c_customer_sk
+and cd_demo_sk = c_current_cdemo_sk
+and hd_demo_sk = c_current_hdemo_sk
+and ca_address_sk = c_current_addr_sk
+and d_year = 2000
+and d_moy = 12
+and ( (cd_marital_status = 'M' and cd_education_status = 'Unknown')
+ or(cd_marital_status = 'W' and cd_education_status = 'Advanced Degree'))
+and hd_buy_potential like 'Unknown%'
+and ca_gmt_offset = -7
+group by cc_call_center_id,cc_name,cc_manager,cd_marital_status,cd_education_status
+order by sum(cr_net_loss) desc;
+
+-- end query 91 in stream 0 using template query91.tpl
+-- start query 92 in stream 0 using template query92.tpl
+select
+ sum(ws_ext_discount_amt) as "Excess Discount Amount"
+from
+ web_sales
+ ,item
+ ,date_dim
+where
+i_manufact_id = 714
+and i_item_sk = ws_item_sk
+and d_date between '2000-02-01' and
+ (cast('2000-02-01' as date) + 90 days)
+and d_date_sk = ws_sold_date_sk
+and ws_ext_discount_amt
+ > (
+ SELECT
+ 1.3 * avg(ws_ext_discount_amt)
+ FROM
+ web_sales
+ ,date_dim
+ WHERE
+ ws_item_sk = i_item_sk
+ and d_date between '2000-02-01' and
+ (cast('2000-02-01' as date) + 90 days)
+ and d_date_sk = ws_sold_date_sk
+ )
+order by sum(ws_ext_discount_amt)
+limit 100;
+
+-- end query 92 in stream 0 using template query92.tpl
+-- start query 93 in stream 0 using template query93.tpl
+select ss_customer_sk
+ ,sum(act_sales) sumsales
+ from (select ss_item_sk
+ ,ss_ticket_number
+ ,ss_customer_sk
+ ,case when sr_return_quantity is not null then (ss_quantity-sr_return_quantity)*ss_sales_price
+ else (ss_quantity*ss_sales_price) end act_sales
+ from store_sales left outer join store_returns on (sr_item_sk = ss_item_sk
+ and sr_ticket_number = ss_ticket_number)
+ ,reason
+ where sr_reason_sk = r_reason_sk
+ and r_reason_desc = 'reason 58') t
+ group by ss_customer_sk
+ order by sumsales, ss_customer_sk
+limit 100;
+
+-- end query 93 in stream 0 using template query93.tpl
+-- start query 94 in stream 0 using template query94.tpl
+select
+ count(distinct ws_order_number) as "order count"
+ ,sum(ws_ext_ship_cost) as "total shipping cost"
+ ,sum(ws_net_profit) as "total net profit"
+from
+ web_sales ws1
+ ,date_dim
+ ,customer_address
+ ,web_site
+where
+ d_date between '2002-5-01' and
+ (cast('2002-5-01' as date) + 60 days)
+and ws1.ws_ship_date_sk = d_date_sk
+and ws1.ws_ship_addr_sk = ca_address_sk
+and ca_state = 'OK'
+and ws1.ws_web_site_sk = web_site_sk
+and web_company_name = 'pri'
+and exists (select *
+ from web_sales ws2
+ where ws1.ws_order_number = ws2.ws_order_number
+ and ws1.ws_warehouse_sk <> ws2.ws_warehouse_sk)
+and not exists(select *
+ from web_returns wr1
+ where ws1.ws_order_number = wr1.wr_order_number)
+order by count(distinct ws_order_number)
+limit 100;
+
+-- end query 94 in stream 0 using template query94.tpl
+-- start query 95 in stream 0 using template query95.tpl
+with ws_wh as
+(select ws1.ws_order_number,ws1.ws_warehouse_sk wh1,ws2.ws_warehouse_sk wh2
+ from web_sales ws1,web_sales ws2
+ where ws1.ws_order_number = ws2.ws_order_number
+ and ws1.ws_warehouse_sk <> ws2.ws_warehouse_sk)
+ select
+ count(distinct ws_order_number) as "order count"
+ ,sum(ws_ext_ship_cost) as "total shipping cost"
+ ,sum(ws_net_profit) as "total net profit"
+from
+ web_sales ws1
+ ,date_dim
+ ,customer_address
+ ,web_site
+where
+ d_date between '2001-4-01' and
+ (cast('2001-4-01' as date) + 60 days)
+and ws1.ws_ship_date_sk = d_date_sk
+and ws1.ws_ship_addr_sk = ca_address_sk
+and ca_state = 'VA'
+and ws1.ws_web_site_sk = web_site_sk
+and web_company_name = 'pri'
+and ws1.ws_order_number in (select ws_order_number
+ from ws_wh)
+and ws1.ws_order_number in (select wr_order_number
+ from web_returns,ws_wh
+ where wr_order_number = ws_wh.ws_order_number)
+order by count(distinct ws_order_number)
+limit 100;
+
+-- end query 95 in stream 0 using template query95.tpl
+-- start query 96 in stream 0 using template query96.tpl
+select count(*)
+from store_sales
+ ,household_demographics
+ ,time_dim, store
+where ss_sold_time_sk = time_dim.t_time_sk
+ and ss_hdemo_sk = household_demographics.hd_demo_sk
+ and ss_store_sk = s_store_sk
+ and time_dim.t_hour = 8
+ and time_dim.t_minute >= 30
+ and household_demographics.hd_dep_count = 0
+ and store.s_store_name = 'ese'
+order by count(*)
+limit 100;
+
+-- end query 96 in stream 0 using template query96.tpl
+-- start query 97 in stream 0 using template query97.tpl
+with ssci as (
+select ss_customer_sk customer_sk
+ ,ss_item_sk item_sk
+from store_sales,date_dim
+where ss_sold_date_sk = d_date_sk
+ and d_month_seq between 1199 and 1199 + 11
+group by ss_customer_sk
+ ,ss_item_sk),
+csci as(
+ select cs_bill_customer_sk customer_sk
+ ,cs_item_sk item_sk
+from catalog_sales,date_dim
+where cs_sold_date_sk = d_date_sk
+ and d_month_seq between 1199 and 1199 + 11
+group by cs_bill_customer_sk
+ ,cs_item_sk)
+ select sum(case when ssci.customer_sk is not null and csci.customer_sk is null then 1 else 0 end) store_only
+ ,sum(case when ssci.customer_sk is null and csci.customer_sk is not null then 1 else 0 end) catalog_only
+ ,sum(case when ssci.customer_sk is not null and csci.customer_sk is not null then 1 else 0 end) store_and_catalog
+from ssci full outer join csci on (ssci.customer_sk=csci.customer_sk
+ and ssci.item_sk = csci.item_sk)
+limit 100;
+
+-- end query 97 in stream 0 using template query97.tpl
+-- start query 98 in stream 0 using template query98.tpl
+select i_item_id
+ ,i_item_desc
+ ,i_category
+ ,i_class
+ ,i_current_price
+ ,sum(ss_ext_sales_price) as itemrevenue
+ ,sum(ss_ext_sales_price)*100/sum(sum(ss_ext_sales_price)) over
+ (partition by i_class) as revenueratio
+from
+ store_sales
+ ,item
+ ,date_dim
+where
+ ss_item_sk = i_item_sk
+ and i_category in ('Men', 'Sports', 'Jewelry')
+ and ss_sold_date_sk = d_date_sk
+ and d_date between cast('1999-02-05' as date)
+ and (cast('1999-02-05' as date) + 30 days)
+group by
+ i_item_id
+ ,i_item_desc
+ ,i_category
+ ,i_class
+ ,i_current_price
+order by
+ i_category
+ ,i_class
+ ,i_item_id
+ ,i_item_desc
+ ,revenueratio;
+
+-- end query 98 in stream 0 using template query98.tpl
+-- start query 99 in stream 0 using template query99.tpl
+select
+ substr(w_warehouse_name,1,20)
+ ,sm_type
+ ,cc_name
+ ,sum(case when (cs_ship_date_sk - cs_sold_date_sk <= 30 ) then 1 else 0 end) as "30 days"
+ ,sum(case when (cs_ship_date_sk - cs_sold_date_sk > 30) and
+ (cs_ship_date_sk - cs_sold_date_sk <= 60) then 1 else 0 end ) as "31-60 days"
+ ,sum(case when (cs_ship_date_sk - cs_sold_date_sk > 60) and
+ (cs_ship_date_sk - cs_sold_date_sk <= 90) then 1 else 0 end) as "61-90 days"
+ ,sum(case when (cs_ship_date_sk - cs_sold_date_sk > 90) and
+ (cs_ship_date_sk - cs_sold_date_sk <= 120) then 1 else 0 end) as "91-120 days"
+ ,sum(case when (cs_ship_date_sk - cs_sold_date_sk > 120) then 1 else 0 end) as ">120 days"
+from
+ catalog_sales
+ ,warehouse
+ ,ship_mode
+ ,call_center
+ ,date_dim
+where
+ d_month_seq between 1194 and 1194 + 11
+and cs_ship_date_sk = d_date_sk
+and cs_warehouse_sk = w_warehouse_sk
+and cs_ship_mode_sk = sm_ship_mode_sk
+and cs_call_center_sk = cc_call_center_sk
+group by
+ substr(w_warehouse_name,1,20)
+ ,sm_type
+ ,cc_name
+order by substr(w_warehouse_name,1,20)
+ ,sm_type
+ ,cc_name
+limit 100;
+
+-- end query 99 in stream 0 using template query99.tpl
diff --git a/tests/test_cases.py b/tests/test_cases.py
index 175dbd1..5c82bb4 100644
--- a/tests/test_cases.py
+++ b/tests/test_cases.py
@@ -1,48 +1,119 @@
+import testgres
import json
-import psycopg2
-import psycopg2.extensions
import re
-import select
import time
import xml.etree.ElementTree as ET
import yaml
from time import sleep
-
-def wait(conn):
- """wait for some event on connection to postgres"""
- while 1:
- state = conn.poll()
- if state == psycopg2.extensions.POLL_OK:
- break
- elif state == psycopg2.extensions.POLL_WRITE:
- select.select([], [conn.fileno()], [])
- elif state == psycopg2.extensions.POLL_READ:
- select.select([conn.fileno()], [], [])
+from multiprocessing import Process, Queue, Condition
+import subprocess
+import os
+
+class AsyncQueryExecutor():
+ """ Run query in separate process """
+ process = Process()
+ def __init__(self, node):
+ self.node = node
+ self.conn = testgres.connection.NodeConnection(node)
+ self.cursor = self.conn.cursor
+ self.backend_pid = self.conn.pid
+ self.res_q = Queue()
+ self.condition = Condition()
+ self.result = []
+
+ def run_internal(self, conn, query, multiple, res_q, condition):
+ condition.acquire()
+ commands = []
+ if multiple:
+ commands = query.split(';')
+ for i, cmd in enumerate(query.split(';')):
+ if (len(cmd.strip()) == 0):
+ del commands[i]
else:
- raise psycopg2.OperationalError("poll() returned %s" % state)
-
-def n_async_connect(config, n=1):
- """establish n asynchronious connections to the postgres with specified config"""
+ commands.append(query)
+
+ conn.begin()
+ condition.notify()
+ condition.release()
+ for cmd in commands:
+ try:
+ res = conn.execute(cmd)
+ res_q.put(res)
+ conn.commit()
+ except Exception, e:
+ print 'Unable to execute query: "', cmd ,'"'
+ print 'Reason: %s' %e
+ conn.rollback()
+ continue
+ return
- aconfig = config.copy()
- aconfig['async'] = True
+ def run(self, query, multiple = False):
+ """Run async query"""
+ self.process = Process(target=self.run_internal,
+ args=(self.conn, query, multiple, self.res_q, self.condition))
+ self.process.start()
+ self.condition.acquire()
+ self.condition.wait()
+
+ def wait(self):
+ self.result = self.res_q.get()
+ if self.process.is_alive():
+ self.process.join()
+
+ def terminate(self):
+ if self.process.is_alive():
+ self.node.psql("SELECT pg_cancel_backend(%d)" % self.backend_pid)
+ self.process.terminate()
+
+ def close(self):
+ self.terminate()
+ self.conn.close()
+
+def pqs_args(pid, verbose=False, costs=False, timing=False,
+ buffers=False, triggers=False, format='text'):
+ s = "%d, %s, %s, %s, %s, %s, '%s'" % (pid, verbose, costs, timing, buffers,
+ triggers, format)
+ return s
+
+def set_guc(conn, param, value):
+ conn.execute('set %s to %s' % (param, value))
+ conn.commit()
+
+def query_state(node, query, args={}, gucs={}, num_workers=0, expected_len=1, delay = 0):
+ """
+ Get intermediate state of 'query' on connection 'async_conn' after number of 'steps'
+ of node executions from start of query
+ """
result = []
- for _ in xrange(n):
- conn = psycopg2.connect(**aconfig)
- wait(conn)
- result.append(conn)
- return result
+ aq = AsyncQueryExecutor(node)
+ conn = testgres.connection.NodeConnection(node)
-def n_close(conns):
- """close connections to postgres"""
+ gucs.update({'enable_mergejoin' : 'off'})
+ gucs.update({'max_parallel_workers_per_gather' : num_workers})
+ for param, value in gucs.items():
+ set_guc(aq.conn, param, value)
- for conn in conns:
- conn.close()
+ aq.run(query)
+ sleep(delay)
+ # extract current state of query progress
+ while len(result) < expected_len and aq.process.is_alive():
+ result = conn.execute(r"""SELECT pid,
+ frame_number,
+ query_text,
+ plan,
+ leader_pid
+ FROM pg_query_state(%s);""" %
+ pqs_args(aq.backend_pid, **args))
+ aq.wait()
+ aq.close()
+ conn.close()
+ assert result[0][0] == aq.backend_pid and result[0][1] == 0 \
+ and result[0][2] == query and result[0][4] == None
-notices = []
+ return result
-def debug_output(qs, qs_len, pid, query, expected):
+def debug_output(qs, qs_len, pid, query, expected, expected2 = None):
something_happened = False
if (qs_len and len(qs) != qs_len ):
print "len(qs): ", len(qs), ", expected: ", qs_len
@@ -57,10 +128,15 @@ def debug_output(qs, qs_len, pid, query, expected):
print "qs[0][2]:\n", qs[0][2]
print "Expected:\n", query
something_happened = True
- if (not (re.match(expected, qs[0][3]))):
+ if (expected and not (re.match(expected, qs[0][3]))):
print "qs[0][3]:\n", qs[0][3]
print "Expected:\n", expected
something_happened = True
+ if (qs_len == 2 and expected2 and
+ not (re.match(expected2, qs[1][3]))):
+ print "qs[1][3]:\n", qs[1][3]
+ print "Expected:\n", expected
+ something_happened = True
if (qs[0][4] != None):
print "qs[0][4]: ", qs[0][4], "Expected: None"
something_happened = True
@@ -75,90 +151,31 @@ def debug_output(qs, qs_len, pid, query, expected):
if (something_happened):
print "If test have not crashed, then it's OK"
-def notices_warning():
- if (len(notices) > 0):
- print("")
- print("WARNING:")
- print(notices)
-
-def pg_query_state(config, pid, verbose=False, costs=False, timing=False, \
- buffers=False, triggers=False, format='text'):
- """
- Get query state from backend with specified pid and optional parameters.
- Save any warning, info, notice and log data in global variable 'notices'
- """
-
- global notices
-
- conn = psycopg2.connect(**config)
- curs = conn.cursor()
- result = []
- while not result:
- curs.callproc('pg_query_state', (pid, verbose, costs, timing, buffers, triggers, format))
- result = curs.fetchall()
- notices = conn.notices[:]
- conn.close()
- return result
-
-def test_deadlock(config):
+def test_deadlock(node):
"""test when two backends try to extract state of each other"""
- acon1, acon2 = n_async_connect(config, 2)
- acurs1 = acon1.cursor()
- acurs2 = acon2.cursor()
-
- while True:
- acurs1.callproc('pg_query_state', (acon2.get_backend_pid(),))
- acurs2.callproc('pg_query_state', (acon1.get_backend_pid(),))
+ async_query1 = AsyncQueryExecutor(node)
+ async_query2 = AsyncQueryExecutor(node)
- # listen acon1, acon2 with timeout = 10 sec to determine deadlock
- r, w, x = select.select([acon1.fileno(), acon2.fileno()], [], [], 10)
- assert (r or w or x), "Deadlock is happened under cross reading of query states"
-
- wait(acon1)
- wait(acon2)
+ for try_n in range(10):
+ async_query1.run("select pg_query_state(%d)" % async_query2.backend_pid)
+ async_query2.run("select pg_query_state(%d)" % async_query1.backend_pid)
+ async_query1.wait()
+ async_query2.wait()
# exit from loop if one backend could read state of execution 'pg_query_state'
# from other backend
- if acurs1.fetchone() or acurs2.fetchone():
+ if async_query1.result or async_query1.result:
break
+ expected = "Deadlock is happened under cross reading of query states"
+ assert re.match(expected, async_query1.result) or (re.search(expected, async_query2.result))
- n_close((acon1, acon2))
-
-def query_state(config, async_conn, query, args={}, num_workers=0):
- """
- Get intermediate state of 'query' on connection 'async_conn' after number of 'steps'
- of node executions from start of query
- """
-
- acurs = async_conn.cursor()
- conn = psycopg2.connect(**config)
- curs = conn.cursor()
-
- set_guc(async_conn, 'enable_mergejoin', 'off')
- set_guc(async_conn, 'max_parallel_workers_per_gather', num_workers)
- acurs.execute(query)
+ async_query1.close()
+ async_query2.close()
- # extract current state of query progress
- pg_qs_args = {
- 'config': config,
- 'pid': async_conn.get_backend_pid()
- }
- for k, v in args.iteritems():
- pg_qs_args[k] = v
- result = pg_query_state(**pg_qs_args)
- wait(async_conn)
-
- set_guc(async_conn, 'pg_query_state.executor_trace', 'off')
- set_guc(async_conn, 'enable_mergejoin', 'on')
-
- conn.close()
- return result
-
-def test_simple_query(config):
+def test_simple_query(node):
"""test statistics of simple query"""
- acon, = n_async_connect(config)
query = 'select count(*) from foo join bar on foo.c1=bar.c1'
expected = r"""Aggregate \(Current loop: actual rows=\d+, loop number=1\)
-> Hash Join \(Current loop: actual rows=\d+, loop number=1\)
@@ -168,49 +185,51 @@ def test_simple_query(config):
Buckets: \d+ Batches: \d+ Memory Usage: \d+kB
-> Seq Scan on bar \(Current loop: actual rows=\d+, loop number=1\)"""
- qs = query_state(config, acon, query)
- debug_output(qs, 1, acon.get_backend_pid(), query, expected)
- notices_warning()
- #assert len(qs) == 1 #Skip this check while output of test can be different
- assert qs[0][0] == acon.get_backend_pid() and qs[0][1] == 0 \
- and qs[0][2] == query and re.match(expected, qs[0][3]) and qs[0][4] == None
-
- n_close((acon,))
+ qs = query_state(node, query)
+ debug_output(qs, 1, None, query, expected)
+ assert re.match(expected, qs[0][3])
-def test_concurrent_access(config):
+def test_concurrent_access(node):
"""test when two backends compete with each other to extract state from third running backend"""
- acon1, acon2, acon3 = n_async_connect(config, 3)
- acurs1, acurs2, acurs3 = acon1.cursor(), acon2.cursor(), acon3.cursor()
+ acon1 = AsyncQueryExecutor(node)
+ acon2 = AsyncQueryExecutor(node)
+ acon3 = AsyncQueryExecutor(node)
+
query = 'select count(*) from foo join bar on foo.c1=bar.c1'
- set_guc(acon3, 'max_parallel_workers_per_gather', 0)
- acurs3.execute(query)
- time.sleep(0.1)
- acurs1.callproc('pg_query_state', (acon3.get_backend_pid(),))
- acurs2.callproc('pg_query_state', (acon3.get_backend_pid(),))
- wait(acon1)
- wait(acon2)
- wait(acon3)
-
- qs1, qs2 = acurs1.fetchall(), acurs2.fetchall()
- assert len(qs1) == len(qs2) == 1 \
- and qs1[0][0] == qs2[0][0] == acon3.get_backend_pid() \
- and qs1[0][1] == qs2[0][1] == 0 \
- and qs1[0][2] == qs2[0][2] == query \
- and len(qs1[0][3]) > 0 and len(qs2[0][3]) > 0 \
- and qs1[0][4] == qs2[0][4] == None
- #assert len(notices) == 0
- notices_warning()
-
- n_close((acon1, acon2, acon3))
-
-def test_nested_call(config):
+ set_guc(acon3.conn, 'max_parallel_workers_per_gather', 0)
+ acon3.run(query)
+
+ psq_query = r"""SELECT pid,
+ frame_number,
+ query_text,
+ plan,
+ leader_pid
+ FROM pg_query_state(%s);""" % pqs_args(acon3.backend_pid)
+
+ while len(acon1.result) < 1 and acon3.process.is_alive():
+ acon1.run(psq_query)
+ acon2.run(psq_query)
+ acon1.wait()
+ acon2.wait()
+ acon3.terminate()
+
+ qs1 = acon1.result
+ qs2 = acon2.result
+
+ assert acon3.backend_pid == qs1[0][0]
+ assert acon3.backend_pid == qs2[0][0]
+
+ acon1.close()
+ acon2.close()
+ acon3.close()
+
+def test_nested_call(node):
"""test statistics under calling function"""
- acon, = n_async_connect(config)
- util_conn = psycopg2.connect(**config)
- util_curs = util_conn.cursor()
+ conn = testgres.connection.NodeConnection(node)
+
create_function = """
create or replace function n_join_foo_bar() returns integer as $$
begin
@@ -231,29 +250,25 @@ def test_nested_call(config):
Buckets: \d+ Batches: \d+ Memory Usage: \d+kB
-> Seq Scan on bar \(Current loop: actual rows=\d+, loop number=1\)"""
- util_curs.execute(create_function)
- util_conn.commit()
+ conn.execute(create_function)
+ conn.commit()
- qs = query_state(config, acon, call_function)
+ qs = query_state(node, call_function, expected_len = 2)
+ debug_output(qs, 2, None, call_function, None, expected_nested)
assert len(qs) == 2 \
- and qs[0][0] == qs[1][0] == acon.get_backend_pid() \
and qs[0][1] == 0 and qs[1][1] == 1 \
and qs[0][2] == call_function and qs[0][3] == expected \
and qs[1][2] == nested_query and re.match(expected_nested, qs[1][3]) \
and qs[0][4] == qs[1][4] == None
- assert len(notices) == 0
- util_curs.execute(drop_function)
-
- util_conn.close()
- n_close((acon,))
+ conn.execute(drop_function)
+ conn.commit()
+ conn.close()
-def test_insert_on_conflict(config):
+def test_insert_on_conflict(node):
"""test statistics on conflicting tuples under INSERT ON CONFLICT query"""
- acon, = n_async_connect(config)
- util_conn = psycopg2.connect(**config)
- util_curs = util_conn.cursor()
+ util_conn = testgres.connection.NodeConnection(node)
add_field_uniqueness = 'alter table foo add constraint unique_c1 unique(c1)'
drop_field_uniqueness = 'alter table foo drop constraint unique_c1'
query = 'insert into foo select i, md5(random()::text) from generate_series(1, 30000) as i on conflict do nothing'
@@ -263,36 +278,21 @@ def test_insert_on_conflict(config):
Conflicting Tuples: \d+
-> Function Scan on generate_series i \(Current loop: actual rows=\d+, loop number=\d+\)"""
- util_curs.execute(add_field_uniqueness)
+ util_conn.execute(add_field_uniqueness)
util_conn.commit()
- qs = query_state(config, acon, query)
-
- debug_output(qs, 1, acon.get_backend_pid(), query, expected)
- notices_warning()
- #assert len(qs) == 1 \
- assert qs[0][0] == acon.get_backend_pid() and qs[0][1] == 0 \
- and qs[0][2] == query and re.match(expected, qs[0][3]) \
- and qs[0][4] == None
- assert len(notices) == 0
-
- util_curs.execute(drop_field_uniqueness)
+ qs = query_state(node, query)
+ debug_output(qs, 1, None, query, expected)
+ assert re.match(expected, qs[0][3])
+ util_conn.execute(drop_field_uniqueness)
util_conn.close()
- n_close((acon,))
-def set_guc(async_conn, param, value):
- acurs = async_conn.cursor()
- acurs.execute('set %s to %s' % (param, value))
- wait(async_conn)
-
-def test_trigger(config):
+def test_trigger(node):
"""test trigger statistics"""
- acon, = n_async_connect(config)
- acurs = acon.cursor()
- util_conn = psycopg2.connect(**config)
- util_curs = util_conn.cursor()
+ util_conn = testgres.connection.NodeConnection(node)
+
create_trigger_function = """
create or replace function unique_c1_in_foo() returns trigger as $$
begin
@@ -312,35 +312,23 @@ def test_trigger(config):
-> Function Scan on generate_series i \(Current loop: actual rows=\d+, loop number=1\)"""
trigger_suffix = r"""Trigger unique_foo_c1: calls=\d+"""
- util_curs.execute(create_trigger_function)
- util_curs.execute(create_trigger)
+ util_conn.execute(create_trigger_function)
+ util_conn.execute(create_trigger)
util_conn.commit()
- qs = query_state(config, acon, query, {'triggers': True})
- debug_output(qs, None, acon.get_backend_pid(), query, expected_upper)
- notices_warning()
- assert qs[0][0] == acon.get_backend_pid() and qs[0][1] == 0 \
- and qs[0][2] == query and re.match(expected_upper, qs[0][3]) \
- and qs[0][4] == None
- assert len(notices) == 0
-
- qs = query_state(config, acon, query, {'triggers': False})
- debug_output(qs, None, acon.get_backend_pid(), query, expected_upper)
- notices_warning()
- assert qs[0][0] == acon.get_backend_pid() and qs[0][1] == 0 \
- and qs[0][2] == query and re.match(expected_upper, qs[0][3]) \
- and qs[0][4] == None
- assert len(notices) == 0
-
- util_curs.execute(drop_temps)
+ qs = query_state(node, query, {'triggers': True}, delay = 1)
+ debug_output(qs, 2, None, query, expected_upper+'\n'+ trigger_suffix)
+ assert re.match(expected_upper+'\n'+ trigger_suffix, qs[0][3])
+ qs = query_state(node, query, {'triggers': False})
+ debug_output(qs, 1, None, query, expected_upper)
+ assert re.match(expected_upper, qs[0][3])
+ util_conn.execute(drop_temps)
util_conn.close()
- n_close((acon,))
-def test_costs(config):
+def test_costs(node):
"""test plan costs"""
- acon, = n_async_connect(config)
query = 'select count(*) from foo join bar on foo.c1=bar.c1'
expected = r"""Aggregate \(cost=\d+.\d+..\d+.\d+ rows=\d+ width=8\) \(Current loop: actual rows=0, loop number=1\)
-> Hash Join \(cost=\d+.\d+..\d+.\d+ rows=\d+ width=0\) \(Current loop: actual rows=0, loop number=1\)
@@ -350,18 +338,14 @@ def test_costs(config):
Buckets: \d+ Batches: \d+ Memory Usage: \d+kB
-> Seq Scan on bar \(cost=0.00..\d+.\d+ rows=\d+ width=4\) \(Current loop: actual rows=\d+, loop number=1\)"""
- qs = query_state(config, acon, query, {'costs': True})
+ qs = query_state(node, query, {'costs': True})
debug_output(qs, 1, None, query, expected)
- notices_warning()
- assert len(qs) == 1 and re.match(expected, qs[0][3])
- assert len(notices) == 0
-
- n_close((acon,))
+ assert len(qs) == 1
+ assert re.match(expected, qs[0][3])
def test_buffers(config):
"""test buffer statistics"""
- acon, = n_async_connect(config)
query = 'select count(*) from foo join bar on foo.c1=bar.c1'
expected = r"""Aggregate \(Current loop: actual rows=0, loop number=1\)
-> Hash Join \(Current loop: actual rows=0, loop number=1\)
@@ -373,38 +357,27 @@ def test_buffers(config):
-> Seq Scan on bar \(Current loop: actual rows=\d+, loop number=1\)
Buffers: .*"""
- set_guc(acon, 'pg_query_state.enable_buffers', 'on')
-
- qs = query_state(config, acon, query, {'buffers': True})
+ qs = query_state(config, query, {'buffers': True},
+ gucs = {'pg_query_state.enable_buffers' : 'on'})
debug_output(qs, 1, None, query, expected)
- notices_warning()
assert len(qs) == 1 and re.match(expected, qs[0][3])
- assert len(notices) == 0
-
- n_close((acon,))
-def test_timing(config):
+def test_timing(node):
"""test timing statistics"""
- acon, = n_async_connect(config)
query = 'select count(*) from foo join bar on foo.c1=bar.c1'
expected = r"""Aggregate \(Current loop: running time=\d+.\d+ actual rows=0, loop number=1\)
-> Hash Join \(Current loop: running time=\d+.\d+ actual rows=0, loop number=1\)
Hash Cond: \(foo.c1 = bar.c1\)
- -> Seq Scan on foo \(Current loop: actual time=\d+.\d+..\d+.\d+ rows=1, loop number=1\)
- -> Hash \(Current loop: running time=\d+.\d+ actual rows=0, loop number=1\)
- Buckets: \d+ Batches: \d+ Memory Usage: \d+kB
- -> Seq Scan on bar \(Current loop: actual time=\d+.\d+..\d+.\d+ rows=\d+, loop number=1\)"""
-
- set_guc(acon, 'pg_query_state.enable_timing', 'on')
+ -> Seq Scan on foo \(Current loop: (actual|running) time=\d+.\d+(..\d+.\d+)? (actual )?rows=\d+, loop number=1\)
+ -> Hash \(Current loop: running time=\d+.\d+ actual rows=0, loop number=1\)(
+ Buckets: \d+ Batches: \d+ Memory Usage: \d+kB)?
+ -> Seq Scan on bar \(Current loop: (actual|running) time=\d+.\d+(..\d+.\d+)* (actual )*rows=\d+, loop number=1\)"""
- qs = query_state(config, acon, query, {'timing': True})
+ qs = query_state(node, query, {'timing': True},
+ gucs={'pg_query_state.enable_timing' : 'on'})
debug_output(qs, 1, None, query, expected)
- notices_warning()
assert len(qs) == 1 and re.match(expected, qs[0][3])
- assert len(notices) == 0
-
- n_close((acon,))
def check_plan(plan):
assert plan.has_key('Current loop')
@@ -429,7 +402,6 @@ def check_xml(root):
def test_formats(config):
"""test all formats of pg_query_state output"""
- acon, = n_async_connect(config)
query = 'select count(*) from foo join bar on foo.c1=bar.c1'
expected = r"""Aggregate \(Current loop: actual rows=0, loop number=1\)
-> Hash Join \(Current loop: actual rows=0, loop number=1\)
@@ -439,61 +411,101 @@ def test_formats(config):
Buckets: \d+ Batches: \d+ Memory Usage: \d+kB
-> Seq Scan on bar \(Current loop: actual rows=\d+, loop number=1\)"""
- qs = query_state(config, acon, query, {'format': 'text'})
+ qs = query_state(config, query, {'format': 'text'})
debug_output(qs, 1, None, query, expected)
- notices_warning()
assert len(qs) == 1 and re.match(expected, qs[0][3])
- assert len(notices) == 0
- qs = query_state(config, acon, query, {'format': 'json'})
+ qs = query_state(config, query, {'format': 'json'})
try:
js_obj = json.loads(qs[0][3])
except ValueError:
assert False, 'Invalid json format'
assert len(qs) == 1
- assert len(notices) == 0
check_plan(js_obj['Plan'])
- qs = query_state(config, acon, query, {'format': 'xml'})
+ qs = query_state(config, query, {'format': 'xml'})
assert len(qs) == 1
- assert len(notices) == 0
try:
xml_root = ET.fromstring(qs[0][3])
except:
assert False, 'Invalid xml format'
check_xml(xml_root)
- qs = query_state(config, acon, query, {'format': 'yaml'})
+ qs = query_state(config, query, {'format': 'yaml'})
try:
yaml_doc = yaml.load(qs[0][3])
except:
assert False, 'Invalid yaml format'
assert len(qs) == 1
- assert len(notices) == 0
check_plan(yaml_doc['Plan'])
- n_close((acon,))
-
-def test_timing_buffers_conflicts(config):
+def test_timing_buffers_conflicts(node):
"""test when caller requests timing and buffers but counterpart turned off its"""
- acon, = n_async_connect(config)
query = 'select count(*) from foo join bar on foo.c1=bar.c1'
timing_pattern = '(?:running time=\d+.\d+)|(?:actual time=\d+.\d+..\d+.\d+)'
buffers_pattern = 'Buffers:'
- qs = query_state(config, acon, query, {'timing': True, 'buffers': False})
+ qs = query_state(node, query, {'timing': True, 'buffers': False})
assert len(qs) == 1 and not re.search(timing_pattern, qs[0][3])
- assert notices == ['WARNING: timing statistics disabled\n']
+ # Here you can add a check of notices in the case when the
+ # testgres will be able to receive them
+ #assert 'WARNING: timing statistics disabled\n' in notices
- qs = query_state(config, acon, query, {'timing': False, 'buffers': True})
+ qs = query_state(node, query, {'timing': False, 'buffers': True})
assert len(qs) == 1 and not re.search(buffers_pattern, qs[0][3])
- assert notices == ['WARNING: buffers statistics disabled\n']
+ #assert 'WARNING: buffers statistics disabled\n' in notices
- qs = query_state(config, acon, query, {'timing': True, 'buffers': True})
+ qs = query_state(node, query, {'timing': True, 'buffers': True})
assert len(qs) == 1 and not re.search(timing_pattern, qs[0][3]) \
and not re.search(buffers_pattern, qs[0][3])
- assert len(notices) == 2 and 'WARNING: timing statistics disabled\n' in notices \
- and 'WARNING: buffers statistics disabled\n' in notices
+ #assert len(notices) == 2 and 'WARNING: timing statistics disabled\n' in notices \
+ # and 'WARNING: buffers statistics disabled\n' in notices
- n_close((acon,))
+
+class DataLoadException(Exception): pass
+class StressTestException(Exception): pass
+
+def load_tpcds_data(node):
+ print 'Load tpcds...'
+ subprocess.call(['./tests/prepare_stress.sh'])
+ tables = open('tmp_stress/tpcds-kit/tools/tpcds.sql', 'r')
+ tables_sql = tables.read()
+ try:
+ # Create tables
+ node.psql(filename="tmp_stress/tpcds-kit/tools/tpcds.sql")
+ # Copy table data from files
+ for table_datafile in os.listdir('tmp_stress/tpcds-kit/tools/'):
+ if table_datafile.endswith(".dat"):
+ table_name = os.path.splitext(os.path.basename(table_datafile))[0]
+ copy_cmd = "\\copy %s FROM 'tmp_stress/tpcds-kit/tools/tables/%s' CSV DELIMITER '|'" % (table_name, table_datafile)
+ print "Load table ", table_name
+ node.safe_psql("TRUNCATE %s" % table_name)
+ node.safe_psql(copy_cmd)
+ except Exception, e:
+ raise DataLoadException('Load failed: %s' % e)
+ print 'done!'
+
+def stress_test(node):
+ """stress test"""
+ load_tpcds_data(node)
+
+ # execute query in separate thread
+ async_psql = AsyncQueryExecutor(node)
+ sql = open("tests/query_tpcds.sql",'r').read()
+ aq = AsyncQueryExecutor(node)
+ aq.run(sql, True)
+
+ conn = testgres.connection.NodeConnection(node)
+ while aq.process.is_alive():
+ try:
+ conn.execute('SELECT * FROM pg_query_state(%d)' % aq.backend_pid)
+ except Exception, e:
+ async_psql_ex = AsyncQueryExecutor(node)
+ async_psql_ex.run('SELECT state, query FROM pg_stat_activity where pid = %d;' % aq.backend_pid)
+ async_psql_ex.wait()
+ print 'pg_query_state FAILED'
+ print 'state of backend:'
+ print async_psql_ex.result
+ raise StressTestException('Unable to get query state: %s' % e)
+ aq.close()
From ee24bd4cbe907d59c7ae2d116943d43d6ad88c37 Mon Sep 17 00:00:00 2001
From: Sergey Cherkashin <4erkashin@list.ru>
Date: Sat, 10 Nov 2018 20:05:55 +0300
Subject: [PATCH 2/5] Fix regexps in python tests. Fix testing by Travis CI.
---
Dockerfile.tmpl | 2 +-
run_tests.sh | 5 ++--
tests/test_cases.py | 62 ++++++++++++++++++++++-----------------------
3 files changed, 35 insertions(+), 34 deletions(-)
diff --git a/Dockerfile.tmpl b/Dockerfile.tmpl
index 43d3691..0aab86f 100644
--- a/Dockerfile.tmpl
+++ b/Dockerfile.tmpl
@@ -4,7 +4,7 @@ FROM postgres:${PG_VERSION}-alpine
RUN apk add --no-cache \
openssl curl \
perl perl-ipc-run \
- make musl-dev gcc bison flex coreutils \
+ make musl-dev gcc bison flex coreutils linux-headers git\
zlib-dev libedit-dev \
clang clang-analyzer \
python2 python2-dev py2-virtualenv;
diff --git a/run_tests.sh b/run_tests.sh
index 0053aee..3a94cea 100755
--- a/run_tests.sh
+++ b/run_tests.sh
@@ -144,8 +144,9 @@ if [ -f regression.diffs ]; then cat regression.diffs; fi
# run python tests
set +x -e
-virtualenv /tmp/env && source /tmp/env/bin/activate &&
-pip install PyYAML && pip install psycopg2
+virtualenv /tmp/env && source /tmp/env/bin/activate
+pip install PyYAML
+pip install testgres
set -e #exit virtualenv with error code
if [ "$LEVEL" = "stress" ]; then
python tests/pg_qs_test_runner.py --stress
diff --git a/tests/test_cases.py b/tests/test_cases.py
index 5c82bb4..d111fa6 100644
--- a/tests/test_cases.py
+++ b/tests/test_cases.py
@@ -53,7 +53,7 @@ def run(self, query, multiple = False):
args=(self.conn, query, multiple, self.res_q, self.condition))
self.process.start()
self.condition.acquire()
- self.condition.wait()
+ self.condition.wait(5)
def wait(self):
self.result = self.res_q.get()
@@ -135,7 +135,7 @@ def debug_output(qs, qs_len, pid, query, expected, expected2 = None):
if (qs_len == 2 and expected2 and
not (re.match(expected2, qs[1][3]))):
print "qs[1][3]:\n", qs[1][3]
- print "Expected:\n", expected
+ print "Expected:\n", expected2
something_happened = True
if (qs[0][4] != None):
print "qs[0][4]: ", qs[0][4], "Expected: None"
@@ -181,8 +181,8 @@ def test_simple_query(node):
-> Hash Join \(Current loop: actual rows=\d+, loop number=1\)
Hash Cond: \(foo.c1 = bar.c1\)
-> Seq Scan on foo \(Current loop: actual rows=\d+, loop number=1\)
- -> Hash \(Current loop: actual rows=\d+, loop number=1\)
- Buckets: \d+ Batches: \d+ Memory Usage: \d+kB
+ -> Hash \(Current loop: actual rows=\d+, loop number=1\)(
+ Buckets: \d+ Batches: \d+ Memory Usage: \d+kB)?
-> Seq Scan on bar \(Current loop: actual rows=\d+, loop number=1\)"""
qs = query_state(node, query)
@@ -242,12 +242,12 @@ def test_nested_call(node):
expected = 'Function Scan on n_join_foo_bar (Current loop: actual rows=0, loop number=1)'
expected_nested = r"""Result \(Current loop: actual rows=0, loop number=1\)
InitPlan 1 \(returns \$0\)
- -> Aggregate \(Current loop: actual rows=0, loop number=1\)
- -> Hash Join \(Current loop: actual rows=0, loop number=1\)
+ -> Aggregate \(Current loop: actual rows=\d+, loop number=1\)
+ -> Hash Join \(Current loop: actual rows=\d+, loop number=1\)
Hash Cond: \(foo.c1 = bar.c1\)
- -> Seq Scan on foo \(Current loop: actual rows=1, loop number=1\)
- -> Hash \(Current loop: actual rows=0, loop number=1\)
- Buckets: \d+ Batches: \d+ Memory Usage: \d+kB
+ -> Seq Scan on foo \(Current loop: actual rows=\d+, loop number=1\)
+ -> Hash \(Current loop: actual rows=\d+, loop number=1\)(
+ Buckets: \d+ Batches: \d+ Memory Usage: \d+kB)?
-> Seq Scan on bar \(Current loop: actual rows=\d+, loop number=1\)"""
conn.execute(create_function)
@@ -282,7 +282,7 @@ def test_insert_on_conflict(node):
util_conn.commit()
qs = query_state(node, query)
- debug_output(qs, 1, None, query, expected)
+ debug_output(qs, None, None, query, expected)
assert re.match(expected, qs[0][3])
util_conn.execute(drop_field_uniqueness)
@@ -317,10 +317,10 @@ def test_trigger(node):
util_conn.commit()
qs = query_state(node, query, {'triggers': True}, delay = 1)
- debug_output(qs, 2, None, query, expected_upper+'\n'+ trigger_suffix)
+ debug_output(qs, None, None, query, expected_upper+'\n'+ trigger_suffix)
assert re.match(expected_upper+'\n'+ trigger_suffix, qs[0][3])
qs = query_state(node, query, {'triggers': False})
- debug_output(qs, 1, None, query, expected_upper)
+ debug_output(qs, None, None, query, expected_upper)
assert re.match(expected_upper, qs[0][3])
util_conn.execute(drop_temps)
@@ -331,11 +331,11 @@ def test_costs(node):
query = 'select count(*) from foo join bar on foo.c1=bar.c1'
expected = r"""Aggregate \(cost=\d+.\d+..\d+.\d+ rows=\d+ width=8\) \(Current loop: actual rows=0, loop number=1\)
- -> Hash Join \(cost=\d+.\d+..\d+.\d+ rows=\d+ width=0\) \(Current loop: actual rows=0, loop number=1\)
+ -> Hash Join \(cost=\d+.\d+..\d+.\d+ rows=\d+ width=0\) \(Current loop: actual rows=\d+, loop number=1\)
Hash Cond: \(foo.c1 = bar.c1\)
- -> Seq Scan on foo \(cost=0.00..\d+.\d+ rows=\d+ width=4\) \(Current loop: actual rows=1, loop number=1\)
- -> Hash \(cost=\d+.\d+..\d+.\d+ rows=\d+ width=4\) \(Current loop: actual rows=0, loop number=1\)
- Buckets: \d+ Batches: \d+ Memory Usage: \d+kB
+ -> Seq Scan on foo \(cost=0.00..\d+.\d+ rows=\d+ width=4\) \(Current loop: actual rows=\d+, loop number=1\)
+ -> Hash \(cost=\d+.\d+..\d+.\d+ rows=\d+ width=4\) \(Current loop: actual rows=\d+, loop number=1\)(
+ Buckets: \d+ Batches: \d+ Memory Usage: \d+kB)?
-> Seq Scan on bar \(cost=0.00..\d+.\d+ rows=\d+ width=4\) \(Current loop: actual rows=\d+, loop number=1\)"""
qs = query_state(node, query, {'costs': True})
@@ -348,14 +348,14 @@ def test_buffers(config):
query = 'select count(*) from foo join bar on foo.c1=bar.c1'
expected = r"""Aggregate \(Current loop: actual rows=0, loop number=1\)
- -> Hash Join \(Current loop: actual rows=0, loop number=1\)
+ -> Hash Join \(Current loop: actual rows=\d+, loop number=1\)
Hash Cond: \(foo.c1 = bar.c1\)
- -> Seq Scan on foo \(Current loop: actual rows=1, loop number=1\)
- Buffers: [^\n]*
- -> Hash \(Current loop: actual rows=0, loop number=1\)
- Buckets: \d+ Batches: \d+ Memory Usage: \d+kB
- -> Seq Scan on bar \(Current loop: actual rows=\d+, loop number=1\)
- Buffers: .*"""
+ -> Seq Scan on foo \(Current loop: actual rows=\d+, loop number=1\)(
+ Buffers: [^\n]*)?
+ -> Hash \(Current loop: actual rows=\d+, loop number=1\)(
+ Buckets: \d+ Batches: \d+ Memory Usage: \d+kB)?
+ -> Seq Scan on bar \(Current loop: actual rows=\d+, loop number=1\)(
+ Buffers: .*)?"""
qs = query_state(config, query, {'buffers': True},
gucs = {'pg_query_state.enable_buffers' : 'on'})
@@ -367,10 +367,10 @@ def test_timing(node):
query = 'select count(*) from foo join bar on foo.c1=bar.c1'
expected = r"""Aggregate \(Current loop: running time=\d+.\d+ actual rows=0, loop number=1\)
- -> Hash Join \(Current loop: running time=\d+.\d+ actual rows=0, loop number=1\)
+ -> Hash Join \(Current loop: running time=\d+.\d+ actual rows=\d+, loop number=1\)
Hash Cond: \(foo.c1 = bar.c1\)
-> Seq Scan on foo \(Current loop: (actual|running) time=\d+.\d+(..\d+.\d+)? (actual )?rows=\d+, loop number=1\)
- -> Hash \(Current loop: running time=\d+.\d+ actual rows=0, loop number=1\)(
+ -> Hash \(Current loop: running time=\d+.\d+ actual rows=\d+, loop number=1\)(
Buckets: \d+ Batches: \d+ Memory Usage: \d+kB)?
-> Seq Scan on bar \(Current loop: (actual|running) time=\d+.\d+(..\d+.\d+)* (actual )*rows=\d+, loop number=1\)"""
@@ -403,12 +403,12 @@ def test_formats(config):
"""test all formats of pg_query_state output"""
query = 'select count(*) from foo join bar on foo.c1=bar.c1'
- expected = r"""Aggregate \(Current loop: actual rows=0, loop number=1\)
- -> Hash Join \(Current loop: actual rows=0, loop number=1\)
+ expected = r"""Aggregate \(Current loop: actual rows=\d+, loop number=1\)
+ -> Hash Join \(Current loop: actual rows=\d+, loop number=1\)
Hash Cond: \(foo.c1 = bar.c1\)
- -> Seq Scan on foo \(Current loop: actual rows=1, loop number=1\)
- -> Hash \(Current loop: actual rows=0, loop number=1\)
- Buckets: \d+ Batches: \d+ Memory Usage: \d+kB
+ -> Seq Scan on foo \(Current loop: actual rows=\d, loop number=1\)
+ -> Hash \(Current loop: actual rows=\d+, loop number=1\)(
+ Buckets: \d+ Batches: \d+ Memory Usage: \d+kB)?
-> Seq Scan on bar \(Current loop: actual rows=\d+, loop number=1\)"""
qs = query_state(config, query, {'format': 'text'})
@@ -489,7 +489,7 @@ def load_tpcds_data(node):
def stress_test(node):
"""stress test"""
load_tpcds_data(node)
-
+ print 'Test running...'
# execute query in separate thread
async_psql = AsyncQueryExecutor(node)
sql = open("tests/query_tpcds.sql",'r').read()
From 320c84878c53f0c4527cd8b1b0f13020cab49571 Mon Sep 17 00:00:00 2001
From: Sergey Cherkashin <4erkashin@list.ru>
Date: Wed, 14 Nov 2018 01:21:51 +0300
Subject: [PATCH 3/5] Improve stress test
---
run_tests.sh | 2 +
tests/query_tpcds.sql | 87 +++++++++++++++++----------------
tests/test_cases.py | 109 +++++++++++++++++++++++++-----------------
3 files changed, 113 insertions(+), 85 deletions(-)
diff --git a/run_tests.sh b/run_tests.sh
index 3a94cea..edfb7f7 100755
--- a/run_tests.sh
+++ b/run_tests.sh
@@ -146,7 +146,9 @@ if [ -f regression.diffs ]; then cat regression.diffs; fi
set +x -e
virtualenv /tmp/env && source /tmp/env/bin/activate
pip install PyYAML
+pip install psycopg2
pip install testgres
+pip install progressbar2
set -e #exit virtualenv with error code
if [ "$LEVEL" = "stress" ]; then
python tests/pg_qs_test_runner.py --stress
diff --git a/tests/query_tpcds.sql b/tests/query_tpcds.sql
index d619abe..70e799e 100644
--- a/tests/query_tpcds.sql
+++ b/tests/query_tpcds.sql
@@ -248,7 +248,7 @@ with ssr as
store
where date_sk = d_date_sk
and d_date between cast('2000-08-19' as date)
- and (cast('2000-08-19' as date) + 14 days)
+ and (cast('2000-08-19' as date) + interval '14 days')
and store_sk = s_store_sk
group by s_store_id)
,
@@ -279,7 +279,7 @@ with ssr as
catalog_page
where date_sk = d_date_sk
and d_date between cast('2000-08-19' as date)
- and (cast('2000-08-19' as date) + 14 days)
+ and (cast('2000-08-19' as date) + interval '14 days')
and page_sk = cp_catalog_page_sk
group by cp_catalog_page_id)
,
@@ -312,7 +312,7 @@ with ssr as
web_site
where date_sk = d_date_sk
and d_date between cast('2000-08-19' as date)
- and (cast('2000-08-19' as date) + 14 days)
+ and (cast('2000-08-19' as date) + interval '14 days')
and wsr_web_site_sk = web_site_sk
group by web_site_id)
select channel
@@ -712,7 +712,7 @@ where
and i_category in ('Men', 'Books', 'Electronics')
and ws_sold_date_sk = d_date_sk
and d_date between cast('2001-06-15' as date)
- and (cast('2001-06-15' as date) + 30 days)
+ and (cast('2001-06-15' as date) + interval '30 days')
group by
i_item_id
,i_item_desc
@@ -812,7 +812,7 @@ with cross_items as
,date_dim d3
where ws_item_sk = iws.i_item_sk
and ws_sold_date_sk = d3.d_date_sk
- and d3.d_year between 1999 AND 1999 + 2)
+ and d3.d_year between 1999 AND 1999 + 2) as sub
where i_brand_id = brand_id
and i_class_id = class_id
and i_category_id = category_id
@@ -838,7 +838,7 @@ with cross_items as
from web_sales
,date_dim
where ws_sold_date_sk = d_date_sk
- and d_year between 1999 and 1999 + 2) x)
+ and d_year between 1999 and 1999 + 2) as x)
select channel, i_brand_id,i_class_id,i_category_id,sum(sales), sum(number_sales)
from(
select 'store' channel, i_brand_id,i_class_id
@@ -882,6 +882,7 @@ with cross_items as
group by rollup (channel, i_brand_id,i_class_id,i_category_id)
order by channel,i_brand_id,i_class_id,i_category_id
limit 100;
+
with cross_items as
(select i_item_sk ss_item_sk
from item,
@@ -913,7 +914,7 @@ with cross_items as
,date_dim d3
where ws_item_sk = iws.i_item_sk
and ws_sold_date_sk = d3.d_date_sk
- and d3.d_year between 1999 AND 1999 + 2) x
+ and d3.d_year between 1999 AND 1999 + 2) as x
where i_brand_id = brand_id
and i_class_id = class_id
and i_category_id = category_id
@@ -939,7 +940,7 @@ with cross_items as
from web_sales
,date_dim
where ws_sold_date_sk = d_date_sk
- and d_year between 1999 and 1999 + 2) x)
+ and d_year between 1999 and 1999 + 2) as x)
select this_year.channel ty_channel
,this_year.i_brand_id ty_brand
,this_year.i_class_id ty_class
@@ -1022,7 +1023,7 @@ from
,call_center
where
d_date between '2002-4-01' and
- (cast('2002-4-01' as date) + 60 days)
+ (cast('2002-4-01' as date) + interval '60 days')
and cs1.cs_ship_date_sk = d_date_sk
and cs1.cs_ship_addr_sk = ca_address_sk
and ca_state = 'PA'
@@ -1161,7 +1162,7 @@ select i_item_id
and i_category in ('Books', 'Music', 'Sports')
and cs_sold_date_sk = d_date_sk
and d_date between cast('2002-06-18' as date)
- and (cast('2002-06-18' as date) + 30 days)
+ and (cast('2002-06-18' as date) + interval '30 days')
group by i_item_id
,i_item_desc
,i_category
@@ -1193,8 +1194,8 @@ select *
and i_item_sk = inv_item_sk
and inv_warehouse_sk = w_warehouse_sk
and inv_date_sk = d_date_sk
- and d_date between (cast ('1999-06-22' as date) - 30 days)
- and (cast ('1999-06-22' as date) + 30 days)
+ and d_date between (cast ('1999-06-22' as date) - interval '30 days')
+ and (cast ('1999-06-22' as date) + interval '30 days')
group by w_warehouse_name, i_item_id) x
where (case when inv_before > 0
then inv_after / inv_before
@@ -1238,14 +1239,15 @@ with frequent_ss_items as
having count(*) >4),
max_store_sales as
(select max(csales) tpcds_cmax
- from (select c_customer_sk,sum(ss_quantity*ss_sales_price) csales
+ from (select c_customer_sk,sum(ss_quantity*ss_sales_price) as csales
from store_sales
,customer
,date_dim
where ss_customer_sk = c_customer_sk
and ss_sold_date_sk = d_date_sk
and d_year in (2000,2000+1,2000+2,2000+3)
- group by c_customer_sk)),
+ group by c_customer_sk) as scsales
+ ),
best_ss_customer as
(select c_customer_sk,sum(ss_quantity*ss_sales_price) ssales
from store_sales
@@ -1273,8 +1275,9 @@ from
and d_moy = 7
and ws_sold_date_sk = d_date_sk
and ws_item_sk in (select item_sk from frequent_ss_items)
- and ws_bill_customer_sk in (select c_customer_sk from best_ss_customer))
+ and ws_bill_customer_sk in (select c_customer_sk from best_ss_customer)) as foo
limit 100;
+
with frequent_ss_items as
(select substr(i_item_desc,1,30) itemdesc,i_item_sk item_sk,d_date solddate,count(*) cnt
from store_sales
@@ -1294,7 +1297,7 @@ with frequent_ss_items as
where ss_customer_sk = c_customer_sk
and ss_sold_date_sk = d_date_sk
and d_year in (2000,2000+1,2000+2,2000+3)
- group by c_customer_sk)),
+ group by c_customer_sk) as scsales),
best_ss_customer as
(select c_customer_sk,sum(ss_quantity*ss_sales_price) ssales
from store_sales
@@ -1327,7 +1330,7 @@ with frequent_ss_items as
and ws_item_sk in (select item_sk from frequent_ss_items)
and ws_bill_customer_sk in (select c_customer_sk from best_ss_customer)
and ws_bill_customer_sk = c_customer_sk
- group by c_last_name,c_first_name)
+ group by c_last_name,c_first_name) as sub
order by c_last_name,c_first_name,sales
limit 100;
@@ -1724,7 +1727,7 @@ where
i_manufact_id = 722
and i_item_sk = cs_item_sk
and d_date between '2001-03-09' and
- (cast('2001-03-09' as date) + 90 days)
+ (cast('2001-03-09' as date) + interval '90 days')
and d_date_sk = cs_sold_date_sk
and cs_ext_discount_amt
> (
@@ -1736,7 +1739,7 @@ and cs_ext_discount_amt
where
cs_item_sk = i_item_sk
and d_date between '2001-03-09' and
- (cast('2001-03-09' as date) + 90 days)
+ (cast('2001-03-09' as date) + interval '90 days')
and d_date_sk = cs_sold_date_sk
)
limit 100;
@@ -1944,7 +1947,7 @@ select i_item_id
where i_current_price between 29 and 29 + 30
and inv_item_sk = i_item_sk
and d_date_sk=inv_date_sk
- and d_date between cast('2002-03-29' as date) and (cast('2002-03-29' as date) + 60 days)
+ and d_date between cast('2002-03-29' as date) and (cast('2002-03-29' as date) + interval '60 days')
and i_manufact_id in (705,742,777,944)
and inv_quantity_on_hand between 100 and 500
and cs_item_sk = i_item_sk
@@ -2050,8 +2053,8 @@ select
and i_item_sk = cs_item_sk
and cs_warehouse_sk = w_warehouse_sk
and cs_sold_date_sk = d_date_sk
- and d_date between (cast ('2001-05-02' as date) - 30 days)
- and (cast ('2001-05-02' as date) + 30 days)
+ and d_date between (cast ('2001-05-02' as date) - interval '30 days')
+ and (cast ('2001-05-02' as date) + interval '30 days')
group by
w_state,i_item_id
order by w_state,i_item_id
@@ -2395,7 +2398,7 @@ select channel, item, return_ratio, return_rank, currency_rank from
and d_moy = 11
group by ws.ws_item_sk
) in_web
- ) web
+ ) as web
where
(
web.return_rank <= 10
@@ -2438,7 +2441,7 @@ select channel, item, return_ratio, return_rank, currency_rank from
and d_moy = 11
group by cs.cs_item_sk
) in_cat
- ) catalog
+ ) as catalog
where
(
catalog.return_rank <= 10
@@ -2477,13 +2480,13 @@ select channel, item, return_ratio, return_rank, currency_rank from
and d_moy = 11
group by sts.ss_item_sk
) in_store
- ) store
+ ) as store
where (
store.return_rank <= 10
or
store.currency_rank <= 10
)
- )
+ )as tab
order by 1,4,5,2
limit 100;
@@ -3927,7 +3930,7 @@ with ss as
store
where ss_sold_date_sk = d_date_sk
and d_date between cast('2000-08-10' as date)
- and (cast('2000-08-10' as date) + 30 days)
+ and (cast('2000-08-10' as date) + interval '30 days')
and ss_store_sk = s_store_sk
group by s_store_sk)
,
@@ -3940,7 +3943,7 @@ with ss as
store
where sr_returned_date_sk = d_date_sk
and d_date between cast('2000-08-10' as date)
- and (cast('2000-08-10' as date) + 30 days)
+ and (cast('2000-08-10' as date) + interval '30 days')
and sr_store_sk = s_store_sk
group by s_store_sk),
cs as
@@ -3951,7 +3954,7 @@ with ss as
date_dim
where cs_sold_date_sk = d_date_sk
and d_date between cast('2000-08-10' as date)
- and (cast('2000-08-10' as date) + 30 days)
+ and (cast('2000-08-10' as date) + interval '30 days')
group by cs_call_center_sk
),
cr as
@@ -3962,7 +3965,7 @@ with ss as
date_dim
where cr_returned_date_sk = d_date_sk
and d_date between cast('2000-08-10' as date)
- and (cast('2000-08-10' as date) + 30 days)
+ and (cast('2000-08-10' as date) + interval '30 days')
group by cr_call_center_sk
),
ws as
@@ -3974,7 +3977,7 @@ with ss as
web_page
where ws_sold_date_sk = d_date_sk
and d_date between cast('2000-08-10' as date)
- and (cast('2000-08-10' as date) + 30 days)
+ and (cast('2000-08-10' as date) + interval '30 days')
and ws_web_page_sk = wp_web_page_sk
group by wp_web_page_sk),
wr as
@@ -3986,7 +3989,7 @@ with ss as
web_page
where wr_returned_date_sk = d_date_sk
and d_date between cast('2000-08-10' as date)
- and (cast('2000-08-10' as date) + 30 days)
+ and (cast('2000-08-10' as date) + interval '30 days')
and wr_web_page_sk = wp_web_page_sk
group by wp_web_page_sk)
select channel
@@ -4014,7 +4017,7 @@ with ss as
select 'web channel' as channel
, ws.wp_web_page_sk as id
, sales
- , coalesce(returns, 0) returns
+ , coalesce(returns, 0) as returns
, (profit - coalesce(profit_loss,0)) as profit
from ws left join wr
on ws.wp_web_page_sk = wr.wp_web_page_sk
@@ -4120,7 +4123,7 @@ with ssr as
promotion
where ss_sold_date_sk = d_date_sk
and d_date between cast('2002-08-14' as date)
- and (cast('2002-08-14' as date) + 30 days)
+ and (cast('2002-08-14' as date) + interval '30 days')
and ss_store_sk = s_store_sk
and ss_item_sk = i_item_sk
and i_current_price > 50
@@ -4141,7 +4144,7 @@ with ssr as
promotion
where cs_sold_date_sk = d_date_sk
and d_date between cast('2002-08-14' as date)
- and (cast('2002-08-14' as date) + 30 days)
+ and (cast('2002-08-14' as date) + interval '30 days')
and cs_catalog_page_sk = cp_catalog_page_sk
and cs_item_sk = i_item_sk
and i_current_price > 50
@@ -4162,7 +4165,7 @@ group by cp_catalog_page_id)
promotion
where ws_sold_date_sk = d_date_sk
and d_date between cast('2002-08-14' as date)
- and (cast('2002-08-14' as date) + 30 days)
+ and (cast('2002-08-14' as date) + interval '30 days')
and ws_web_site_sk = web_site_sk
and ws_item_sk = i_item_sk
and i_current_price > 50
@@ -4241,7 +4244,7 @@ select i_item_id
where i_current_price between 58 and 58+30
and inv_item_sk = i_item_sk
and d_date_sk=inv_date_sk
- and d_date between cast('2001-01-13' as date) and (cast('2001-01-13' as date) + 60 days)
+ and d_date between cast('2001-01-13' as date) and (cast('2001-01-13' as date) + interval '60 days')
and i_manufact_id in (259,559,580,485)
and inv_quantity_on_hand between 100 and 500
and ss_item_sk = i_item_sk
@@ -4657,7 +4660,7 @@ where
i_manufact_id = 714
and i_item_sk = ws_item_sk
and d_date between '2000-02-01' and
- (cast('2000-02-01' as date) + 90 days)
+ (cast('2000-02-01' as date) + interval '90 days')
and d_date_sk = ws_sold_date_sk
and ws_ext_discount_amt
> (
@@ -4669,7 +4672,7 @@ and ws_ext_discount_amt
WHERE
ws_item_sk = i_item_sk
and d_date between '2000-02-01' and
- (cast('2000-02-01' as date) + 90 days)
+ (cast('2000-02-01' as date) + interval '90 days')
and d_date_sk = ws_sold_date_sk
)
order by sum(ws_ext_discount_amt)
@@ -4706,7 +4709,7 @@ from
,web_site
where
d_date between '2002-5-01' and
- (cast('2002-5-01' as date) + 60 days)
+ (cast('2002-5-01' as date) + interval '60 days')
and ws1.ws_ship_date_sk = d_date_sk
and ws1.ws_ship_addr_sk = ca_address_sk
and ca_state = 'OK'
@@ -4740,7 +4743,7 @@ from
,web_site
where
d_date between '2001-4-01' and
- (cast('2001-4-01' as date) + 60 days)
+ (cast('2001-4-01' as date) + interval '60 days')
and ws1.ws_ship_date_sk = d_date_sk
and ws1.ws_ship_addr_sk = ca_address_sk
and ca_state = 'VA'
@@ -4814,7 +4817,7 @@ where
and i_category in ('Men', 'Sports', 'Jewelry')
and ss_sold_date_sk = d_date_sk
and d_date between cast('1999-02-05' as date)
- and (cast('1999-02-05' as date) + 30 days)
+ and (cast('1999-02-05' as date) + interval '60 days')
group by
i_item_id
,i_item_desc
diff --git a/tests/test_cases.py b/tests/test_cases.py
index d111fa6..a6ebba8 100644
--- a/tests/test_cases.py
+++ b/tests/test_cases.py
@@ -1,4 +1,5 @@
import testgres
+import psycopg2.extensions
import json
import re
import time
@@ -8,6 +9,9 @@
from multiprocessing import Process, Queue, Condition
import subprocess
import os
+import progressbar
+
+class SQLExecuteException(Exception): pass
class AsyncQueryExecutor():
""" Run query in separate process """
@@ -21,36 +25,45 @@ def __init__(self, node):
self.condition = Condition()
self.result = []
- def run_internal(self, conn, query, multiple, res_q, condition):
+ def run_internal(self, conn, query, res_q, condition):
condition.acquire()
- commands = []
- if multiple:
- commands = query.split(';')
- for i, cmd in enumerate(query.split(';')):
- if (len(cmd.strip()) == 0):
- del commands[i]
- else:
- commands.append(query)
-
conn.begin()
condition.notify()
condition.release()
- for cmd in commands:
- try:
- res = conn.execute(cmd)
- res_q.put(res)
- conn.commit()
- except Exception, e:
- print 'Unable to execute query: "', cmd ,'"'
- print 'Reason: %s' %e
- conn.rollback()
- continue
+ try:
+ res = conn.execute(query)
+ res_q.put(res)
+ conn.commit()
+ except Exception, e:
+ conn.rollback()
+ print 'Unable to execute query: "', query ,'"'
+ raise SQLExecuteException(
+ 'Unable to execute query: "%s"\nReason: %s' %(query, e))
return
+ def run_stress(self, conn, query, condition):
+ condition.acquire()
+ condition.notify()
+ condition.release()
+ i = 1
+ try:
+ conn.begin()
+ conn.execute(query)
+ conn.commit()
+ except psycopg2.extensions.QueryCanceledError:
+ pass
+ except Exception, e:
+ print "Unable to execute: %s" %query
+ print "Reason: %s" %e
+
def run(self, query, multiple = False):
"""Run async query"""
- self.process = Process(target=self.run_internal,
- args=(self.conn, query, multiple, self.res_q, self.condition))
+ if multiple:
+ self.process = Process(target=self.run_stress,
+ args=(self.conn, query, self.condition))
+ else:
+ self.process = Process(target=self.run_internal,
+ args=(self.conn, query, self.res_q, self.condition))
self.process.start()
self.condition.acquire()
self.condition.wait(5)
@@ -61,13 +74,15 @@ def wait(self):
self.process.join()
def terminate(self):
- if self.process.is_alive():
+ if self.node.pid:
self.node.psql("SELECT pg_cancel_backend(%d)" % self.backend_pid)
+ if self.process.is_alive():
self.process.terminate()
def close(self):
self.terminate()
- self.conn.close()
+ if self.node.pid:
+ self.conn.close()
def pqs_args(pid, verbose=False, costs=False, timing=False,
buffers=False, triggers=False, format='text'):
@@ -469,8 +484,6 @@ class StressTestException(Exception): pass
def load_tpcds_data(node):
print 'Load tpcds...'
subprocess.call(['./tests/prepare_stress.sh'])
- tables = open('tmp_stress/tpcds-kit/tools/tpcds.sql', 'r')
- tables_sql = tables.read()
try:
# Create tables
node.psql(filename="tmp_stress/tpcds-kit/tools/tpcds.sql")
@@ -491,21 +504,31 @@ def stress_test(node):
load_tpcds_data(node)
print 'Test running...'
# execute query in separate thread
- async_psql = AsyncQueryExecutor(node)
- sql = open("tests/query_tpcds.sql",'r').read()
- aq = AsyncQueryExecutor(node)
- aq.run(sql, True)
-
- conn = testgres.connection.NodeConnection(node)
- while aq.process.is_alive():
+ with open("tests/query_tpcds.sql",'r') as f:
+ sql = f.read()
+ commands = sql.split(';')
+ for i, cmd in enumerate(sql.split(';')):
+ if (len(cmd.strip()) == 0):
+ del commands[i]
+
+ timeout_list = []
+ bar = progressbar.ProgressBar(max_value=len(commands))
+ for i, cmd in enumerate(commands):
+ bar.update(i+1)
try:
- conn.execute('SELECT * FROM pg_query_state(%d)' % aq.backend_pid)
- except Exception, e:
- async_psql_ex = AsyncQueryExecutor(node)
- async_psql_ex.run('SELECT state, query FROM pg_stat_activity where pid = %d;' % aq.backend_pid)
- async_psql_ex.wait()
- print 'pg_query_state FAILED'
- print 'state of backend:'
- print async_psql_ex.result
- raise StressTestException('Unable to get query state: %s' % e)
- aq.close()
+ conn = testgres.connection.NodeConnection(node)
+ aq = AsyncQueryExecutor(node)
+ # set query timeout to 10 sec
+ set_guc(aq.conn, 'statement_timeout', 10000)
+ set_guc(conn, 'statement_timeout', 10000)
+ aq.run(cmd, True)
+ while aq.process.is_alive() and node.pid:
+ conn.execute('SELECT * FROM pg_query_state(%d)' % aq.backend_pid)
+ #TODO: Put here testgres exception when supported
+ except psycopg2.extensions.QueryCanceledError:
+ timeout_list.append(i)
+ finally:
+ aq.close()
+ conn.close()
+ if len(timeout_list) > 0:
+ print 'It was pg_query_state timeouts(10s) on queries: ', timeout_list
From fa6ce2d8604e43beaad06f230763e15c209c7c14 Mon Sep 17 00:00:00 2001
From: Sergey Cherkashin <4erkashin@list.ru>
Date: Wed, 14 Nov 2018 19:29:24 +0300
Subject: [PATCH 4/5] Fix sql queries in stress test
---
tests/query_tpcds.sql | 876 +++++++++++++++++++++---------------------
tests/test_cases.py | 7 +-
2 files changed, 443 insertions(+), 440 deletions(-)
diff --git a/tests/query_tpcds.sql b/tests/query_tpcds.sql
index 70e799e..e82fca1 100644
--- a/tests/query_tpcds.sql
+++ b/tests/query_tpcds.sql
@@ -29,12 +29,12 @@ with wscs as
,sales_price
from (select ws_sold_date_sk sold_date_sk
,ws_ext_sales_price sales_price
- from web_sales
+ from web_sales
union all
select cs_sold_date_sk sold_date_sk
,cs_ext_sales_price sales_price
from catalog_sales) as sdsp),
- wswscs as
+ wswscs as
(select d_week_seq,
sum(case when (d_day_name='Sunday') then sales_price else null end) sun_sales,
sum(case when (d_day_name='Monday') then sales_price else null end) mon_sales,
@@ -64,7 +64,7 @@ with wscs as
,thu_sales thu_sales1
,fri_sales fri_sales1
,sat_sales sat_sales1
- from wswscs,date_dim
+ from wswscs,date_dim
where date_dim.d_week_seq = wswscs.d_week_seq and
d_year = 1998) y,
(select wswscs.d_week_seq d_week_seq2
@@ -76,7 +76,7 @@ with wscs as
,fri_sales fri_sales2
,sat_sales sat_sales2
from wswscs
- ,date_dim
+ ,date_dim
where date_dim.d_week_seq = wswscs.d_week_seq and
d_year = 1998+1) z
where d_week_seq1=d_week_seq2-53
@@ -84,11 +84,11 @@ with wscs as
-- end query 2 in stream 0 using template query2.tpl
-- start query 3 in stream 0 using template query3.tpl
-select dt.d_year
- ,item.i_brand_id brand_id
+select dt.d_year
+ ,item.i_brand_id brand_id
,item.i_brand brand
,sum(ss_sales_price) sum_agg
- from date_dim dt
+ from date_dim dt
,store_sales
,item
where dt.d_date_sk = store_sales.ss_sold_date_sk
@@ -178,7 +178,7 @@ union all
,c_email_address
,d_year
)
- select
+ select
t_s_secyear.customer_id
,t_s_secyear.customer_first_name
,t_s_secyear.customer_last_name
@@ -247,7 +247,7 @@ with ssr as
date_dim,
store
where date_sk = d_date_sk
- and d_date between cast('2000-08-19' as date)
+ and d_date between cast('2000-08-19' as date)
and (cast('2000-08-19' as date) + interval '14 days')
and store_sk = s_store_sk
group by s_store_id)
@@ -320,7 +320,7 @@ with ssr as
, sum(sales) as sales
, sum(returns) as returns
, sum(profit) as profit
- from
+ from
(select 'store channel' as channel
, 'store' || s_store_id as id
, sales
@@ -359,37 +359,37 @@ select a.ca_state state, count(*) cnt
and c.c_customer_sk = s.ss_customer_sk
and s.ss_sold_date_sk = d.d_date_sk
and s.ss_item_sk = i.i_item_sk
- and d.d_month_seq =
+ and d.d_month_seq =
(select distinct (d_month_seq)
from date_dim
where d_year = 2002
and d_moy = 3 )
- and i.i_current_price > 1.2 *
- (select avg(j.i_current_price)
- from item j
+ and i.i_current_price > 1.2 *
+ (select avg(j.i_current_price)
+ from item j
where j.i_category = i.i_category)
group by a.ca_state
having count(*) >= 10
- order by cnt, a.ca_state
+ order by cnt, a.ca_state
limit 100;
-- end query 6 in stream 0 using template query6.tpl
-- start query 7 in stream 0 using template query7.tpl
-select i_item_id,
+select i_item_id,
avg(ss_quantity) agg1,
avg(ss_list_price) agg2,
avg(ss_coupon_amt) agg3,
- avg(ss_sales_price) agg4
+ avg(ss_sales_price) agg4
from store_sales, customer_demographics, date_dim, item, promotion
where ss_sold_date_sk = d_date_sk and
ss_item_sk = i_item_sk and
ss_cdemo_sk = cd_demo_sk and
ss_promo_sk = p_promo_sk and
- cd_gender = 'F' and
+ cd_gender = 'F' and
cd_marital_status = 'W' and
cd_education_status = 'College' and
(p_channel_email = 'N' or p_channel_event = 'N') and
- d_year = 2001
+ d_year = 2001
group by i_item_id
order by i_item_id
limit 100;
@@ -504,12 +504,12 @@ select s_store_name
-- end query 8 in stream 0 using template query8.tpl
-- start query 9 in stream 0 using template query9.tpl
-select case when (select count(*)
- from store_sales
+select case when (select count(*)
+ from store_sales
where ss_quantity between 1 and 20) > 1071
- then (select avg(ss_ext_tax)
- from store_sales
- where ss_quantity between 1 and 20)
+ then (select avg(ss_ext_tax)
+ from store_sales
+ where ss_quantity between 1 and 20)
else (select avg(ss_net_paid_inc_tax)
from store_sales
where ss_quantity between 1 and 20) end bucket1 ,
@@ -518,7 +518,7 @@ select case when (select count(*)
where ss_quantity between 21 and 40) > 39161
then (select avg(ss_ext_tax)
from store_sales
- where ss_quantity between 21 and 40)
+ where ss_quantity between 21 and 40)
else (select avg(ss_net_paid_inc_tax)
from store_sales
where ss_quantity between 21 and 40) end bucket2,
@@ -555,7 +555,7 @@ where r_reason_sk = 1
-- end query 9 in stream 0 using template query9.tpl
-- start query 10 in stream 0 using template query10.tpl
-select
+select
cd_gender,
cd_marital_status,
cd_education_status,
@@ -575,7 +575,7 @@ select
where
c.c_current_addr_sk = ca.ca_address_sk and
ca_county in ('Fairfield County','Campbell County','Washtenaw County','Escambia County','Cleburne County') and
- cd_demo_sk = c.c_current_cdemo_sk and
+ cd_demo_sk = c.c_current_cdemo_sk and
exists (select *
from store_sales,date_dim
where c.c_customer_sk = ss_customer_sk and
@@ -587,8 +587,8 @@ select
where c.c_customer_sk = ws_bill_customer_sk and
ws_sold_date_sk = d_date_sk and
d_year = 2001 and
- d_moy between 3 ANd 3+3) or
- exists (select *
+ d_moy between 3 ANd 3+3) or
+ exists (select *
from catalog_sales,date_dim
where c.c_customer_sk = cs_ship_customer_sk and
cs_sold_date_sk = d_date_sk and
@@ -633,11 +633,11 @@ with year_total as (
group by c_customer_id
,c_first_name
,c_last_name
- ,c_preferred_cust_flag
+ ,c_preferred_cust_flag
,c_birth_country
,c_login
,c_email_address
- ,d_year
+ ,d_year
union all
select c_customer_id customer_id
,c_first_name customer_first_name
@@ -657,13 +657,13 @@ with year_total as (
group by c_customer_id
,c_first_name
,c_last_name
- ,c_preferred_cust_flag
+ ,c_preferred_cust_flag
,c_birth_country
,c_login
,c_email_address
,d_year
)
- select
+ select
t_s_secyear.customer_id
,t_s_secyear.customer_first_name
,t_s_secyear.customer_last_name
@@ -696,30 +696,30 @@ limit 100;
-- end query 11 in stream 0 using template query11.tpl
-- start query 12 in stream 0 using template query12.tpl
select i_item_id
- ,i_item_desc
- ,i_category
- ,i_class
+ ,i_item_desc
+ ,i_category
+ ,i_class
,i_current_price
- ,sum(ws_ext_sales_price) as itemrevenue
+ ,sum(ws_ext_sales_price) as itemrevenue
,sum(ws_ext_sales_price)*100/sum(sum(ws_ext_sales_price)) over
(partition by i_class) as revenueratio
-from
+from
web_sales
- ,item
+ ,item
,date_dim
-where
- ws_item_sk = i_item_sk
+where
+ ws_item_sk = i_item_sk
and i_category in ('Men', 'Books', 'Electronics')
and ws_sold_date_sk = d_date_sk
- and d_date between cast('2001-06-15' as date)
+ and d_date between cast('2001-06-15' as date)
and (cast('2001-06-15' as date) + interval '30 days')
-group by
+group by
i_item_id
- ,i_item_desc
+ ,i_item_desc
,i_category
,i_class
,i_current_price
-order by
+order by
i_category
,i_class
,i_item_id
@@ -746,36 +746,36 @@ select avg(ss_quantity)
and cd_marital_status = 'M'
and cd_education_status = 'College'
and ss_sales_price between 100.00 and 150.00
- and hd_dep_count = 3
+ and hd_dep_count = 3
)or
(ss_hdemo_sk=hd_demo_sk
and cd_demo_sk = ss_cdemo_sk
and cd_marital_status = 'D'
and cd_education_status = 'Primary'
- and ss_sales_price between 50.00 and 100.00
+ and ss_sales_price between 50.00 and 100.00
and hd_dep_count = 1
- ) or
+ ) or
(ss_hdemo_sk=hd_demo_sk
and cd_demo_sk = ss_cdemo_sk
and cd_marital_status = 'W'
and cd_education_status = '2 yr Degree'
- and ss_sales_price between 150.00 and 200.00
- and hd_dep_count = 1
+ and ss_sales_price between 150.00 and 200.00
+ and hd_dep_count = 1
))
and((ss_addr_sk = ca_address_sk
and ca_country = 'United States'
and ca_state in ('IL', 'TN', 'TX')
- and ss_net_profit between 100 and 200
+ and ss_net_profit between 100 and 200
) or
(ss_addr_sk = ca_address_sk
and ca_country = 'United States'
and ca_state in ('WY', 'OH', 'ID')
- and ss_net_profit between 150 and 300
+ and ss_net_profit between 150 and 300
) or
(ss_addr_sk = ca_address_sk
and ca_country = 'United States'
and ca_state in ('MS', 'SC', 'IA')
- and ss_net_profit between 50 and 250
+ and ss_net_profit between 50 and 250
))
;
@@ -793,7 +793,7 @@ with cross_items as
where ss_item_sk = iss.i_item_sk
and ss_sold_date_sk = d1.d_date_sk
and d1.d_year between 1999 AND 1999 + 2
- intersect
+ intersect
select ics.i_brand_id
,ics.i_class_id
,ics.i_category_id
@@ -825,13 +825,13 @@ with cross_items as
,date_dim
where ss_sold_date_sk = d_date_sk
and d_year between 1999 and 1999 + 2
- union all
- select cs_quantity quantity
+ union all
+ select cs_quantity quantity
,cs_list_price list_price
from catalog_sales
,date_dim
where cs_sold_date_sk = d_date_sk
- and d_year between 1999 and 1999 + 2
+ and d_year between 1999 and 1999 + 2
union all
select ws_quantity quantity
,ws_list_price list_price
@@ -850,7 +850,7 @@ with cross_items as
where ss_item_sk in (select ss_item_sk from cross_items)
and ss_item_sk = i_item_sk
and ss_sold_date_sk = d_date_sk
- and d_year = 1999+2
+ and d_year = 1999+2
and d_moy = 11
group by i_brand_id,i_class_id,i_category_id
having sum(ss_quantity*ss_list_price) > (select average_sales from avg_sales)
@@ -862,7 +862,7 @@ with cross_items as
where cs_item_sk in (select ss_item_sk from cross_items)
and cs_item_sk = i_item_sk
and cs_sold_date_sk = d_date_sk
- and d_year = 1999+2
+ and d_year = 1999+2
and d_moy = 11
group by i_brand_id,i_class_id,i_category_id
having sum(cs_quantity*cs_list_price) > (select average_sales from avg_sales)
@@ -952,11 +952,11 @@ with cross_items as
,last_year.i_class_id ly_class
,last_year.i_category_id ly_category
,last_year.sales ly_sales
- ,last_year.number_sales ly_number_sales
+ ,last_year.number_sales ly_number_sales
from
(select 'store' channel, i_brand_id,i_class_id,i_category_id
,sum(ss_quantity*ss_list_price) sales, count(*) number_sales
- from store_sales
+ from store_sales
,item
,date_dim
where ss_item_sk in (select ss_item_sk from cross_items)
@@ -999,7 +999,7 @@ select ca_zip
,customer_address
,date_dim
where cs_bill_customer_sk = c_customer_sk
- and c_current_addr_sk = ca_address_sk
+ and c_current_addr_sk = ca_address_sk
and ( substr(ca_zip,1,5) in ('85669', '86197','88274','83405','86475',
'85392', '85460', '80348', '81792')
or ca_state in ('CA','WA','GA')
@@ -1012,7 +1012,7 @@ select ca_zip
-- end query 15 in stream 0 using template query15.tpl
-- start query 16 in stream 0 using template query16.tpl
-select
+select
count(distinct cs_order_number) as "order count"
,sum(cs_ext_ship_cost) as "total shipping cost"
,sum(cs_net_profit) as "total net profit"
@@ -1022,7 +1022,7 @@ from
,customer_address
,call_center
where
- d_date between '2002-4-01' and
+ d_date between '2002-4-01' and
(cast('2002-4-01' as date) + interval '60 days')
and cs1.cs_ship_date_sk = d_date_sk
and cs1.cs_ship_addr_sk = ca_address_sk
@@ -1090,7 +1090,7 @@ limit 100;
-- start query 18 in stream 0 using template query18.tpl
select i_item_id,
ca_country,
- ca_state,
+ ca_state,
ca_county,
avg( cast(cs_quantity as decimal(12,2))) agg1,
avg( cast(cs_list_price as decimal(12,2))) agg2,
@@ -1099,13 +1099,13 @@ select i_item_id,
avg( cast(cs_net_profit as decimal(12,2))) agg5,
avg( cast(c_birth_year as decimal(12,2))) agg6,
avg( cast(cd1.cd_dep_count as decimal(12,2))) agg7
- from catalog_sales, customer_demographics cd1,
+ from catalog_sales, customer_demographics cd1,
customer_demographics cd2, customer, customer_address, date_dim, item
where cs_sold_date_sk = d_date_sk and
cs_item_sk = i_item_sk and
cs_bill_cdemo_sk = cd1.cd_demo_sk and
cs_bill_customer_sk = c_customer_sk and
- cd1.cd_gender = 'F' and
+ cd1.cd_gender = 'F' and
cd1.cd_education_status = 'Primary' and
c_current_cdemo_sk = cd2.cd_demo_sk and
c_current_addr_sk = ca_address_sk and
@@ -1115,7 +1115,7 @@ select i_item_id,
,'GA','MT','IN','CA')
group by rollup (i_item_id, ca_country, ca_state, ca_county)
order by ca_country,
- ca_state,
+ ca_state,
ca_county,
i_item_id
limit 100;
@@ -1130,10 +1130,10 @@ select i_brand_id brand_id, i_brand brand, i_manufact_id, i_manufact,
and i_manager_id=14
and d_moy=11
and d_year=2002
- and ss_customer_sk = c_customer_sk
+ and ss_customer_sk = c_customer_sk
and c_current_addr_sk = ca_address_sk
- and substr(ca_zip,1,5) <> substr(s_zip,1,5)
- and ss_store_sk = s_store_sk
+ and substr(ca_zip,1,5) <> substr(s_zip,1,5)
+ and ss_store_sk = s_store_sk
group by i_brand
,i_brand_id
,i_manufact_id
@@ -1148,23 +1148,23 @@ limit 100 ;
-- end query 19 in stream 0 using template query19.tpl
-- start query 20 in stream 0 using template query20.tpl
select i_item_id
- ,i_item_desc
- ,i_category
- ,i_class
+ ,i_item_desc
+ ,i_category
+ ,i_class
,i_current_price
- ,sum(cs_ext_sales_price) as itemrevenue
+ ,sum(cs_ext_sales_price) as itemrevenue
,sum(cs_ext_sales_price)*100/sum(sum(cs_ext_sales_price)) over
(partition by i_class) as revenueratio
from catalog_sales
- ,item
+ ,item
,date_dim
- where cs_item_sk = i_item_sk
+ where cs_item_sk = i_item_sk
and i_category in ('Books', 'Music', 'Sports')
and cs_sold_date_sk = d_date_sk
- and d_date between cast('2002-06-18' as date)
+ and d_date between cast('2002-06-18' as date)
and (cast('2002-06-18' as date) + interval '30 days')
group by i_item_id
- ,i_item_desc
+ ,i_item_desc
,i_category
,i_class
,i_current_price
@@ -1181,10 +1181,10 @@ select *
from(select w_warehouse_name
,i_item_id
,sum(case when (cast(d_date as date) < cast ('1999-06-22' as date))
- then inv_quantity_on_hand
+ then inv_quantity_on_hand
else 0 end) as inv_before
,sum(case when (cast(d_date as date) >= cast ('1999-06-22' as date))
- then inv_quantity_on_hand
+ then inv_quantity_on_hand
else 0 end) as inv_after
from inventory
,warehouse
@@ -1197,8 +1197,8 @@ select *
and d_date between (cast ('1999-06-22' as date) - interval '30 days')
and (cast ('1999-06-22' as date) + interval '30 days')
group by w_warehouse_name, i_item_id) x
- where (case when inv_before > 0
- then inv_after / inv_before
+ where (case when inv_before > 0
+ then inv_after / inv_before
else null
end) between 2.0/3.0 and 3.0/2.0
order by w_warehouse_name
@@ -1227,25 +1227,25 @@ limit 100;
-- end query 22 in stream 0 using template query22.tpl
-- start query 23 in stream 0 using template query23.tpl
-with frequent_ss_items as
+with frequent_ss_items as
(select substr(i_item_desc,1,30) itemdesc,i_item_sk item_sk,d_date solddate,count(*) cnt
from store_sales
- ,date_dim
+ ,date_dim
,item
where ss_sold_date_sk = d_date_sk
- and ss_item_sk = i_item_sk
+ and ss_item_sk = i_item_sk
and d_year in (2000,2000+1,2000+2,2000+3)
group by substr(i_item_desc,1,30),i_item_sk,d_date
having count(*) >4),
max_store_sales as
- (select max(csales) tpcds_cmax
+ (select max(csales) tpcds_cmax
from (select c_customer_sk,sum(ss_quantity*ss_sales_price) as csales
from store_sales
,customer
- ,date_dim
+ ,date_dim
where ss_customer_sk = c_customer_sk
and ss_sold_date_sk = d_date_sk
- and d_year in (2000,2000+1,2000+2,2000+3)
+ and d_year in (2000,2000+1,2000+2,2000+3)
group by c_customer_sk) as scsales
),
best_ss_customer as
@@ -1261,21 +1261,21 @@ from
select sum(sales)
from (select cs_quantity*cs_list_price sales
from catalog_sales
- ,date_dim
- where d_year = 2000
- and d_moy = 7
- and cs_sold_date_sk = d_date_sk
+ ,date_dim
+ where d_year = 2000
+ and d_moy = 7
+ and cs_sold_date_sk = d_date_sk
and cs_item_sk in (select item_sk from frequent_ss_items)
and cs_bill_customer_sk in (select c_customer_sk from best_ss_customer)
union all
select ws_quantity*ws_list_price sales
- from web_sales
- ,date_dim
- where d_year = 2000
- and d_moy = 7
- and ws_sold_date_sk = d_date_sk
+ from web_sales
+ ,date_dim
+ where d_year = 2000
+ and d_moy = 7
+ and ws_sold_date_sk = d_date_sk
and ws_item_sk in (select item_sk from frequent_ss_items)
- and ws_bill_customer_sk in (select c_customer_sk from best_ss_customer)) as foo
+ and ws_bill_customer_sk in (select c_customer_sk from best_ss_customer)) as foo
limit 100;
with frequent_ss_items as
@@ -1293,7 +1293,7 @@ with frequent_ss_items as
from (select c_customer_sk,sum(ss_quantity*ss_sales_price) csales
from store_sales
,customer
- ,date_dim
+ ,date_dim
where ss_customer_sk = c_customer_sk
and ss_sold_date_sk = d_date_sk
and d_year in (2000,2000+1,2000+2,2000+3)
@@ -1311,26 +1311,26 @@ with frequent_ss_items as
from (select c_last_name,c_first_name,sum(cs_quantity*cs_list_price) sales
from catalog_sales
,customer
- ,date_dim
- where d_year = 2000
- and d_moy = 7
- and cs_sold_date_sk = d_date_sk
+ ,date_dim
+ where d_year = 2000
+ and d_moy = 7
+ and cs_sold_date_sk = d_date_sk
and cs_item_sk in (select item_sk from frequent_ss_items)
and cs_bill_customer_sk in (select c_customer_sk from best_ss_customer)
- and cs_bill_customer_sk = c_customer_sk
+ and cs_bill_customer_sk = c_customer_sk
group by c_last_name,c_first_name
union all
select c_last_name,c_first_name,sum(ws_quantity*ws_list_price) sales
from web_sales
,customer
- ,date_dim
- where d_year = 2000
- and d_moy = 7
- and ws_sold_date_sk = d_date_sk
+ ,date_dim
+ where d_year = 2000
+ and d_moy = 7
+ and ws_sold_date_sk = d_date_sk
and ws_item_sk in (select item_sk from frequent_ss_items)
and ws_bill_customer_sk in (select c_customer_sk from best_ss_customer)
and ws_bill_customer_sk = c_customer_sk
- group by c_last_name,c_first_name) as sub
+ group by c_last_name,c_first_name) as sub
order by c_last_name,c_first_name,sales
limit 100;
@@ -1443,7 +1443,7 @@ order by c_last_name
-- end query 24 in stream 0 using template query24.tpl
-- start query 25 in stream 0 using template query25.tpl
-select
+select
i_item_id
,i_item_desc
,s_store_id
@@ -1475,7 +1475,7 @@ select
and sr_customer_sk = cs_bill_customer_sk
and sr_item_sk = cs_item_sk
and cs_sold_date_sk = d3.d_date_sk
- and d3.d_moy between 4 and 10
+ and d3.d_moy between 4 and 10
and d3.d_year = 1999
group by
i_item_id
@@ -1491,21 +1491,21 @@ select
-- end query 25 in stream 0 using template query25.tpl
-- start query 26 in stream 0 using template query26.tpl
-select i_item_id,
+select i_item_id,
avg(cs_quantity) agg1,
avg(cs_list_price) agg2,
avg(cs_coupon_amt) agg3,
- avg(cs_sales_price) agg4
+ avg(cs_sales_price) agg4
from catalog_sales, customer_demographics, date_dim, item, promotion
where cs_sold_date_sk = d_date_sk and
cs_item_sk = i_item_sk and
cs_bill_cdemo_sk = cd_demo_sk and
cs_promo_sk = p_promo_sk and
- cd_gender = 'M' and
+ cd_gender = 'M' and
cd_marital_status = 'W' and
cd_education_status = 'Unknown' and
(p_channel_email = 'N' or p_channel_event = 'N') and
- d_year = 2002
+ d_year = 2002
group by i_item_id
order by i_item_id
limit 100;
@@ -1541,7 +1541,7 @@ from (select avg(ss_list_price) B1_LP
,count(distinct ss_list_price) B1_CNTD
from store_sales
where ss_quantity between 0 and 5
- and (ss_list_price between 107 and 107+10
+ and (ss_list_price between 107 and 107+10
or ss_coupon_amt between 1319 and 1319+1000
or ss_wholesale_cost between 60 and 60+20)) B1,
(select avg(ss_list_price) B2_LP
@@ -1588,7 +1588,7 @@ limit 100;
-- end query 28 in stream 0 using template query28.tpl
-- start query 29 in stream 0 using template query29.tpl
-select
+select
i_item_id
,i_item_desc
,s_store_id
@@ -1606,7 +1606,7 @@ select
,store
,item
where
- d1.d_moy = 4
+ d1.d_moy = 4
and d1.d_year = 1998
and d1.d_date_sk = ss_sold_date_sk
and i_item_sk = ss_item_sk
@@ -1615,11 +1615,11 @@ select
and ss_item_sk = sr_item_sk
and ss_ticket_number = sr_ticket_number
and sr_returned_date_sk = d2.d_date_sk
- and d2.d_moy between 4 and 4 + 3
+ and d2.d_moy between 4 and 4 + 3
and d2.d_year = 1998
and sr_customer_sk = cs_bill_customer_sk
and sr_item_sk = cs_item_sk
- and cs_sold_date_sk = d3.d_date_sk
+ and cs_sold_date_sk = d3.d_date_sk
and d3.d_year in (1998,1998+1,1998+2)
group by
i_item_id
@@ -1627,7 +1627,7 @@ select
,s_store_id
,s_store_name
order by
- i_item_id
+ i_item_id
,i_item_desc
,s_store_id
,s_store_name
@@ -1637,14 +1637,14 @@ select
-- start query 30 in stream 0 using template query30.tpl
with customer_total_return as
(select wr_returning_customer_sk as ctr_customer_sk
- ,ca_state as ctr_state,
+ ,ca_state as ctr_state,
sum(wr_return_amt) as ctr_total_return
from web_returns
,date_dim
,customer_address
- where wr_returned_date_sk = d_date_sk
+ where wr_returned_date_sk = d_date_sk
and d_year =2000
- and wr_returning_addr_sk = ca_address_sk
+ and wr_returning_addr_sk = ca_address_sk
group by wr_returning_customer_sk
,ca_state)
select c_customer_id,c_salutation,c_first_name,c_last_name,c_preferred_cust_flag
@@ -1654,7 +1654,7 @@ with customer_total_return as
,customer_address
,customer
where ctr1.ctr_total_return > (select avg(ctr_total_return)*1.2
- from customer_total_return ctr2
+ from customer_total_return ctr2
where ctr1.ctr_state = ctr2.ctr_state)
and ca_address_sk = c_current_addr_sk
and ca_state = 'AR'
@@ -1678,7 +1678,7 @@ with ss as
where ws_sold_date_sk = d_date_sk
and ws_bill_addr_sk=ca_address_sk
group by ca_county,d_qoy, d_year)
- select
+ select
ss1.ca_county
,ss1.d_year
,ws2.web_sales/ws1.web_sales web_q1_q2_increase
@@ -1710,7 +1710,7 @@ with ss as
and ws1.ca_county = ws3.ca_county
and ws3.d_qoy = 3
and ws3.d_year =1999
- and case when ws1.web_sales > 0 then ws2.web_sales/ws1.web_sales else null end
+ and case when ws1.web_sales > 0 then ws2.web_sales/ws1.web_sales else null end
> case when ss1.store_sales > 0 then ss2.store_sales/ss1.store_sales else null end
and case when ws2.web_sales > 0 then ws3.web_sales/ws2.web_sales else null end
> case when ss2.store_sales > 0 then ss3.store_sales/ss2.store_sales else null end
@@ -1718,30 +1718,30 @@ with ss as
-- end query 31 in stream 0 using template query31.tpl
-- start query 32 in stream 0 using template query32.tpl
-select sum(cs_ext_discount_amt) as "excess discount amount"
-from
- catalog_sales
- ,item
+select sum(cs_ext_discount_amt) as "excess discount amount"
+from
+ catalog_sales
+ ,item
,date_dim
where
i_manufact_id = 722
-and i_item_sk = cs_item_sk
-and d_date between '2001-03-09' and
+and i_item_sk = cs_item_sk
+and d_date between '2001-03-09' and
(cast('2001-03-09' as date) + interval '90 days')
-and d_date_sk = cs_sold_date_sk
-and cs_ext_discount_amt
- > (
- select
- 1.3 * avg(cs_ext_discount_amt)
- from
- catalog_sales
+and d_date_sk = cs_sold_date_sk
+and cs_ext_discount_amt
+ > (
+ select
+ 1.3 * avg(cs_ext_discount_amt)
+ from
+ catalog_sales
,date_dim
- where
- cs_item_sk = i_item_sk
+ where
+ cs_item_sk = i_item_sk
and d_date between '2001-03-09' and
(cast('2001-03-09' as date) + interval '90 days')
- and d_date_sk = cs_sold_date_sk
- )
+ and d_date_sk = cs_sold_date_sk
+ )
limit 100;
-- end query 32 in stream 0 using template query32.tpl
@@ -1765,7 +1765,7 @@ where i_category in ('Books'))
and d_year = 2001
and d_moy = 3
and ss_addr_sk = ca_address_sk
- and ca_gmt_offset = -5
+ and ca_gmt_offset = -5
group by i_manufact_id),
cs as (
select
@@ -1786,7 +1786,7 @@ where i_category in ('Books'))
and d_year = 2001
and d_moy = 3
and cs_bill_addr_sk = ca_address_sk
- and ca_gmt_offset = -5
+ and ca_gmt_offset = -5
group by i_manufact_id),
ws as (
select
@@ -1810,9 +1810,9 @@ where i_category in ('Books'))
and ca_gmt_offset = -5
group by i_manufact_id)
select i_manufact_id ,sum(total_sales) total_sales
- from (select * from ss
+ from (select * from ss
union all
- select * from cs
+ select * from cs
union all
select * from ws) tmp1
group by i_manufact_id
@@ -1832,15 +1832,15 @@ select c_last_name
,count(*) cnt
from store_sales,date_dim,store,household_demographics
where store_sales.ss_sold_date_sk = date_dim.d_date_sk
- and store_sales.ss_store_sk = store.s_store_sk
+ and store_sales.ss_store_sk = store.s_store_sk
and store_sales.ss_hdemo_sk = household_demographics.hd_demo_sk
and (date_dim.d_dom between 1 and 3 or date_dim.d_dom between 25 and 28)
and (household_demographics.hd_buy_potential = '1001-5000' or
household_demographics.hd_buy_potential = '0-500')
and household_demographics.hd_vehicle_count > 0
- and (case when household_demographics.hd_vehicle_count > 0
- then household_demographics.hd_dep_count/ household_demographics.hd_vehicle_count
- else null
+ and (case when household_demographics.hd_vehicle_count > 0
+ then household_demographics.hd_dep_count/ household_demographics.hd_vehicle_count
+ else null
end) > 1.2
and date_dim.d_year in (2000,2000+1,2000+2)
and store.s_county in ('Williamson County','Williamson County','Williamson County','Williamson County',
@@ -1852,7 +1852,7 @@ select c_last_name
-- end query 34 in stream 0 using template query34.tpl
-- start query 35 in stream 0 using template query35.tpl
-select
+select
ca_state,
cd_gender,
cd_marital_status,
@@ -1875,7 +1875,7 @@ select
customer c,customer_address ca,customer_demographics
where
c.c_current_addr_sk = ca.ca_address_sk and
- cd_demo_sk = c.c_current_cdemo_sk and
+ cd_demo_sk = c.c_current_cdemo_sk and
exists (select *
from store_sales,date_dim
where c.c_customer_sk = ss_customer_sk and
@@ -1887,8 +1887,8 @@ select
where c.c_customer_sk = ws_bill_customer_sk and
ws_sold_date_sk = d_date_sk and
d_year = 1999 and
- d_qoy < 4) or
- exists (select *
+ d_qoy < 4) or
+ exists (select *
from catalog_sales,date_dim
where c.c_customer_sk = cs_ship_customer_sk and
cs_sold_date_sk = d_date_sk and
@@ -1910,14 +1910,16 @@ select
-- end query 35 in stream 0 using template query35.tpl
-- start query 36 in stream 0 using template query36.tpl
-select
+select *
+from
+(select
sum(ss_net_profit)/sum(ss_ext_sales_price) as gross_margin
,i_category
,i_class
,grouping(i_category)+grouping(i_class) as lochierarchy
,rank() over (
partition by grouping(i_category)+grouping(i_class),
- case when grouping(i_class) = 0 then i_category end
+ case when grouping(i_class) = 0 then i_category end
order by sum(ss_net_profit)/sum(ss_ext_sales_price) asc) as rank_within_parent
from
store_sales
@@ -1925,13 +1927,13 @@ select
,item
,store
where
- d1.d_year = 2000
+ d1.d_year = 2000
and d1.d_date_sk = ss_sold_date_sk
- and i_item_sk = ss_item_sk
+ and i_item_sk = ss_item_sk
and s_store_sk = ss_store_sk
and s_state in ('TN','TN','TN','TN',
'TN','TN','TN','TN')
- group by rollup(i_category,i_class)
+ group by rollup(i_category,i_class)) as sub
order by
lochierarchy desc
,case when lochierarchy = 0 then i_category end
@@ -2034,27 +2036,27 @@ order by inv1.w_warehouse_sk,inv1.i_item_sk,inv1.d_moy,inv1.mean,inv1.cov
-- end query 39 in stream 0 using template query39.tpl
-- start query 40 in stream 0 using template query40.tpl
-select
+select
w_state
,i_item_id
- ,sum(case when (cast(d_date as date) < cast ('2001-05-02' as date))
+ ,sum(case when (cast(d_date as date) < cast ('2001-05-02' as date))
then cs_sales_price - coalesce(cr_refunded_cash,0) else 0 end) as sales_before
- ,sum(case when (cast(d_date as date) >= cast ('2001-05-02' as date))
+ ,sum(case when (cast(d_date as date) >= cast ('2001-05-02' as date))
then cs_sales_price - coalesce(cr_refunded_cash,0) else 0 end) as sales_after
from
catalog_sales left outer join catalog_returns on
- (cs_order_number = cr_order_number
+ (cs_order_number = cr_order_number
and cs_item_sk = cr_item_sk)
- ,warehouse
+ ,warehouse
,item
,date_dim
where
i_current_price between 0.99 and 1.49
and i_item_sk = cs_item_sk
- and cs_warehouse_sk = w_warehouse_sk
+ and cs_warehouse_sk = w_warehouse_sk
and cs_sold_date_sk = d_date_sk
and d_date between (cast ('2001-05-02' as date) - interval '30 days')
- and (cast ('2001-05-02' as date) + interval '30 days')
+ and (cast ('2001-05-02' as date) + interval '30 days')
group by
w_state,i_item_id
order by w_state,i_item_id
@@ -2064,12 +2066,12 @@ limit 100;
-- start query 41 in stream 0 using template query41.tpl
select distinct(i_product_name)
from item i1
- where i_manufact_id between 704 and 704+40
+ where i_manufact_id between 704 and 704+40
and (select count(*) as item_cnt
from item
where (i_manufact = i1.i_manufact and
- ((i_category = 'Women' and
- (i_color = 'forest' or i_color = 'lime') and
+ ((i_category = 'Women' and
+ (i_color = 'forest' or i_color = 'lime') and
(i_units = 'Pallet' or i_units = 'Pound') and
(i_size = 'economy' or i_size = 'small')
) or
@@ -2089,8 +2091,8 @@ select distinct(i_product_name)
(i_size = 'economy' or i_size = 'small')
))) or
(i_manufact = i1.i_manufact and
- ((i_category = 'Women' and
- (i_color = 'dark' or i_color = 'aquamarine') and
+ ((i_category = 'Women' and
+ (i_color = 'dark' or i_color = 'aquamarine') and
(i_units = 'Ton' or i_units = 'Tbl') and
(i_size = 'economy' or i_size = 'small')
) or
@@ -2123,7 +2125,7 @@ select dt.d_year
,item
where dt.d_date_sk = store_sales.ss_sold_date_sk
and store_sales.ss_item_sk = item.i_item_sk
- and item.i_manager_id = 1
+ and item.i_manager_id = 1
and dt.d_moy=11
and dt.d_year=1998
group by dt.d_year
@@ -2148,7 +2150,7 @@ select s_store_name, s_store_id,
where d_date_sk = ss_sold_date_sk and
s_store_sk = ss_store_sk and
s_gmt_offset = -5 and
- d_year = 2000
+ d_year = 2000
group by s_store_name, s_store_id
order by s_store_name, s_store_id,sun_sales,mon_sales,tue_sales,wed_sales,thu_sales,fri_sales,sat_sales
limit 100;
@@ -2158,7 +2160,7 @@ select s_store_name, s_store_id,
select asceding.rnk, i1.i_product_name best_performing, i2.i_product_name worst_performing
from(select *
from (select item_sk,rank() over (order by rank_col asc) rnk
- from (select ss_item_sk item_sk,avg(ss_net_profit) rank_col
+ from (select ss_item_sk item_sk,avg(ss_net_profit) rank_col
from store_sales ss1
where ss_store_sk = 4
group by ss_item_sk
@@ -2182,7 +2184,7 @@ from(select *
where rnk < 11) descending,
item i1,
item i2
-where asceding.rnk = descending.rnk
+where asceding.rnk = descending.rnk
and i1.i_item_sk=asceding.item_sk
and i2.i_item_sk=descending.item_sk
order by asceding.rnk
@@ -2193,10 +2195,10 @@ limit 100;
select ca_zip, ca_city, sum(ws_sales_price)
from web_sales, customer, customer_address, date_dim, item
where ws_bill_customer_sk = c_customer_sk
- and c_current_addr_sk = ca_address_sk
- and ws_item_sk = i_item_sk
+ and c_current_addr_sk = ca_address_sk
+ and ws_item_sk = i_item_sk
and ( substr(ca_zip,1,5) in ('85669', '86197','88274','83405','86475', '85392', '85460', '80348', '81792')
- or
+ or
i_item_id in (select i_item_id
from item
where i_item_sk in (2, 3, 5, 7, 11, 13, 17, 19, 23, 29)
@@ -2215,23 +2217,23 @@ select c_last_name
,ca_city
,bought_city
,ss_ticket_number
- ,amt,profit
+ ,amt,profit
from
(select ss_ticket_number
,ss_customer_sk
,ca_city bought_city
,sum(ss_coupon_amt) amt
,sum(ss_net_profit) profit
- from store_sales,date_dim,store,household_demographics,customer_address
+ from store_sales,date_dim,store,household_demographics,customer_address
where store_sales.ss_sold_date_sk = date_dim.d_date_sk
- and store_sales.ss_store_sk = store.s_store_sk
+ and store_sales.ss_store_sk = store.s_store_sk
and store_sales.ss_hdemo_sk = household_demographics.hd_demo_sk
and store_sales.ss_addr_sk = customer_address.ca_address_sk
and (household_demographics.hd_dep_count = 8 or
household_demographics.hd_vehicle_count= 0)
and date_dim.d_dow in (6,0)
- and date_dim.d_year in (2000,2000+1,2000+2)
- and store.s_city in ('Midway','Fairview','Fairview','Midway','Fairview')
+ and date_dim.d_year in (2000,2000+1,2000+2)
+ and store.s_city in ('Midway','Fairview','Fairview','Midway','Fairview')
group by ss_ticket_number,ss_customer_sk,ss_addr_sk,ca_city) dn,customer,customer_address current_addr
where ss_customer_sk = c_customer_sk
and customer.c_current_addr_sk = current_addr.ca_address_sk
@@ -2288,7 +2290,7 @@ with v1 as(
v1.rn = v1_lead.rn - 1)
select *
from v2
- where d_year = 2000 and
+ where d_year = 2000 and
avg_monthly_sales > 0 and
case when avg_monthly_sales > 0 then abs(sum_sales - avg_monthly_sales) / avg_monthly_sales else null end > 0.1
order by sum_sales - avg_monthly_sales, nsum
@@ -2300,36 +2302,36 @@ select sum (ss_quantity)
from store_sales, store, customer_demographics, customer_address, date_dim
where s_store_sk = ss_store_sk
and ss_sold_date_sk = d_date_sk and d_year = 2001
- and
+ and
(
(
cd_demo_sk = ss_cdemo_sk
- and
+ and
cd_marital_status = 'S'
- and
+ and
cd_education_status = 'Secondary'
- and
- ss_sales_price between 100.00 and 150.00
+ and
+ ss_sales_price between 100.00 and 150.00
)
or
(
cd_demo_sk = ss_cdemo_sk
- and
+ and
cd_marital_status = 'M'
- and
+ and
cd_education_status = '2 yr Degree'
- and
- ss_sales_price between 50.00 and 100.00
+ and
+ ss_sales_price between 50.00 and 100.00
)
- or
+ or
(
cd_demo_sk = ss_cdemo_sk
- and
+ and
cd_marital_status = 'D'
- and
+ and
cd_education_status = 'Advanced Degree'
- and
- ss_sales_price between 150.00 and 200.00
+ and
+ ss_sales_price between 150.00 and 200.00
)
)
and
@@ -2340,7 +2342,7 @@ select sum (ss_quantity)
ca_country = 'United States'
and
ca_state in ('ND', 'NY', 'SD')
- and ss_net_profit between 0 and 2000
+ and ss_net_profit between 0 and 2000
)
or
(ss_addr_sk = ca_address_sk
@@ -2348,7 +2350,7 @@ select sum (ss_quantity)
ca_country = 'United States'
and
ca_state in ('MD', 'GA', 'KS')
- and ss_net_profit between 150 and 3000
+ and ss_net_profit between 150 and 3000
)
or
(ss_addr_sk = ca_address_sk
@@ -2356,7 +2358,7 @@ select sum (ss_quantity)
ca_country = 'United States'
and
ca_state in ('CO', 'MN', 'NC')
- and ss_net_profit between 50 and 25000
+ and ss_net_profit between 50 and 25000
)
)
;
@@ -2371,7 +2373,7 @@ select channel, item, return_ratio, return_rank, currency_rank from
,web.return_rank
,web.currency_rank
from (
- select
+ select
item
,return_ratio
,currency_ratio
@@ -2383,13 +2385,13 @@ select channel, item, return_ratio, return_rank, currency_rank from
cast(sum(coalesce(ws.ws_quantity,0)) as decimal(15,4) )) as return_ratio
,(cast(sum(coalesce(wr.wr_return_amt,0)) as decimal(15,4))/
cast(sum(coalesce(ws.ws_net_paid,0)) as decimal(15,4) )) as currency_ratio
- from
- web_sales ws left outer join web_returns wr
- on (ws.ws_order_number = wr.wr_order_number and
+ from
+ web_sales ws left outer join web_returns wr
+ on (ws.ws_order_number = wr.wr_order_number and
ws.ws_item_sk = wr.wr_item_sk)
,date_dim
- where
- wr.wr_return_amt > 10000
+ where
+ wr.wr_return_amt > 10000
and ws.ws_net_profit > 1
and ws.ws_net_paid > 0
and ws.ws_quantity > 0
@@ -2399,40 +2401,40 @@ select channel, item, return_ratio, return_rank, currency_rank from
group by ws.ws_item_sk
) in_web
) as web
- where
+ where
(
web.return_rank <= 10
or
web.currency_rank <= 10
)
union
- select
+ select
'catalog' as channel
,catalog.item
,catalog.return_ratio
,catalog.return_rank
,catalog.currency_rank
from (
- select
+ select
item
,return_ratio
,currency_ratio
,rank() over (order by return_ratio) as return_rank
,rank() over (order by currency_ratio) as currency_rank
from
- ( select
+ ( select
cs.cs_item_sk as item
,(cast(sum(coalesce(cr.cr_return_quantity,0)) as decimal(15,4))/
cast(sum(coalesce(cs.cs_quantity,0)) as decimal(15,4) )) as return_ratio
,(cast(sum(coalesce(cr.cr_return_amount,0)) as decimal(15,4))/
cast(sum(coalesce(cs.cs_net_paid,0)) as decimal(15,4) )) as currency_ratio
- from
+ from
catalog_sales cs left outer join catalog_returns cr
- on (cs.cs_order_number = cr.cr_order_number and
+ on (cs.cs_order_number = cr.cr_order_number and
cs.cs_item_sk = cr.cr_item_sk)
,date_dim
- where
- cr.cr_return_amount > 10000
+ where
+ cr.cr_return_amount > 10000
and cs.cs_net_profit > 1
and cs.cs_net_paid > 0
and cs.cs_quantity > 0
@@ -2442,21 +2444,21 @@ select channel, item, return_ratio, return_rank, currency_rank from
group by cs.cs_item_sk
) in_cat
) as catalog
- where
+ where
(
catalog.return_rank <= 10
or
catalog.currency_rank <=10
)
union
- select
+ select
'store' as channel
,store.item
,store.return_ratio
,store.return_rank
,store.currency_rank
from (
- select
+ select
item
,return_ratio
,currency_ratio
@@ -2466,14 +2468,14 @@ select channel, item, return_ratio, return_rank, currency_rank from
( select sts.ss_item_sk as item
,(cast(sum(coalesce(sr.sr_return_quantity,0)) as decimal(15,4))/cast(sum(coalesce(sts.ss_quantity,0)) as decimal(15,4) )) as return_ratio
,(cast(sum(coalesce(sr.sr_return_amt,0)) as decimal(15,4))/cast(sum(coalesce(sts.ss_net_paid,0)) as decimal(15,4) )) as currency_ratio
- from
+ from
store_sales sts left outer join store_returns sr
on (sts.ss_ticket_number = sr.sr_ticket_number and sts.ss_item_sk = sr.sr_item_sk)
,date_dim
- where
- sr.sr_return_amt > 10000
+ where
+ sr.sr_return_amt > 10000
and sts.ss_net_profit > 1
- and sts.ss_net_paid > 0
+ and sts.ss_net_paid > 0
and sts.ss_quantity > 0
and ss_sold_date_sk = d_date_sk
and d_year = 1998
@@ -2483,7 +2485,7 @@ select channel, item, return_ratio, return_rank, currency_rank from
) as store
where (
store.return_rank <= 10
- or
+ or
store.currency_rank <= 10
)
)as tab
@@ -2492,7 +2494,7 @@ select channel, item, return_ratio, return_rank, currency_rank from
-- end query 49 in stream 0 using template query49.tpl
-- start query 50 in stream 0 using template query50.tpl
-select
+select
s_store_name
,s_company_id
,s_street_number
@@ -2503,14 +2505,14 @@ select
,s_county
,s_state
,s_zip
- ,sum(case when (sr_returned_date_sk - ss_sold_date_sk <= 30 ) then 1 else 0 end) as "30 days"
- ,sum(case when (sr_returned_date_sk - ss_sold_date_sk > 30) and
- (sr_returned_date_sk - ss_sold_date_sk <= 60) then 1 else 0 end ) as "31-60 days"
- ,sum(case when (sr_returned_date_sk - ss_sold_date_sk > 60) and
- (sr_returned_date_sk - ss_sold_date_sk <= 90) then 1 else 0 end) as "61-90 days"
+ ,sum(case when (sr_returned_date_sk - ss_sold_date_sk <= 30 ) then 1 else 0 end) as "30 days"
+ ,sum(case when (sr_returned_date_sk - ss_sold_date_sk > 30) and
+ (sr_returned_date_sk - ss_sold_date_sk <= 60) then 1 else 0 end ) as "31-60 days"
+ ,sum(case when (sr_returned_date_sk - ss_sold_date_sk > 60) and
+ (sr_returned_date_sk - ss_sold_date_sk <= 90) then 1 else 0 end) as "61-90 days"
,sum(case when (sr_returned_date_sk - ss_sold_date_sk > 90) and
- (sr_returned_date_sk - ss_sold_date_sk <= 120) then 1 else 0 end) as "91-120 days"
- ,sum(case when (sr_returned_date_sk - ss_sold_date_sk > 120) then 1 else 0 end) as ">120 days"
+ (sr_returned_date_sk - ss_sold_date_sk <= 120) then 1 else 0 end) as "91-120 days"
+ ,sum(case when (sr_returned_date_sk - ss_sold_date_sk > 120) then 1 else 0 end) as ">120 days"
from
store_sales
,store_returns
@@ -2618,7 +2620,7 @@ limit 100 ;
-- end query 52 in stream 0 using template query52.tpl
-- start query 53 in stream 0 using template query53.tpl
-select * from
+select * from
(select i_manufact_id,
sum(ss_sales_price) sum_sales,
avg(sum(ss_sales_price)) over (partition by i_manufact_id) avg_quarterly_sales
@@ -2636,8 +2638,8 @@ i_class in ('accessories','classical','fragrances','pants') and
i_brand in ('amalgimporto #1','edu packscholar #1','exportiimporto #1',
'importoamalg #1')))
group by i_manufact_id, d_qoy ) tmp1
-where case when avg_quarterly_sales > 0
- then abs (sum_sales - avg_quarterly_sales)/ avg_quarterly_sales
+where case when avg_quarterly_sales > 0
+ then abs (sum_sales - avg_quarterly_sales)/ avg_quarterly_sales
else null end > 0.1
order by avg_quarterly_sales,
sum_sales,
@@ -2649,7 +2651,7 @@ limit 100;
with my_customers as (
select distinct c_customer_sk
, c_current_addr_sk
- from
+ from
( select cs_sold_date_sk sold_date_sk,
cs_bill_customer_sk customer_sk,
cs_item_sk item_sk
@@ -2732,7 +2734,7 @@ where i_color in ('powder','orchid','pink'))
and d_year = 2000
and d_moy = 3
and ss_addr_sk = ca_address_sk
- and ca_gmt_offset = -6
+ and ca_gmt_offset = -6
group by i_item_id),
cs as (
select i_item_id,sum(cs_ext_sales_price) total_sales
@@ -2751,7 +2753,7 @@ where i_color in ('powder','orchid','pink'))
and d_year = 2000
and d_moy = 3
and cs_bill_addr_sk = ca_address_sk
- and ca_gmt_offset = -6
+ and ca_gmt_offset = -6
group by i_item_id),
ws as (
select i_item_id,sum(ws_ext_sales_price) total_sales
@@ -2773,9 +2775,9 @@ where i_color in ('powder','orchid','pink'))
and ca_gmt_offset = -6
group by i_item_id)
select i_item_id ,sum(total_sales) total_sales
- from (select * from ss
+ from (select * from ss
union all
- select * from cs
+ select * from cs
union all
select * from ws) tmp1
group by i_item_id
@@ -2835,14 +2837,14 @@ with v1 as(
-- start query 58 in stream 0 using template query58.tpl
with ss_items as
(select i_item_id item_id
- ,sum(ss_ext_sales_price) ss_item_rev
+ ,sum(ss_ext_sales_price) ss_item_rev
from store_sales
,item
,date_dim
where ss_item_sk = i_item_sk
and d_date in (select d_date
from date_dim
- where d_week_seq = (select d_week_seq
+ where d_week_seq = (select d_week_seq
from date_dim
where d_date = '2001-06-16'))
and ss_sold_date_sk = d_date_sk
@@ -2856,7 +2858,7 @@ with ss_items as
where cs_item_sk = i_item_sk
and d_date in (select d_date
from date_dim
- where d_week_seq = (select d_week_seq
+ where d_week_seq = (select d_week_seq
from date_dim
where d_date = '2001-06-16'))
and cs_sold_date_sk = d_date_sk
@@ -2870,7 +2872,7 @@ with ss_items as
where ws_item_sk = i_item_sk
and d_date in (select d_date
from date_dim
- where d_week_seq =(select d_week_seq
+ where d_week_seq =(select d_week_seq
from date_dim
where d_date = '2001-06-16'))
and ws_sold_date_sk = d_date_sk
@@ -2885,7 +2887,7 @@ with ss_items as
,(ss_item_rev+cs_item_rev+ws_item_rev)/3 average
from ss_items,cs_items,ws_items
where ss_items.item_id=cs_items.item_id
- and ss_items.item_id=ws_items.item_id
+ and ss_items.item_id=ws_items.item_id
and ss_item_rev between 0.9 * cs_item_rev and 1.1 * cs_item_rev
and ss_item_rev between 0.9 * ws_item_rev and 1.1 * ws_item_rev
and cs_item_rev between 0.9 * ss_item_rev and 1.1 * ss_item_rev
@@ -2898,7 +2900,7 @@ with ss_items as
-- end query 58 in stream 0 using template query58.tpl
-- start query 59 in stream 0 using template query59.tpl
-with wss as
+with wss as
(select d_week_seq,
ss_store_sk,
sum(case when (d_day_name='Sunday') then ss_sales_price else null end) sun_sales,
@@ -2924,7 +2926,7 @@ with wss as
,fri_sales fri_sales1,sat_sales sat_sales1
from wss,store,date_dim d
where d.d_week_seq = wss.d_week_seq and
- ss_store_sk = s_store_sk and
+ ss_store_sk = s_store_sk and
d_month_seq between 1195 and 1195 + 11) y,
(select s_store_name s_store_name2,wss.d_week_seq d_week_seq2
,s_store_id s_store_id2,sun_sales sun_sales2
@@ -2933,7 +2935,7 @@ with wss as
,fri_sales fri_sales2,sat_sales sat_sales2
from wss,store,date_dim d
where d.d_week_seq = wss.d_week_seq and
- ss_store_sk = s_store_sk and
+ ss_store_sk = s_store_sk and
d_month_seq between 1195+ 12 and 1195 + 23) x
where s_store_id1=s_store_id2
and d_week_seq1=d_week_seq2-52
@@ -2961,7 +2963,7 @@ where i_category in ('Jewelry'))
and d_year = 2000
and d_moy = 10
and ss_addr_sk = ca_address_sk
- and ca_gmt_offset = -5
+ and ca_gmt_offset = -5
group by i_item_id),
cs as (
select
@@ -2982,7 +2984,7 @@ where i_category in ('Jewelry'))
and d_year = 2000
and d_moy = 10
and cs_bill_addr_sk = ca_address_sk
- and ca_gmt_offset = -5
+ and ca_gmt_offset = -5
group by i_item_id),
ws as (
select
@@ -3005,12 +3007,12 @@ where i_category in ('Jewelry'))
and ws_bill_addr_sk = ca_address_sk
and ca_gmt_offset = -5
group by i_item_id)
- select
+ select
i_item_id
,sum(total_sales) total_sales
- from (select * from ss
+ from (select * from ss
union all
- select * from cs
+ select * from cs
union all
select * from ws) tmp1
group by i_item_id
@@ -3028,14 +3030,14 @@ from
,promotion
,date_dim
,customer
- ,customer_address
+ ,customer_address
,item
where ss_sold_date_sk = d_date_sk
and ss_store_sk = s_store_sk
and ss_promo_sk = p_promo_sk
and ss_customer_sk= c_customer_sk
and ca_address_sk = c_current_addr_sk
- and ss_item_sk = i_item_sk
+ and ss_item_sk = i_item_sk
and ca_gmt_offset = -7
and i_category = 'Home'
and (p_channel_dmail = 'Y' or p_channel_email = 'Y' or p_channel_tv = 'Y')
@@ -3064,18 +3066,18 @@ limit 100;
-- end query 61 in stream 0 using template query61.tpl
-- start query 62 in stream 0 using template query62.tpl
-select
+select
substr(w_warehouse_name,1,20)
,sm_type
,web_name
- ,sum(case when (ws_ship_date_sk - ws_sold_date_sk <= 30 ) then 1 else 0 end) as "30 days"
- ,sum(case when (ws_ship_date_sk - ws_sold_date_sk > 30) and
- (ws_ship_date_sk - ws_sold_date_sk <= 60) then 1 else 0 end ) as "31-60 days"
- ,sum(case when (ws_ship_date_sk - ws_sold_date_sk > 60) and
- (ws_ship_date_sk - ws_sold_date_sk <= 90) then 1 else 0 end) as "61-90 days"
+ ,sum(case when (ws_ship_date_sk - ws_sold_date_sk <= 30 ) then 1 else 0 end) as "30 days"
+ ,sum(case when (ws_ship_date_sk - ws_sold_date_sk > 30) and
+ (ws_ship_date_sk - ws_sold_date_sk <= 60) then 1 else 0 end ) as "31-60 days"
+ ,sum(case when (ws_ship_date_sk - ws_sold_date_sk > 60) and
+ (ws_ship_date_sk - ws_sold_date_sk <= 90) then 1 else 0 end) as "61-90 days"
,sum(case when (ws_ship_date_sk - ws_sold_date_sk > 90) and
- (ws_ship_date_sk - ws_sold_date_sk <= 120) then 1 else 0 end) as "91-120 days"
- ,sum(case when (ws_ship_date_sk - ws_sold_date_sk > 120) then 1 else 0 end) as ">120 days"
+ (ws_ship_date_sk - ws_sold_date_sk <= 120) then 1 else 0 end) as "91-120 days"
+ ,sum(case when (ws_ship_date_sk - ws_sold_date_sk > 120) then 1 else 0 end) as ">120 days"
from
web_sales
,warehouse
@@ -3099,7 +3101,7 @@ limit 100;
-- end query 62 in stream 0 using template query62.tpl
-- start query 63 in stream 0 using template query63.tpl
-select *
+select *
from (select i_manager_id
,sum(ss_sales_price) sum_sales
,avg(sum(ss_sales_price)) over (partition by i_manager_id) avg_monthly_sales
@@ -3249,7 +3251,7 @@ order by cs1.product_name
-- end query 64 in stream 0 using template query64.tpl
-- start query 65 in stream 0 using template query65.tpl
-select
+select
s_store_name,
i_item_desc,
sc.revenue,
@@ -3259,7 +3261,7 @@ select
from store, item,
(select ss_store_sk, avg(revenue) as ave
from
- (select ss_store_sk, ss_item_sk,
+ (select ss_store_sk, ss_item_sk,
sum(ss_sales_price) as revenue
from store_sales, date_dim
where ss_sold_date_sk = d_date_sk and d_month_seq between 1176 and 1176+11
@@ -3269,7 +3271,7 @@ select
from store_sales, date_dim
where ss_sold_date_sk = d_date_sk and d_month_seq between 1176 and 1176+11
group by ss_store_sk, ss_item_sk) sc
- where sb.ss_store_sk = sc.ss_store_sk and
+ where sb.ss_store_sk = sc.ss_store_sk and
sc.revenue <= 0.1 * sb.ave and
s_store_sk = sc.ss_store_sk and
i_item_sk = sc.ss_item_sk
@@ -3278,7 +3280,7 @@ limit 100;
-- end query 65 in stream 0 using template query65.tpl
-- start query 66 in stream 0 using template query66.tpl
-select
+select
w_warehouse_name
,w_warehouse_sq_ft
,w_city
@@ -3324,7 +3326,7 @@ select
,sum(nov_net) as nov_net
,sum(dec_net) as dec_net
from (
- select
+ select
w_warehouse_name
,w_warehouse_sq_ft
,w_city
@@ -3333,49 +3335,49 @@ select
,w_country
,'ORIENTAL' || ',' || 'BOXBUNDLES' as ship_carriers
,d_year as year
- ,sum(case when d_moy = 1
+ ,sum(case when d_moy = 1
then ws_ext_sales_price* ws_quantity else 0 end) as jan_sales
- ,sum(case when d_moy = 2
+ ,sum(case when d_moy = 2
then ws_ext_sales_price* ws_quantity else 0 end) as feb_sales
- ,sum(case when d_moy = 3
+ ,sum(case when d_moy = 3
then ws_ext_sales_price* ws_quantity else 0 end) as mar_sales
- ,sum(case when d_moy = 4
+ ,sum(case when d_moy = 4
then ws_ext_sales_price* ws_quantity else 0 end) as apr_sales
- ,sum(case when d_moy = 5
+ ,sum(case when d_moy = 5
then ws_ext_sales_price* ws_quantity else 0 end) as may_sales
- ,sum(case when d_moy = 6
+ ,sum(case when d_moy = 6
then ws_ext_sales_price* ws_quantity else 0 end) as jun_sales
- ,sum(case when d_moy = 7
+ ,sum(case when d_moy = 7
then ws_ext_sales_price* ws_quantity else 0 end) as jul_sales
- ,sum(case when d_moy = 8
+ ,sum(case when d_moy = 8
then ws_ext_sales_price* ws_quantity else 0 end) as aug_sales
- ,sum(case when d_moy = 9
+ ,sum(case when d_moy = 9
then ws_ext_sales_price* ws_quantity else 0 end) as sep_sales
- ,sum(case when d_moy = 10
+ ,sum(case when d_moy = 10
then ws_ext_sales_price* ws_quantity else 0 end) as oct_sales
,sum(case when d_moy = 11
then ws_ext_sales_price* ws_quantity else 0 end) as nov_sales
,sum(case when d_moy = 12
then ws_ext_sales_price* ws_quantity else 0 end) as dec_sales
- ,sum(case when d_moy = 1
+ ,sum(case when d_moy = 1
then ws_net_paid_inc_ship * ws_quantity else 0 end) as jan_net
,sum(case when d_moy = 2
then ws_net_paid_inc_ship * ws_quantity else 0 end) as feb_net
- ,sum(case when d_moy = 3
+ ,sum(case when d_moy = 3
then ws_net_paid_inc_ship * ws_quantity else 0 end) as mar_net
- ,sum(case when d_moy = 4
+ ,sum(case when d_moy = 4
then ws_net_paid_inc_ship * ws_quantity else 0 end) as apr_net
- ,sum(case when d_moy = 5
+ ,sum(case when d_moy = 5
then ws_net_paid_inc_ship * ws_quantity else 0 end) as may_net
- ,sum(case when d_moy = 6
+ ,sum(case when d_moy = 6
then ws_net_paid_inc_ship * ws_quantity else 0 end) as jun_net
- ,sum(case when d_moy = 7
+ ,sum(case when d_moy = 7
then ws_net_paid_inc_ship * ws_quantity else 0 end) as jul_net
- ,sum(case when d_moy = 8
+ ,sum(case when d_moy = 8
then ws_net_paid_inc_ship * ws_quantity else 0 end) as aug_net
- ,sum(case when d_moy = 9
+ ,sum(case when d_moy = 9
then ws_net_paid_inc_ship * ws_quantity else 0 end) as sep_net
- ,sum(case when d_moy = 10
+ ,sum(case when d_moy = 10
then ws_net_paid_inc_ship * ws_quantity else 0 end) as oct_net
,sum(case when d_moy = 11
then ws_net_paid_inc_ship * ws_quantity else 0 end) as nov_net
@@ -3393,9 +3395,9 @@ select
and ws_sold_time_sk = t_time_sk
and ws_ship_mode_sk = sm_ship_mode_sk
and d_year = 2001
- and t_time between 42970 and 42970+28800
+ and t_time between 42970 and 42970+28800
and sm_carrier in ('ORIENTAL','BOXBUNDLES')
- group by
+ group by
w_warehouse_name
,w_warehouse_sq_ft
,w_city
@@ -3404,7 +3406,7 @@ select
,w_country
,d_year
union all
- select
+ select
w_warehouse_name
,w_warehouse_sq_ft
,w_city
@@ -3413,49 +3415,49 @@ select
,w_country
,'ORIENTAL' || ',' || 'BOXBUNDLES' as ship_carriers
,d_year as year
- ,sum(case when d_moy = 1
+ ,sum(case when d_moy = 1
then cs_ext_list_price* cs_quantity else 0 end) as jan_sales
- ,sum(case when d_moy = 2
+ ,sum(case when d_moy = 2
then cs_ext_list_price* cs_quantity else 0 end) as feb_sales
- ,sum(case when d_moy = 3
+ ,sum(case when d_moy = 3
then cs_ext_list_price* cs_quantity else 0 end) as mar_sales
- ,sum(case when d_moy = 4
+ ,sum(case when d_moy = 4
then cs_ext_list_price* cs_quantity else 0 end) as apr_sales
- ,sum(case when d_moy = 5
+ ,sum(case when d_moy = 5
then cs_ext_list_price* cs_quantity else 0 end) as may_sales
- ,sum(case when d_moy = 6
+ ,sum(case when d_moy = 6
then cs_ext_list_price* cs_quantity else 0 end) as jun_sales
- ,sum(case when d_moy = 7
+ ,sum(case when d_moy = 7
then cs_ext_list_price* cs_quantity else 0 end) as jul_sales
- ,sum(case when d_moy = 8
+ ,sum(case when d_moy = 8
then cs_ext_list_price* cs_quantity else 0 end) as aug_sales
- ,sum(case when d_moy = 9
+ ,sum(case when d_moy = 9
then cs_ext_list_price* cs_quantity else 0 end) as sep_sales
- ,sum(case when d_moy = 10
+ ,sum(case when d_moy = 10
then cs_ext_list_price* cs_quantity else 0 end) as oct_sales
,sum(case when d_moy = 11
then cs_ext_list_price* cs_quantity else 0 end) as nov_sales
,sum(case when d_moy = 12
then cs_ext_list_price* cs_quantity else 0 end) as dec_sales
- ,sum(case when d_moy = 1
+ ,sum(case when d_moy = 1
then cs_net_paid * cs_quantity else 0 end) as jan_net
- ,sum(case when d_moy = 2
+ ,sum(case when d_moy = 2
then cs_net_paid * cs_quantity else 0 end) as feb_net
- ,sum(case when d_moy = 3
+ ,sum(case when d_moy = 3
then cs_net_paid * cs_quantity else 0 end) as mar_net
- ,sum(case when d_moy = 4
+ ,sum(case when d_moy = 4
then cs_net_paid * cs_quantity else 0 end) as apr_net
- ,sum(case when d_moy = 5
+ ,sum(case when d_moy = 5
then cs_net_paid * cs_quantity else 0 end) as may_net
- ,sum(case when d_moy = 6
+ ,sum(case when d_moy = 6
then cs_net_paid * cs_quantity else 0 end) as jun_net
- ,sum(case when d_moy = 7
+ ,sum(case when d_moy = 7
then cs_net_paid * cs_quantity else 0 end) as jul_net
- ,sum(case when d_moy = 8
+ ,sum(case when d_moy = 8
then cs_net_paid * cs_quantity else 0 end) as aug_net
- ,sum(case when d_moy = 9
+ ,sum(case when d_moy = 9
then cs_net_paid * cs_quantity else 0 end) as sep_net
- ,sum(case when d_moy = 10
+ ,sum(case when d_moy = 10
then cs_net_paid * cs_quantity else 0 end) as oct_net
,sum(case when d_moy = 11
then cs_net_paid * cs_quantity else 0 end) as nov_net
@@ -3473,9 +3475,9 @@ select
and cs_sold_time_sk = t_time_sk
and cs_ship_mode_sk = sm_ship_mode_sk
and d_year = 2001
- and t_time between 42970 AND 42970+28800
+ and t_time between 42970 AND 42970+28800
and sm_carrier in ('ORIENTAL','BOXBUNDLES')
- group by
+ group by
w_warehouse_name
,w_warehouse_sq_ft
,w_city
@@ -3484,7 +3486,7 @@ select
,w_country
,d_year
) x
- group by
+ group by
w_warehouse_name
,w_warehouse_sq_ft
,w_city
@@ -3553,19 +3555,19 @@ select c_last_name
from (select ss_ticket_number
,ss_customer_sk
,ca_city bought_city
- ,sum(ss_ext_sales_price) extended_price
+ ,sum(ss_ext_sales_price) extended_price
,sum(ss_ext_list_price) list_price
- ,sum(ss_ext_tax) extended_tax
+ ,sum(ss_ext_tax) extended_tax
from store_sales
,date_dim
,store
,household_demographics
- ,customer_address
+ ,customer_address
where store_sales.ss_sold_date_sk = date_dim.d_date_sk
- and store_sales.ss_store_sk = store.s_store_sk
+ and store_sales.ss_store_sk = store.s_store_sk
and store_sales.ss_hdemo_sk = household_demographics.hd_demo_sk
and store_sales.ss_addr_sk = customer_address.ca_address_sk
- and date_dim.d_dom between 1 and 2
+ and date_dim.d_dom between 1 and 2
and (household_demographics.hd_dep_count = 3 or
household_demographics.hd_vehicle_count= 4)
and date_dim.d_year in (1998,1998+1,1998+2)
@@ -3584,7 +3586,7 @@ select c_last_name
-- end query 68 in stream 0 using template query68.tpl
-- start query 69 in stream 0 using template query69.tpl
-select
+select
cd_gender,
cd_marital_status,
cd_education_status,
@@ -3598,7 +3600,7 @@ select
where
c.c_current_addr_sk = ca.ca_address_sk and
ca_state in ('IL','TX','ME') and
- cd_demo_sk = c.c_current_cdemo_sk and
+ cd_demo_sk = c.c_current_cdemo_sk and
exists (select *
from store_sales,date_dim
where c.c_customer_sk = ss_customer_sk and
@@ -3611,7 +3613,7 @@ select
ws_sold_date_sk = d_date_sk and
d_year = 2002 and
d_moy between 1 and 1+2) and
- not exists (select *
+ not exists (select *
from catalog_sales,date_dim
where c.c_customer_sk = cs_ship_customer_sk and
cs_sold_date_sk = d_date_sk and
@@ -3631,14 +3633,15 @@ select
-- end query 69 in stream 0 using template query69.tpl
-- start query 70 in stream 0 using template query70.tpl
-select
+select *
+from (select
sum(ss_net_profit) as total_sum
,s_state
,s_county
,grouping(s_state)+grouping(s_county) as lochierarchy
,rank() over (
partition by grouping(s_state)+grouping(s_county),
- case when grouping(s_county) = 0 then s_state end
+ case when grouping(s_county) = 0 then s_state end
order by sum(ss_net_profit) desc) as rank_within_parent
from
store_sales
@@ -3657,10 +3660,10 @@ select
and d_date_sk = ss_sold_date_sk
and s_store_sk = ss_store_sk
group by s_state
- ) tmp1
+ ) tmp1
where ranking <= 5
)
- group by rollup(s_state,s_county)
+ group by rollup(s_state,s_county)) as sub
order by
lochierarchy desc
,case when lochierarchy = 0 then s_state end
@@ -3671,10 +3674,10 @@ select
-- start query 71 in stream 0 using template query71.tpl
select i_brand_id brand_id, i_brand brand,t_hour,t_minute,
sum(ext_price) ext_price
- from item, (select ws_ext_sales_price as ext_price,
+ from item, (select ws_ext_sales_price as ext_price,
ws_sold_date_sk as sold_date_sk,
ws_item_sk as sold_item_sk,
- ws_sold_time_sk as time_sk
+ ws_sold_time_sk as time_sk
from web_sales,date_dim
where d_date_sk = ws_sold_date_sk
and d_moy=12
@@ -3727,7 +3730,7 @@ join date_dim d3 on (cs_ship_date_sk = d3.d_date_sk)
left outer join promotion on (cs_promo_sk=p_promo_sk)
left outer join catalog_returns on (cr_item_sk = cs_item_sk and cr_order_number = cs_order_number)
where d1.d_week_seq = d2.d_week_seq
- and inv_quantity_on_hand < cs_quantity
+ and inv_quantity_on_hand < cs_quantity
and d3.d_date > d1.d_date + 5
and hd_buy_potential = '1001-5000'
and d1.d_year = 1998
@@ -3741,7 +3744,7 @@ limit 100;
select c_last_name
,c_first_name
,c_salutation
- ,c_preferred_cust_flag
+ ,c_preferred_cust_flag
,ss_ticket_number
,cnt from
(select ss_ticket_number
@@ -3749,13 +3752,13 @@ select c_last_name
,count(*) cnt
from store_sales,date_dim,store,household_demographics
where store_sales.ss_sold_date_sk = date_dim.d_date_sk
- and store_sales.ss_store_sk = store.s_store_sk
+ and store_sales.ss_store_sk = store.s_store_sk
and store_sales.ss_hdemo_sk = household_demographics.hd_demo_sk
- and date_dim.d_dom between 1 and 2
+ and date_dim.d_dom between 1 and 2
and (household_demographics.hd_buy_potential = '1001-5000' or
household_demographics.hd_buy_potential = '5001-10000')
and household_demographics.hd_vehicle_count > 0
- and case when household_demographics.hd_vehicle_count > 0 then
+ and case when household_demographics.hd_vehicle_count > 0 then
household_demographics.hd_dep_count/ household_demographics.hd_vehicle_count else null end > 1
and date_dim.d_year in (2000,2000+1,2000+2)
and store.s_county in ('Williamson County','Williamson County','Williamson County','Williamson County')
@@ -3801,7 +3804,7 @@ with year_total as (
,c_last_name
,d_year
)
- select
+ select
t_s_secyear.customer_id, t_s_secyear.customer_first_name, t_s_secyear.customer_last_name
from year_total t_s_firstyear
,year_total t_s_secyear
@@ -3844,7 +3847,7 @@ WITH all_sales AS (
,cs_ext_sales_price - COALESCE(cr_return_amount,0.0) AS sales_amt
FROM catalog_sales JOIN item ON i_item_sk=cs_item_sk
JOIN date_dim ON d_date_sk=cs_sold_date_sk
- LEFT JOIN catalog_returns ON (cs_order_number=cr_order_number
+ LEFT JOIN catalog_returns ON (cs_order_number=cr_order_number
AND cs_item_sk=cr_item_sk)
WHERE i_category='Sports'
UNION
@@ -3857,7 +3860,7 @@ WITH all_sales AS (
,ss_ext_sales_price - COALESCE(sr_return_amt,0.0) AS sales_amt
FROM store_sales JOIN item ON i_item_sk=ss_item_sk
JOIN date_dim ON d_date_sk=ss_sold_date_sk
- LEFT JOIN store_returns ON (ss_ticket_number=sr_ticket_number
+ LEFT JOIN store_returns ON (ss_ticket_number=sr_ticket_number
AND ss_item_sk=sr_item_sk)
WHERE i_category='Sports'
UNION
@@ -3870,7 +3873,7 @@ WITH all_sales AS (
,ws_ext_sales_price - COALESCE(wr_return_amt,0.0) AS sales_amt
FROM web_sales JOIN item ON i_item_sk=ws_item_sk
JOIN date_dim ON d_date_sk=ws_sold_date_sk
- LEFT JOIN web_returns ON (ws_order_number=wr_order_number
+ LEFT JOIN web_returns ON (ws_order_number=wr_order_number
AND ws_item_sk=wr_item_sk)
WHERE i_category='Sports') sales_detail
GROUP BY d_year, i_brand_id, i_class_id, i_category_id, i_manufact_id)
@@ -3929,8 +3932,8 @@ with ss as
date_dim,
store
where ss_sold_date_sk = d_date_sk
- and d_date between cast('2000-08-10' as date)
- and (cast('2000-08-10' as date) + interval '30 days')
+ and d_date between cast('2000-08-10' as date)
+ and (cast('2000-08-10' as date) + interval '30 days')
and ss_store_sk = s_store_sk
group by s_store_sk)
,
@@ -3945,7 +3948,7 @@ with ss as
and d_date between cast('2000-08-10' as date)
and (cast('2000-08-10' as date) + interval '30 days')
and sr_store_sk = s_store_sk
- group by s_store_sk),
+ group by s_store_sk),
cs as
(select cs_call_center_sk,
sum(cs_ext_sales_price) as sales,
@@ -3955,8 +3958,8 @@ with ss as
where cs_sold_date_sk = d_date_sk
and d_date between cast('2000-08-10' as date)
and (cast('2000-08-10' as date) + interval '30 days')
- group by cs_call_center_sk
- ),
+ group by cs_call_center_sk
+ ),
cr as
(select cr_call_center_sk,
sum(cr_return_amount) as returns,
@@ -3967,7 +3970,7 @@ with ss as
and d_date between cast('2000-08-10' as date)
and (cast('2000-08-10' as date) + interval '30 days')
group by cr_call_center_sk
- ),
+ ),
ws as
( select wp_web_page_sk,
sum(ws_ext_sales_price) as sales,
@@ -3979,7 +3982,7 @@ with ss as
and d_date between cast('2000-08-10' as date)
and (cast('2000-08-10' as date) + interval '30 days')
and ws_web_page_sk = wp_web_page_sk
- group by wp_web_page_sk),
+ group by wp_web_page_sk),
wr as
(select wp_web_page_sk,
sum(wr_return_amt) as returns,
@@ -3997,7 +4000,7 @@ with ss as
, sum(sales) as sales
, sum(returns) as returns
, sum(profit) as profit
- from
+ from
(select 'store channel' as channel
, ss.s_store_sk as id
, sales
@@ -4065,7 +4068,7 @@ ss as
where sr_ticket_number is null
group by d_year, ss_item_sk, ss_customer_sk
)
- select
+ select
ss_customer_sk,
round(ss_qty/(coalesce(ws_qty,0)+coalesce(cs_qty,0)),2) ratio,
ss_qty store_qty, ss_wc store_wholesale_cost, ss_sp store_sales_price,
@@ -4076,7 +4079,7 @@ from ss
left join ws on (ws_sold_year=ss_sold_year and ws_item_sk=ss_item_sk and ws_customer_sk=ss_customer_sk)
left join cs on (cs_sold_year=ss_sold_year and cs_item_sk=ss_item_sk and cs_customer_sk=ss_customer_sk)
where (coalesce(ws_qty,0)>0 or coalesce(cs_qty, 0)>0) and ss_sold_year=1998
-order by
+order by
ss_customer_sk,
ss_qty desc, ss_wc desc, ss_sp desc,
other_chan_qty,
@@ -4087,7 +4090,7 @@ limit 100;
-- end query 78 in stream 0 using template query78.tpl
-- start query 79 in stream 0 using template query79.tpl
-select
+select
c_last_name,c_first_name,substr(s_city,1,30),ss_ticket_number,amt,profit
from
(select ss_ticket_number
@@ -4097,11 +4100,11 @@ select
,sum(ss_net_profit) profit
from store_sales,date_dim,store,household_demographics
where store_sales.ss_sold_date_sk = date_dim.d_date_sk
- and store_sales.ss_store_sk = store.s_store_sk
+ and store_sales.ss_store_sk = store.s_store_sk
and store_sales.ss_hdemo_sk = household_demographics.hd_demo_sk
and (household_demographics.hd_dep_count = 7 or household_demographics.hd_vehicle_count > -1)
and date_dim.d_dow = 1
- and date_dim.d_year in (2000,2000+1,2000+2)
+ and date_dim.d_year in (2000,2000+1,2000+2)
and store.s_number_employees between 200 and 295
group by ss_ticket_number,ss_customer_sk,ss_addr_sk,store.s_city) ms,customer
where ss_customer_sk = c_customer_sk
@@ -4122,7 +4125,7 @@ with ssr as
item,
promotion
where ss_sold_date_sk = d_date_sk
- and d_date between cast('2002-08-14' as date)
+ and d_date between cast('2002-08-14' as date)
and (cast('2002-08-14' as date) + interval '30 days')
and ss_store_sk = s_store_sk
and ss_item_sk = i_item_sk
@@ -4177,7 +4180,7 @@ group by web_site_id)
, sum(sales) as sales
, sum(returns) as returns
, sum(profit) as profit
- from
+ from
(select 'store channel' as channel
, 'store' || store_id as id
, sales
@@ -4208,14 +4211,14 @@ group by web_site_id)
-- start query 81 in stream 0 using template query81.tpl
with customer_total_return as
(select cr_returning_customer_sk as ctr_customer_sk
- ,ca_state as ctr_state,
+ ,ca_state as ctr_state,
sum(cr_return_amt_inc_tax) as ctr_total_return
from catalog_returns
,date_dim
,customer_address
- where cr_returned_date_sk = d_date_sk
+ where cr_returned_date_sk = d_date_sk
and d_year =2001
- and cr_returning_addr_sk = ca_address_sk
+ and cr_returning_addr_sk = ca_address_sk
group by cr_returning_customer_sk
,ca_state )
select c_customer_id,c_salutation,c_first_name,c_last_name,ca_street_number,ca_street_name
@@ -4225,7 +4228,7 @@ with customer_total_return as
,customer_address
,customer
where ctr1.ctr_total_return > (select avg(ctr_total_return)*1.2
- from customer_total_return ctr2
+ from customer_total_return ctr2
where ctr1.ctr_state = ctr2.ctr_state)
and ca_address_sk = c_current_addr_sk
and ca_state = 'TN'
@@ -4261,10 +4264,10 @@ with sr_items as
item,
date_dim
where sr_item_sk = i_item_sk
- and d_date in
+ and d_date in
(select d_date
from date_dim
- where d_week_seq in
+ where d_week_seq in
(select d_week_seq
from date_dim
where d_date in ('2001-07-13','2001-09-10','2001-11-16')))
@@ -4277,10 +4280,10 @@ with sr_items as
item,
date_dim
where cr_item_sk = i_item_sk
- and d_date in
+ and d_date in
(select d_date
from date_dim
- where d_week_seq in
+ where d_week_seq in
(select d_week_seq
from date_dim
where d_date in ('2001-07-13','2001-09-10','2001-11-16')))
@@ -4293,10 +4296,10 @@ with sr_items as
item,
date_dim
where wr_item_sk = i_item_sk
- and d_date in
+ and d_date in
(select d_date
from date_dim
- where d_week_seq in
+ where d_week_seq in
(select d_week_seq
from date_dim
where d_date in ('2001-07-13','2001-09-10','2001-11-16')))
@@ -4314,7 +4317,7 @@ with sr_items as
,cr_items
,wr_items
where sr_items.item_id=cr_items.item_id
- and sr_items.item_id=wr_items.item_id
+ and sr_items.item_id=wr_items.item_id
order by sr_items.item_id
,sr_item_qty
limit 100;
@@ -4347,12 +4350,12 @@ select substr(r_reason_desc,1,20)
,avg(wr_refunded_cash)
,avg(wr_fee)
from web_sales, web_returns, web_page, customer_demographics cd1,
- customer_demographics cd2, customer_address, date_dim, reason
+ customer_demographics cd2, customer_address, date_dim, reason
where ws_web_page_sk = wp_web_page_sk
and ws_item_sk = wr_item_sk
and ws_order_number = wr_order_number
and ws_sold_date_sk = d_date_sk and d_year = 1998
- and cd1.cd_demo_sk = wr_refunded_cdemo_sk
+ and cd1.cd_demo_sk = wr_refunded_cdemo_sk
and cd2.cd_demo_sk = wr_returning_cdemo_sk
and ca_address_sk = wr_refunded_addr_sk
and r_reason_sk = wr_reason_sk
@@ -4364,7 +4367,7 @@ select substr(r_reason_desc,1,20)
cd1.cd_marital_status = cd2.cd_marital_status
and
cd1.cd_education_status = 'Primary'
- and
+ and
cd1.cd_education_status = cd2.cd_education_status
and
ws_sales_price between 100.00 and 150.00
@@ -4375,7 +4378,7 @@ select substr(r_reason_desc,1,20)
and
cd1.cd_marital_status = cd2.cd_marital_status
and
- cd1.cd_education_status = 'College'
+ cd1.cd_education_status = 'College'
and
cd1.cd_education_status = cd2.cd_education_status
and
@@ -4400,21 +4403,21 @@ select substr(r_reason_desc,1,20)
ca_country = 'United States'
and
ca_state in ('NC', 'TX', 'IA')
- and ws_net_profit between 100 and 200
+ and ws_net_profit between 100 and 200
)
or
(
ca_country = 'United States'
and
ca_state in ('WI', 'WV', 'GA')
- and ws_net_profit between 150 and 300
+ and ws_net_profit between 150 and 300
)
or
(
ca_country = 'United States'
and
ca_state in ('OK', 'VA', 'KY')
- and ws_net_profit between 50 and 250
+ and ws_net_profit between 50 and 250
)
)
group by r_reason_desc
@@ -4426,14 +4429,15 @@ limit 100;
-- end query 85 in stream 0 using template query85.tpl
-- start query 86 in stream 0 using template query86.tpl
-select
+select *
+from (select
sum(ws_net_paid) as total_sum
,i_category
,i_class
,grouping(i_category)+grouping(i_class) as lochierarchy
,rank() over (
partition by grouping(i_category)+grouping(i_class),
- case when grouping(i_class) = 0 then i_category end
+ case when grouping(i_class) = 0 then i_category end
order by sum(ws_net_paid) desc) as rank_within_parent
from
web_sales
@@ -4443,7 +4447,7 @@ select
d1.d_month_seq between 1186 and 1186+11
and d1.d_date_sk = ws_sold_date_sk
and i_item_sk = ws_item_sk
- group by rollup(i_category,i_class)
+ group by rollup(i_category,i_class)) as sub
order by
lochierarchy desc,
case when lochierarchy = 0 then i_category end,
@@ -4452,7 +4456,7 @@ select
-- end query 86 in stream 0 using template query86.tpl
-- start query 87 in stream 0 using template query87.tpl
-select count(*)
+select count(*)
from ((select distinct c_last_name, c_first_name, d_date
from store_sales, date_dim, customer
where store_sales.ss_sold_date_sk = date_dim.d_date_sk
@@ -4479,27 +4483,27 @@ select *
from
(select count(*) h8_30_to_9
from store_sales, household_demographics , time_dim, store
- where ss_sold_time_sk = time_dim.t_time_sk
- and ss_hdemo_sk = household_demographics.hd_demo_sk
+ where ss_sold_time_sk = time_dim.t_time_sk
+ and ss_hdemo_sk = household_demographics.hd_demo_sk
and ss_store_sk = s_store_sk
and time_dim.t_hour = 8
and time_dim.t_minute >= 30
and ((household_demographics.hd_dep_count = 0 and household_demographics.hd_vehicle_count<=0+2) or
(household_demographics.hd_dep_count = -1 and household_demographics.hd_vehicle_count<=-1+2) or
- (household_demographics.hd_dep_count = 3 and household_demographics.hd_vehicle_count<=3+2))
+ (household_demographics.hd_dep_count = 3 and household_demographics.hd_vehicle_count<=3+2))
and store.s_store_name = 'ese') s1,
- (select count(*) h9_to_9_30
+ (select count(*) h9_to_9_30
from store_sales, household_demographics , time_dim, store
where ss_sold_time_sk = time_dim.t_time_sk
and ss_hdemo_sk = household_demographics.hd_demo_sk
- and ss_store_sk = s_store_sk
- and time_dim.t_hour = 9
+ and ss_store_sk = s_store_sk
+ and time_dim.t_hour = 9
and time_dim.t_minute < 30
and ((household_demographics.hd_dep_count = 0 and household_demographics.hd_vehicle_count<=0+2) or
(household_demographics.hd_dep_count = -1 and household_demographics.hd_vehicle_count<=-1+2) or
(household_demographics.hd_dep_count = 3 and household_demographics.hd_vehicle_count<=3+2))
and store.s_store_name = 'ese') s2,
- (select count(*) h9_30_to_10
+ (select count(*) h9_30_to_10
from store_sales, household_demographics , time_dim, store
where ss_sold_time_sk = time_dim.t_time_sk
and ss_hdemo_sk = household_demographics.hd_demo_sk
@@ -4515,7 +4519,7 @@ from
where ss_sold_time_sk = time_dim.t_time_sk
and ss_hdemo_sk = household_demographics.hd_demo_sk
and ss_store_sk = s_store_sk
- and time_dim.t_hour = 10
+ and time_dim.t_hour = 10
and time_dim.t_minute < 30
and ((household_demographics.hd_dep_count = 0 and household_demographics.hd_vehicle_count<=0+2) or
(household_demographics.hd_dep_count = -1 and household_demographics.hd_vehicle_count<=-1+2) or
@@ -4526,7 +4530,7 @@ from
where ss_sold_time_sk = time_dim.t_time_sk
and ss_hdemo_sk = household_demographics.hd_demo_sk
and ss_store_sk = s_store_sk
- and time_dim.t_hour = 10
+ and time_dim.t_hour = 10
and time_dim.t_minute >= 30
and ((household_demographics.hd_dep_count = 0 and household_demographics.hd_vehicle_count<=0+2) or
(household_demographics.hd_dep_count = -1 and household_demographics.hd_vehicle_count<=-1+2) or
@@ -4536,7 +4540,7 @@ from
from store_sales, household_demographics , time_dim, store
where ss_sold_time_sk = time_dim.t_time_sk
and ss_hdemo_sk = household_demographics.hd_demo_sk
- and ss_store_sk = s_store_sk
+ and ss_store_sk = s_store_sk
and time_dim.t_hour = 11
and time_dim.t_minute < 30
and ((household_demographics.hd_dep_count = 0 and household_demographics.hd_vehicle_count<=0+2) or
@@ -4587,7 +4591,7 @@ where ss_item_sk = i_item_sk and
i_class in ('history','school-uniforms','audio')
)
or (i_category in ('Men','Sports','Shoes') and
- i_class in ('pants','tennis','womens')
+ i_class in ('pants','tennis','womens')
))
group by i_category, i_class, i_brand,
s_store_name, s_company_name, d_moy) tmp1
@@ -4619,7 +4623,7 @@ select cast(amc as decimal(15,4))/cast(pmc as decimal(15,4)) am_pm_ratio
-- end query 90 in stream 0 using template query90.tpl
-- start query 91 in stream 0 using template query91.tpl
-select
+select
cc_call_center_id Call_Center,
cc_name Call_Center_Name,
cc_manager Manager,
@@ -4639,7 +4643,7 @@ and cr_returning_customer_sk= c_customer_sk
and cd_demo_sk = c_current_cdemo_sk
and hd_demo_sk = c_current_hdemo_sk
and ca_address_sk = c_current_addr_sk
-and d_year = 2000
+and d_year = 2000
and d_moy = 12
and ( (cd_marital_status = 'M' and cd_education_status = 'Unknown')
or(cd_marital_status = 'W' and cd_education_status = 'Advanced Degree'))
@@ -4650,31 +4654,31 @@ order by sum(cr_net_loss) desc;
-- end query 91 in stream 0 using template query91.tpl
-- start query 92 in stream 0 using template query92.tpl
-select
- sum(ws_ext_discount_amt) as "Excess Discount Amount"
-from
- web_sales
- ,item
+select
+ sum(ws_ext_discount_amt) as "Excess Discount Amount"
+from
+ web_sales
+ ,item
,date_dim
where
i_manufact_id = 714
-and i_item_sk = ws_item_sk
-and d_date between '2000-02-01' and
+and i_item_sk = ws_item_sk
+and d_date between '2000-02-01' and
(cast('2000-02-01' as date) + interval '90 days')
-and d_date_sk = ws_sold_date_sk
-and ws_ext_discount_amt
- > (
- SELECT
- 1.3 * avg(ws_ext_discount_amt)
- FROM
- web_sales
+and d_date_sk = ws_sold_date_sk
+and ws_ext_discount_amt
+ > (
+ SELECT
+ 1.3 * avg(ws_ext_discount_amt)
+ FROM
+ web_sales
,date_dim
- WHERE
- ws_item_sk = i_item_sk
+ WHERE
+ ws_item_sk = i_item_sk
and d_date between '2000-02-01' and
(cast('2000-02-01' as date) + interval '90 days')
- and d_date_sk = ws_sold_date_sk
- )
+ and d_date_sk = ws_sold_date_sk
+ )
order by sum(ws_ext_discount_amt)
limit 100;
@@ -4698,7 +4702,7 @@ limit 100;
-- end query 93 in stream 0 using template query93.tpl
-- start query 94 in stream 0 using template query94.tpl
-select
+select
count(distinct ws_order_number) as "order count"
,sum(ws_ext_ship_cost) as "total shipping cost"
,sum(ws_net_profit) as "total net profit"
@@ -4708,7 +4712,7 @@ from
,customer_address
,web_site
where
- d_date between '2002-5-01' and
+ d_date between '2002-5-01' and
(cast('2002-5-01' as date) + interval '60 days')
and ws1.ws_ship_date_sk = d_date_sk
and ws1.ws_ship_addr_sk = ca_address_sk
@@ -4732,7 +4736,7 @@ with ws_wh as
from web_sales ws1,web_sales ws2
where ws1.ws_order_number = ws2.ws_order_number
and ws1.ws_warehouse_sk <> ws2.ws_warehouse_sk)
- select
+ select
count(distinct ws_order_number) as "order count"
,sum(ws_ext_ship_cost) as "total shipping cost"
,sum(ws_net_profit) as "total net profit"
@@ -4742,7 +4746,7 @@ from
,customer_address
,web_site
where
- d_date between '2001-4-01' and
+ d_date between '2001-4-01' and
(cast('2001-4-01' as date) + interval '60 days')
and ws1.ws_ship_date_sk = d_date_sk
and ws1.ws_ship_addr_sk = ca_address_sk
@@ -4759,12 +4763,12 @@ limit 100;
-- end query 95 in stream 0 using template query95.tpl
-- start query 96 in stream 0 using template query96.tpl
-select count(*)
+select count(*)
from store_sales
- ,household_demographics
+ ,household_demographics
,time_dim, store
-where ss_sold_time_sk = time_dim.t_time_sk
- and ss_hdemo_sk = household_demographics.hd_demo_sk
+where ss_sold_time_sk = time_dim.t_time_sk
+ and ss_hdemo_sk = household_demographics.hd_demo_sk
and ss_store_sk = s_store_sk
and time_dim.t_hour = 8
and time_dim.t_minute >= 30
@@ -4801,30 +4805,30 @@ limit 100;
-- end query 97 in stream 0 using template query97.tpl
-- start query 98 in stream 0 using template query98.tpl
select i_item_id
- ,i_item_desc
- ,i_category
- ,i_class
+ ,i_item_desc
+ ,i_category
+ ,i_class
,i_current_price
- ,sum(ss_ext_sales_price) as itemrevenue
+ ,sum(ss_ext_sales_price) as itemrevenue
,sum(ss_ext_sales_price)*100/sum(sum(ss_ext_sales_price)) over
(partition by i_class) as revenueratio
-from
+from
store_sales
- ,item
+ ,item
,date_dim
-where
- ss_item_sk = i_item_sk
+where
+ ss_item_sk = i_item_sk
and i_category in ('Men', 'Sports', 'Jewelry')
and ss_sold_date_sk = d_date_sk
- and d_date between cast('1999-02-05' as date)
+ and d_date between cast('1999-02-05' as date)
and (cast('1999-02-05' as date) + interval '60 days')
-group by
+group by
i_item_id
- ,i_item_desc
+ ,i_item_desc
,i_category
,i_class
,i_current_price
-order by
+order by
i_category
,i_class
,i_item_id
@@ -4833,18 +4837,18 @@ order by
-- end query 98 in stream 0 using template query98.tpl
-- start query 99 in stream 0 using template query99.tpl
-select
+select
substr(w_warehouse_name,1,20)
,sm_type
,cc_name
- ,sum(case when (cs_ship_date_sk - cs_sold_date_sk <= 30 ) then 1 else 0 end) as "30 days"
- ,sum(case when (cs_ship_date_sk - cs_sold_date_sk > 30) and
- (cs_ship_date_sk - cs_sold_date_sk <= 60) then 1 else 0 end ) as "31-60 days"
- ,sum(case when (cs_ship_date_sk - cs_sold_date_sk > 60) and
- (cs_ship_date_sk - cs_sold_date_sk <= 90) then 1 else 0 end) as "61-90 days"
+ ,sum(case when (cs_ship_date_sk - cs_sold_date_sk <= 30 ) then 1 else 0 end) as "30 days"
+ ,sum(case when (cs_ship_date_sk - cs_sold_date_sk > 30) and
+ (cs_ship_date_sk - cs_sold_date_sk <= 60) then 1 else 0 end ) as "31-60 days"
+ ,sum(case when (cs_ship_date_sk - cs_sold_date_sk > 60) and
+ (cs_ship_date_sk - cs_sold_date_sk <= 90) then 1 else 0 end) as "61-90 days"
,sum(case when (cs_ship_date_sk - cs_sold_date_sk > 90) and
- (cs_ship_date_sk - cs_sold_date_sk <= 120) then 1 else 0 end) as "91-120 days"
- ,sum(case when (cs_ship_date_sk - cs_sold_date_sk > 120) then 1 else 0 end) as ">120 days"
+ (cs_ship_date_sk - cs_sold_date_sk <= 120) then 1 else 0 end) as "91-120 days"
+ ,sum(case when (cs_ship_date_sk - cs_sold_date_sk > 120) then 1 else 0 end) as ">120 days"
from
catalog_sales
,warehouse
@@ -4865,5 +4869,3 @@ order by substr(w_warehouse_name,1,20)
,sm_type
,cc_name
limit 100;
-
--- end query 99 in stream 0 using template query99.tpl
diff --git a/tests/test_cases.py b/tests/test_cases.py
index a6ebba8..0d23215 100644
--- a/tests/test_cases.py
+++ b/tests/test_cases.py
@@ -507,7 +507,8 @@ def stress_test(node):
with open("tests/query_tpcds.sql",'r') as f:
sql = f.read()
commands = sql.split(';')
- for i, cmd in enumerate(sql.split(';')):
+ for i, cmd in enumerate(commands):
+ commands[i] = cmd.replace('%','%%')
if (len(cmd.strip()) == 0):
del commands[i]
@@ -530,5 +531,5 @@ def stress_test(node):
finally:
aq.close()
conn.close()
- if len(timeout_list) > 0:
- print 'It was pg_query_state timeouts(10s) on queries: ', timeout_list
+ if len(timeout_list) > 0:
+ print 'It was pg_query_state timeouts(10s) on queries: ', timeout_list
From 7e81aafdbbf10fdd17bf89749e069b4c52c4aed3 Mon Sep 17 00:00:00 2001
From: Alexey Kondratov <kondratov.aleksey@gmail.com>
Date: Fri, 25 Oct 2019 14:31:57 +0300
Subject: [PATCH 5/5] Remove extra linux-headers
---
Dockerfile.tmpl | 2 +-
1 file changed, 1 insertion(+), 1 deletion(-)
diff --git a/Dockerfile.tmpl b/Dockerfile.tmpl
index 86e3fb5..3cf4b5b 100644
--- a/Dockerfile.tmpl
+++ b/Dockerfile.tmpl
@@ -4,7 +4,7 @@ FROM postgres:${PG_VERSION}-alpine
RUN apk add --no-cache \
openssl curl \
perl perl-ipc-run \
- make musl-dev gcc bison flex coreutils linux-headers git\
+ make musl-dev gcc bison flex coreutils git\
zlib-dev libedit-dev \
clang clang-analyzer linux-headers \
python2 python2-dev py2-virtualenv;