[Spark load] Add spark etl cluster and cluster manager

[wyb]

1. User interface:

1.1 Spark resource management

Spark is used as an external computing resource in Doris to do ETL work. In the future, there may be other external resources that will be used in Doris, for example, MapReduce is used for ETL, Spark/GPU is used for queries, HDFS/S3 is used for external storage. We introduced resource management to manage these external resources used by Doris.

-- create spark resource
CREATE EXTERNAL RESOURCE resource_name
PROPERTIES 
(                 
  type = spark,
  spark_conf_key = spark_conf_value,
  working_dir = path,
  broker = broker_name,
  broker.property_key = property_value
)

-- drop spark resource
DROP RESOURCE resource_name

-- show resources
SHOW RESOURCES
SHOW PROC "/resources"

-- privileges
GRANT USAGE_PRIV ON RESOURCE resource_name TO user_identity
GRANT USAGE_PRIV ON RESOURCE resource_name TO ROLE role_name

REVOKE USAGE_PRIV ON RESOURCE resource_name FROM user_identity
REVOKE USAGE_PRIV ON RESOURCE resource_name FROM ROLE role_name

• CREATE EXTERNAL RESOURCE:

FOR user_name is optional. If there has, the external resource belongs to this user. If not, the external resource belongs to the system and all users are available.

PROPERTIES：

1. type: resource type. Only support spark now.
2. spark configuration: follow the standard writing of Spark configurations, refer to: https://spark.apache.org/docs/latest/configuration.html.
3. working_dir: optional, used to store ETL intermediate results in spark ETL.
4. broker: optional, used in spark ETL. The ETL intermediate results need to be read with the broker when pushed into BE.

Example:

CREATE EXTERNAL RESOURCE "spark0"
PROPERTIES 
(                                                                             
  "type" = "spark",                   
  "spark.master" = "yarn",
  "spark.submit.deployMode" = "cluster",
  "spark.jars" = "xxx.jar,yyy.jar",
  "spark.files" = "/tmp/aaa,/tmp/bbb",
  "spark.yarn.queue" = "queue0",
  "spark.executor.memory" = "1g",
  "spark.hadoop.yarn.resourcemanager.address" = "127.0.0.1:9999",
  "spark.hadoop.fs.defaultFS" = "hdfs://127.0.0.1:10000",
  "working_dir" = "hdfs://127.0.0.1:10000/tmp/doris",
  "broker" = "broker0",
  "broker.username" = "user0",
  "broker.password" = "password0"
)

• SHOW RESOURCES:
  General users can only see their own resources.
  Admin and root users can show all resources.

1.2 Create spark load job

LOAD LABEL db_name.label_name 
(
  DATA INFILE ("/tmp/file1") INTO TABLE table_name, ...
)
WITH RESOURCE resource_name
[(key1 = value1, ...)]
[PROPERTIES (key2 = value2, ... )]

Example:

LOAD LABEL example_db.test_label 
(
  DATA INFILE ("hdfs:/127.0.0.1:10000/tmp/file1") INTO TABLE example_table
)
WITH RESOURCE "spark0"
(
  "spark.executor.memory" = "1g",
  "spark.files" = "/tmp/aaa,/tmp/bbb"
)
PROPERTIES ("timeout" = "3600")

The spark configuartions in load stmt can override the existing configuration in the resource for temporary use.

#3010

[kangkaisen]

@wyb Hi, why comment the update load cluster code?

[wyb]

@wyb Hi, why comment the update load cluster code?

Because EtlClusterDesc class is used in the load job process, and is not in this pr.
I will remove the comment in the load job process pr.

[imay]

SHOW PROC "/load_etl_clusters"

why load_etl_clusters? seems load_clusters is OK.

[imay]

Should add documents for resource operations.

[morningman]

LGTM

[imay]

LGTM

[imay]

LGTM