[doc](update) modify the example for UPDATE usage (apache#1412)

# Versions - [x] dev - [x] 3.0 - [x] 2.1 - [x] 2.0 # Languages - [x] Chinese - [x] English # relate case PR apache/doris#44854
echo-hhj · Jan 6, 2025 · 7db70e2 · 7db70e2
1 parent bc8f803
commit 7db70e2
Show file tree

Hide file tree

Showing 8 changed files with 592 additions and 184 deletions.
diff --git a/docs/data-operate/update/unique-update.md b/docs/data-operate/update/unique-update.md
@@ -50,40 +50,91 @@ The performance of the UPDATE statement depends on the number of rows to be upda
 
 ## Example
 
-Suppose there is an order table in Doris, where the order_id is the key column, and the order status and order amount are the Value columns. The data looks as follows:
+Assuming in a financial risk control scenario, there is a transaction details table with the following structure:
 
-| order_id | order_amount | order_status |
-| -------- | ------------ | ------------ |
-| 1        | 100          | Pending      |
+```sql
+CREATE TABLE transaction_details (
+  transaction_id BIGINT NOT NULL,        -- Unique transaction ID
+  user_id BIGINT NOT NULL,               -- User ID
+  transaction_date DATE NOT NULL,        -- Transaction date
+  transaction_time DATETIME NOT NULL,    -- Transaction time
+  transaction_amount DECIMAL(18, 2),     -- Transaction amount
+  transaction_device STRING,             -- Transaction device
+  transaction_region STRING,             -- Transaction region
+  average_daily_amount DECIMAL(18, 2),   -- Average daily transaction amount over the last 3 months
+  recent_transaction_count INT,          -- Number of transactions in the last 7 days
+  has_dispute_history BOOLEAN,           -- Whether there is a dispute history
+  risk_level STRING                      -- Risk level
+)
+UNIQUE KEY(transaction_id)
+DISTRIBUTED BY HASH(transaction_id) BUCKETS 16
+PROPERTIES (
+  "replication_num" = "3",               -- Number of replicas, default is 3
+  "enable_unique_key_merge_on_write" = "true"  -- Enable MOW mode, support merge update
+);
+```
+
+The following transaction data exists:
 
 ```sql
-+----------+--------------+--------------+
-| order_id | order_amount | order_status |
-+----------+--------------+--------------+
-| 1        | 100          | Pending      |
-+----------+--------------+--------------+
-1 row in set (0.01 sec)
++----------------+---------+------------------+---------------------+--------------------+--------------------+--------------------+----------------------+--------------------------+---------------------+------------+
+| transaction_id | user_id | transaction_date | transaction_time    | transaction_amount | transaction_device | transaction_region | average_daily_amount | recent_transaction_count | has_dispute_history | risk_level |
++----------------+---------+------------------+---------------------+--------------------+--------------------+--------------------+----------------------+--------------------------+---------------------+------------+
+|           1001 |    5001 | 2024-11-24       | 2024-11-24 14:30:00 |             100.00 | iPhone 12          | New York           |               100.00 |                       10 |                   0 | NULL       |
+|           1002 |    5002 | 2024-11-24       | 2024-11-24 03:30:00 |             120.00 | iPhone 12          | New York           |               100.00 |                       15 |                   0 | NULL       |
+|           1003 |    5003 | 2024-11-24       | 2024-11-24 10:00:00 |             150.00 | Samsung S21        | Los Angeles        |               100.00 |                       30 |                   0 | NULL       |
+|           1004 |    5004 | 2024-11-24       | 2024-11-24 16:00:00 |             300.00 | MacBook Pro        | high_risk_region1  |               200.00 |                        5 |                   0 | NULL       |
+|           1005 |    5005 | 2024-11-24       | 2024-11-24 11:00:00 |            1100.00 | iPad Pro           | Chicago            |               200.00 |                       10 |                   0 | NULL       |
++----------------+---------+------------------+---------------------+--------------------+--------------------+--------------------+----------------------+--------------------------+---------------------+------------+
 ```
 
-Now, when a user clicks on the payment, the Doris system needs to update the order status of the order with ID '1' to 'To be shipped'. This requires using the UPDATE functionality.
+Update the risk level of all transactions on a daily basis according to the following risk control rules:
+1. If there is a dispute history, the risk is high.
+2. If in a high-risk region, the risk is high.
+3. If the transaction amount is abnormal (more than 5 times the daily average), the risk is high.
+4. Frequent transactions in the last 7 days:
+  a. If the number of transactions > 50, the risk is high.
+  b. If the number of transactions is between 20 and 50, the risk is medium.
+5. Transactions during non-working hours (2 AM to 4 AM), the risk is medium.
+6. The default risk is low.
 
 ```sql
-mysql> UPDATE test_order SET order_status = 'To be shipped' WHERE order_id = 1;
-Query OK, 1 row affected (0.11 sec)
-{'label':'update_20ae22daf0354fe0-b5aceeaaddc666c5', 'status':'VISIBLE', 'txnId':'33', 'queryId':'20ae22daf0354fe0-b5aceeaaddc666c5'}
+UPDATE transaction_details
+SET risk_level = CASE
+  -- Transactions with dispute history or in high-risk regions
+  WHEN has_dispute_history = TRUE THEN 'high'
+  WHEN transaction_region IN ('high_risk_region1', 'high_risk_region2') THEN 'high'
+
+  -- Abnormal transaction amount
+  WHEN transaction_amount > 5 * average_daily_amount THEN 'high'
+
+  -- High transaction frequency in the last 7 days
+  WHEN recent_transaction_count > 50 THEN 'high'
+  WHEN recent_transaction_count BETWEEN 20 AND 50 THEN 'medium'
+
+  -- Transactions during non-working hours
+  WHEN HOUR(transaction_time) BETWEEN 2 AND 4 THEN 'medium'
+
+  -- Default risk
+  ELSE 'low'
+END
+WHERE transaction_date = '2024-11-24';
 ```
 
-The updated result is as follows:
+The updated data is:
 
 ```sql
-+----------+--------------+--------------+
-| order_id | order_amount | order_status |
-+----------+--------------+--------------+
-| 1        | 100          | To be shipped|
-+----------+--------------+--------------+
-1 row in set (0.01 sec)
++----------------+---------+------------------+---------------------+--------------------+--------------------+--------------------+----------------------+--------------------------+---------------------+------------+
+| transaction_id | user_id | transaction_date | transaction_time    | transaction_amount | transaction_device | transaction_region | average_daily_amount | recent_transaction_count | has_dispute_history | risk_level |
++----------------+---------+------------------+---------------------+--------------------+--------------------+--------------------+----------------------+--------------------------+---------------------+------------+
+|           1001 |    5001 | 2024-11-24       | 2024-11-24 14:30:00 |             100.00 | iPhone 12          | New York           |               100.00 |                       10 |                   0 | low        |
+|           1002 |    5002 | 2024-11-24       | 2024-11-24 03:30:00 |             120.00 | iPhone 12          | New York           |               100.00 |                       15 |                   0 | medium     |
+|           1003 |    5003 | 2024-11-24       | 2024-11-24 10:00:00 |             150.00 | Samsung S21        | Los Angeles        |               100.00 |                       30 |                   0 | medium     |
+|           1004 |    5004 | 2024-11-24       | 2024-11-24 16:00:00 |             300.00 | MacBook Pro        | high_risk_region1  |               200.00 |                        5 |                   0 | high       |
+|           1005 |    5005 | 2024-11-24       | 2024-11-24 11:00:00 |            1100.00 | iPad Pro           | Chicago            |               200.00 |                       10 |                   0 | high       |
++----------------+---------+------------------+---------------------+--------------------+--------------------+--------------------+----------------------+--------------------------+---------------------+------------+
 ```
 
 ## More Details
 
-For more detailed syntax on data updates, please refer to the [UPDATE](../../sql-manual/sql-statements/Data-Manipulation-Statements/Manipulation/UPDATE) command manual. You can also enter `HELP UPDATE` in the MySQL client command line for more information and assistance.
+For more detailed syntax on data updates, please refer to the [UPDATE](../../sql-manual/sql-statements/Data-Manipulation-Statements/Manipulation/UPDATE) command manual. You can also enter `HELP UPDATE` in the MySQL client command line for more information and assistance.
diff --git a/...-CN/docusaurus-plugin-content-docs/current/data-operate/update/unique-update.md b/...-CN/docusaurus-plugin-content-docs/current/data-operate/update/unique-update.md
@@ -42,46 +42,97 @@ Update 语法在 Doris 中是一个同步语法，即 Update 语句执行成功
 
 ### 性能
 
-Update 语句的性能和待更新的行数以及 condition 的检索效率密切相关。
+Update 语句的性能和待更新的行数以及查询条件的检索效率密切相关。
 
 - 待更新的行数：待更新的行数越多，Update 语句的速度就会越慢。Update 更新比较合适偶发更新的场景，比如修改个别行的值。Update 并不适合大批量的修改数据。
 
-- condition 的检索效率：Update 实现原理是先将满足 condition 的行做读取处理，所以如果 condition 的检索效率高，则 Update 的速度也会快。condition 列最好能命中索引或者分区分桶裁剪，这样 Doris 就不需要扫全表，可以快速定位到需要更新的行，从而提升更新效率。强烈不推荐 condition 列中包含 value 列。
+- 查询条件的检索效率：Update 实现原理是先将满足查询条件的行做读取处理，所以如果查询条件的检索效率高，则 Update 的速度也会快。条件列最好能命中索引或者分区分桶裁剪，这样 Doris 就不需要扫全表，可以快速定位到需要更新的行，从而提升更新效率。强烈不推荐条件列中包含 value 列。
 
 ## 使用示例
 
-假设 Doris 中存在一张订单表，其中订单 id 是 Key 列，订单状态，订单金额是 Value 列。数据状态如下：
+假设在金融风控场景中，存在如下结构的交易明细表：
 
-| 订单 id | 订单金额 | 订单状态 |
-| ------ | -------- | -------- |
-| 1      | 100      | 待付款   |
+```sql
+CREATE TABLE transaction_details (
+    transaction_id BIGINT NOT NULL,        -- 唯一交易编号
+    user_id BIGINT NOT NULL,               -- 用户编号
+    transaction_date DATE NOT NULL,        -- 交易日期
+    transaction_time DATETIME NOT NULL,    -- 交易时间
+    transaction_amount DECIMAL(18, 2),     -- 交易金额
+    transaction_device STRING,             -- 交易设备
+    transaction_region STRING,             -- 交易地区
+    average_daily_amount DECIMAL(18, 2),   -- 最近3个月日均交易金额
+    recent_transaction_count INT,          -- 最近7天交易次数
+    has_dispute_history BOOLEAN,           -- 是否有拒付记录
+    risk_level STRING                      -- 风险等级
+)
+UNIQUE KEY(transaction_id)
+DISTRIBUTED BY HASH(transaction_id) BUCKETS 16
+PROPERTIES (
+    "replication_num" = "3",               -- 副本数量，默认3
+    "enable_unique_key_merge_on_write" = "true"  -- 启用MOW模式，支持合并更新
+);
+```
+
+存在如下交易数据：
 
 ```sql
-+----------+--------------+--------------+
-| order_id | order_amount | order_status |
-+----------+--------------+--------------+
-| 1        |          100 | 待付款       |
-+----------+--------------+--------------+
-1 row in set (0.01 sec)
++----------------+---------+------------------+---------------------+--------------------+--------------------+--------------------+----------------------+--------------------------+---------------------+------------+
+| transaction_id | user_id | transaction_date | transaction_time    | transaction_amount | transaction_device | transaction_region | average_daily_amount | recent_transaction_count | has_dispute_history | risk_level |
++----------------+---------+------------------+---------------------+--------------------+--------------------+--------------------+----------------------+--------------------------+---------------------+------------+
+|           1001 |    5001 | 2024-11-24       | 2024-11-24 14:30:00 |             100.00 | iPhone 12          | New York           |               100.00 |                       10 |                   0 | NULL       |
+|           1002 |    5002 | 2024-11-24       | 2024-11-24 03:30:00 |             120.00 | iPhone 12          | New York           |               100.00 |                       15 |                   0 | NULL       |
+|           1003 |    5003 | 2024-11-24       | 2024-11-24 10:00:00 |             150.00 | Samsung S21        | Los Angeles        |               100.00 |                       30 |                   0 | NULL       |
+|           1004 |    5004 | 2024-11-24       | 2024-11-24 16:00:00 |             300.00 | MacBook Pro        | high_risk_region1  |               200.00 |                        5 |                   0 | NULL       |
+|           1005 |    5005 | 2024-11-24       | 2024-11-24 11:00:00 |            1100.00 | iPad Pro           | Chicago            |               200.00 |                       10 |                   0 | NULL       |
++----------------+---------+------------------+---------------------+--------------------+--------------------+--------------------+----------------------+--------------------------+---------------------+------------+
 ```
 
-这时候，用户点击付款后，Doris 系统需要将订单 id 为 '1' 的订单状态变更为 '待发货'，就需要用到 Update 功能。
+按照如下风控规则来更新每日所有交易记录的风险等级：
+1. 有拒付记录，风险为 high。
+2. 在高风险地区，风险为 high。
+3. 交易金额异常（超过日均 5 倍），风险为 high。
+4. 最近 7 天交易频繁：
+  a. 交易次数 > 50，风险为 high。
+  b. 交易次数在 20-50 之间，风险为 medium。
+5. 非工作时间交易（凌晨 2 点到 4 点），风险为 medium。
+6. 默认风险为 low。
 
 ```sql
-mysql> UPDATE test_order SET order_status = '待发货' WHERE order_id = 1;
-Query OK, 1 row affected (0.11 sec)
-{'label':'update_20ae22daf0354fe0-b5aceeaaddc666c5', 'status':'VISIBLE', 'txnId':'33', 'queryId':'20ae22daf0354fe0-b5aceeaaddc666c5'}
+UPDATE transaction_details
+SET risk_level = CASE
+    -- 有拒付记录或在高风险地区的交易
+    WHEN has_dispute_history = TRUE THEN 'high'
+    WHEN transaction_region IN ('high_risk_region1', 'high_risk_region2') THEN 'high'
+
+    -- 突然异常交易金额
+    WHEN transaction_amount > 5 * average_daily_amount THEN 'high'
+
+    -- 最近7天交易频率很高
+    WHEN recent_transaction_count > 50 THEN 'high'
+    WHEN recent_transaction_count BETWEEN 20 AND 50 THEN 'medium'
+
+    -- 非工作时间交易
+    WHEN HOUR(transaction_time) BETWEEN 2 AND 4 THEN 'medium'
+
+    -- 默认风险
+    ELSE 'low'
+END
+WHERE transaction_date = '2024-11-24';
 ```
 
-更新后结果如下
+更新之后的数据为
 
 ```sql
-+----------+--------------+--------------+
-| order_id | order_amount | order_status |
-+----------+--------------+--------------+
-| 1        |          100 | 待发货       |
-+----------+--------------+--------------+
-1 row in set (0.01 sec)
++----------------+---------+------------------+---------------------+--------------------+--------------------+--------------------+----------------------+--------------------------+---------------------+------------+
+| transaction_id | user_id | transaction_date | transaction_time    | transaction_amount | transaction_device | transaction_region | average_daily_amount | recent_transaction_count | has_dispute_history | risk_level |
++----------------+---------+------------------+---------------------+--------------------+--------------------+--------------------+----------------------+--------------------------+---------------------+------------+
+|           1001 |    5001 | 2024-11-24       | 2024-11-24 14:30:00 |             100.00 | iPhone 12          | New York           |               100.00 |                       10 |                   0 | low        |
+|           1002 |    5002 | 2024-11-24       | 2024-11-24 03:30:00 |             120.00 | iPhone 12          | New York           |               100.00 |                       15 |                   0 | medium     |
+|           1003 |    5003 | 2024-11-24       | 2024-11-24 10:00:00 |             150.00 | Samsung S21        | Los Angeles        |               100.00 |                       30 |                   0 | medium     |
+|           1004 |    5004 | 2024-11-24       | 2024-11-24 16:00:00 |             300.00 | MacBook Pro        | high_risk_region1  |               200.00 |                        5 |                   0 | high       |
+|           1005 |    5005 | 2024-11-24       | 2024-11-24 11:00:00 |            1100.00 | iPad Pro           | Chicago            |               200.00 |                       10 |                   0 | high       |
++----------------+---------+------------------+---------------------+--------------------+--------------------+--------------------+----------------------+--------------------------+---------------------+------------+
 ```
 
 ## 更多帮助