PolarDB：使用說明

建立DLM策略

以下樣本將建立一張表名為sales的分區表，該表以order_time列作為分區鍵，按時間間隔劃分分區。同時，該表存在INTERVAL和DLM兩種策略：

• INTERVAL策略：當插入的資料超過分區範圍時，將自動建立新的分區，時間間隔為1年。

• DLM策略：定義當前表僅有3個分區，當分區數量大於3時，執行DLM策略會直接將之前的分區轉存至OSS。

1. 建立sales表。

   CREATE TABLE `sales` (
     `id` int DEFAULT NULL,
     `name` varchar(20) DEFAULT NULL,
     `order_time` datetime NOT NULL,
      PRIMARY KEY (`order_time`)
   ) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4
   PARTITION BY RANGE  COLUMNS(order_time) INTERVAL(YEAR, 1)
   (PARTITION p20200101000000 VALUES LESS THAN ('2020-01-01 00:00:00') ENGINE = InnoDB,
    PARTITION p20210101000000 VALUES LESS THAN ('2021-01-01 00:00:00') ENGINE = InnoDB,
    PARTITION p20220101000000 VALUES LESS THAN ('2022-01-01 00:00:00') ENGINE = InnoDB)
   DLM ADD POLICY policy_part2part TIER TO PARTITION ENGINE=CSV STORAGE=OSS READ ONLY ON (PARTITIONS OVER 3);

   該表的DLM策略名稱稱為policy_part2part，當分區數量大於3時，會將舊的分區轉存至OSS。

2. 在mysql.dlm_policies表中查看DLM策略。

   SELECT * FROM mysql.dlm_policies\G

   執行結果如下：

   *************************** 1. row ***************************
                      Id: 2
            Table_schema: test
              Table_name: sales
             Policy_name: policy_part2part
             Policy_type: PARTITION
            Archive_type: PARTITION COUNT
            Storage_mode: READ ONLY
          Storage_engine: CSV
           Storage_media: OSS
     Storage_schema_name: NULL
      Storage_table_name: NULL
         Data_compressed: OFF
    Compressed_algorithm: NULL
                 Enabled: ENABLED
         Priority_number: 10300
   Tier_partition_number: 3
          Tier_condition: NULL
              Extra_info: null
                 Comment: NULL
   1 row in set (0.03 sec)

3. 使用proc_batch_insert預存程序向sales分區表中插入一定的測試資料，以觸發INTERVAL策略來自動建立新的分區。

   CALL proc_batch_insert(1, 3000, 'sales');

   執行結果如下，表示資料插入成功：

   Query OK, 1 row affected, 1 warning (0.99 sec)

4. 執行以下命令，查看sales表的結構資訊。

   SHOW CREATE TABLE sales \G

   執行結果如下：

   *************************** 1. row ***************************
          Table: sales
   Create Table: CREATE TABLE `sales` (
     `id` int(11) DEFAULT NULL,
     `name` varchar(20) DEFAULT NULL,
     `order_time` datetime DEFAULT NULL,
      PRIMARY KEY (`order_time`)
   ) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4 COLLATE=utf8mb4_0900_ai_ci
   /*!50500 PARTITION BY RANGE  COLUMNS(order_time) */ /*!99990 800020200 INTERVAL(YEAR, 1) */
   /*!50500 (PARTITION p20200101000000 VALUES LESS THAN ('2020-01-01 00:00:00') ENGINE = InnoDB,
    PARTITION p20210101000000 VALUES LESS THAN ('2021-01-01 00:00:00') ENGINE = InnoDB,
    PARTITION p20220101000000 VALUES LESS THAN ('2022-01-01 00:00:00') ENGINE = InnoDB,
    PARTITION _p20230101000000 VALUES LESS THAN ('2023-01-01 00:00:00') ENGINE = InnoDB,
    PARTITION _p20240101000000 VALUES LESS THAN ('2024-01-01 00:00:00') ENGINE = InnoDB,
    PARTITION _p20250101000000 VALUES LESS THAN ('2025-01-01 00:00:00') ENGINE = InnoDB,
    PARTITION _p20260101000000 VALUES LESS THAN ('2026-01-01 00:00:00') ENGINE = InnoDB,
    PARTITION _p20270101000000 VALUES LESS THAN ('2027-01-01 00:00:00') ENGINE = InnoDB,
    PARTITION _p20280101000000 VALUES LESS THAN ('2028-01-01 00:00:00') ENGINE = InnoDB) */
   1 row in set (0.03 sec)

執行DLM策略

1. 通過以下命令來執行DLM策略。

   CALL dbms_dlm.execute_all_dlm_policies();

2. 通過mysql.dlm_progress表查看DLM執行記錄。

   SELECT * FROM mysql.dlm_progress \G

   執行結果如下：

   *************************** 1. row ***************************
                     Id: 4
           Table_schema: test
             Table_name: sales
            Policy_name: policy_part2part
            Policy_type: PARTITION
         Archive_option: PARTITIONS OVER 3
         Storage_engine: CSV
          Storage_media: OSS
        Data_compressed: OFF
   Compressed_algorithm: NULL
     Archive_partitions: p20200101000000, p20210101000000, p20220101000000, _p20230101000000, _p20240101000000, _p20250101000000
          Archive_stage: ARCHIVE_COMPLETE
     Archive_percentage: 100
     Archived_file_info: null
             Start_time: 2023-09-11 18:04:39
               End_time: 2023-09-11 18:04:40
             Extra_info: null
   1 row in set (0.02 sec)

3. 執行以下命令，查看sales表結構資訊。

   SHOW CREATE TABLE sales \G

   執行結果如下：

   *************************** 1. row ***************************
          Table: sales
   Create Table: CREATE TABLE `sales` (
     `id` int(11) DEFAULT NULL,
     `name` varchar(20) DEFAULT NULL,
     `order_time` datetime DEFAULT NULL,
      PRIMARY KEY (`order_time`)
   ) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4 COLLATE=utf8mb4_0900_ai_ci CONNECTION='default_oss_server'
   /*!99990 800020205 PARTITION BY RANGE  COLUMNS(order_time) */ /*!99990 800020200 INTERVAL(YEAR, 1) */
   /*!99990 800020205 (PARTITION p20200101000000 VALUES LESS THAN ('2020-01-01 00:00:00') ENGINE = CSV,
    PARTITION p20210101000000 VALUES LESS THAN ('2021-01-01 00:00:00') ENGINE = CSV,
    PARTITION p20220101000000 VALUES LESS THAN ('2022-01-01 00:00:00') ENGINE = CSV,
    PARTITION _p20230101000000 VALUES LESS THAN ('2023-01-01 00:00:00') ENGINE = CSV,
    PARTITION _p20240101000000 VALUES LESS THAN ('2024-01-01 00:00:00') ENGINE = CSV,
    PARTITION _p20250101000000 VALUES LESS THAN ('2025-01-01 00:00:00') ENGINE = CSV,
    PARTITION _p20260101000000 VALUES LESS THAN ('2026-01-01 00:00:00') ENGINE = InnoDB,
    PARTITION _p20270101000000 VALUES LESS THAN ('2027-01-01 00:00:00') ENGINE = InnoDB,
    PARTITION _p20280101000000 VALUES LESS THAN ('2028-01-01 00:00:00') ENGINE = InnoDB) */
   1 row in set (0.03 sec)

   由查詢到的表結構資訊可以看出，sales分區表中的p20200101000000、p20210101000000、p20220101000000、_p20230101000000、_p20240101000000以及_p20250101000000分區均轉存至OSS，InnoDB引擎中僅保留了3個熱資料分區_p20260101000000、_p20270101000000和_p20280101000000。sales表變為了混合分區表，查詢混合分區表中的資料操作方法請參見查詢混合分區。