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Filter DML Events Using SQL Expressions

This document introduces how to filter binlog events using SQL expressions when you use DM to perform continuous incremental data replication. For the detailed replication instruction, refer to the following documents:

When performing incremental data replication, you can use the Binlog Event Filter to filter certain types of binlog events. For example, you can choose not to replicate DELETE events to the downstream for the purposes like archiving and auditing. However, the Binlog Event Filter cannot determine whether to filter the DELETE event of a row that requires finer granularity.

To address the issue, since v2.0.5, DM supports using binlog value filter in incremental data replication to filter data. Among the DM-supported and ROW-formatted binlog, the binlog events carry values of all columns, and you can configure SQL expressions based on these values. If the expression calculates a row change as TRUE, DM does not replicate this row change to the downstream.

Similar to Binlog Event Filter, you need to configure binlog value filter in the task configuration file. For details, see the following configuration example. For the advanced task configuration and the description, refer to DM advanced task configuration file.

name: test
task-mode: all

mysql-instances:
  - source-id: "mysql-replica-01"
    expression-filters: ["even_c"]

expression-filter:
  even_c:
    schema: "expr_filter"
    table: "tbl"
    insert-value-expr: "c % 2 = 0"

In the above configuration example, the even_c rule is configured and referenced by the data source mysql-replica-01. According to this rule, for the tb1 table in the expr_filter schema, when an even number is inserted into the c column (c % 2 = 0), this insert statement is not replicated to the downstream. The following example shows the effect of this rule.

Incrementally insert the following data in the upstream data source:

INSERT INTO tbl(id, c) VALUES (1, 1), (2, 2), (3, 3), (4, 4);

Then query the tb1 table on downstream. You can see that only the rows with odd numbers on c are replicated.

MySQL [test]> select * from tbl;
+------+------+
| id   | c    |
+------+------+
|    1 |    1 |
|    3 |    3 |
+------+------+
2 rows in set (0.001 sec)

Configuration parameters and description

  • schema: The name of the upstream schema to match. Wildcard matching or regular matching is not supported.
  • table: The name of the upstream table to match. Wildcard matching or regular matching is not supported.
  • insert-value-expr: Configures an expression that takes effect on values carried by the INSERT type binlog events (WRITE_ROWS_EVENT). You cannot use this expression together with update-old-value-expr, update-new-value-expr or delete-value-expr in the same configuration item.
  • update-old-value-expr: Configures an expression that takes effect on the old values carried by the UPDATE type binlog events (UPDATE_ROWS_EVENT). You cannot use this expression together with insert-value-expr or delete-value-expr in the same configuration item.
  • update-new-value-expr: Configures an expression that takes effect on the new values carried by the UPDATE type binlog events (UPDATE_ROWS_EVENT). You cannot use this expression together with insert-value-expr or delete-value-expr in the same configuration item.
  • delete-value-expr: Configures an expression that takes effect on values carried by the DELETE type binlog events (DELETE_ROWS_EVENT). You cannot use this expression together with insert-value-expr, update-old-value-expr or update-new-value-expr.

You can use the SQL expression on one column or on multiple columns. You can also use the SQL functions supported by TiDB, such as c % 2 = 0, a*a + b*b = c*c, and ts > NOW().

The TIMESTAMP default time zone is the time zone specified in the task configuration file. The default value is the time zone of the downstream. You can explicitly specify the time zone in a way like c_timestamp = '2021-01-01 12:34:56.5678+08:00'.

You can configure multiple filtering rules under the expression-filter configuration item. The upstream data source references the required rule in expression-filters to make it effective. When multiple rules are used, if any one of the rules are matched, the entire row change is filtered.

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