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Multi-Table Transform in SeaTunnel

SeaTunnel’s transform feature supports multi-table transformations, which is especially useful when the upstream plugin outputs multiple tables. This allows you to complete all necessary transformation operations within a single transform configuration. Currently, many connectors in SeaTunnel support multi-table outputs, such as JDBCSource and MySQL-CDC. All transforms can be configured for multi-table transform as described below.

:::tip

Multi-table Transform has no limitations on Transform capabilities; any Transform configuration can be used in a multi-table Transform. The purpose of multi-table Transform is to handle multiple tables in the data stream individually and merge the Transform configurations of multiple tables into one Transform for easier management.

:::

Properties

Name	Type	Required	Default	Description
table_match_regex	String	No	.*	A regular expression to match the tables that require transformation. By default, it matches all tables. Note that this table name refers to the actual upstream table name, not plugin_output.
table_transform	List	No	-	You can use a list in table_transform to specify rules for individual tables. If a transformation rule is configured for a specific table in table_transform, the outer rules will not apply to that table. The rules in table_transform take precedence.
table_transform.table_path	String	No	-	When configuring a transformation rule for a table in table_transform, you need to specify the table path using the table_path field. The table path should include databaseName[.schemaName].tableName.

Matching Logic

Suppose we read five tables from upstream: test.abc, test.abcd, test.xyz, test.xyzxyz, and test.www. They share the same structure, each having three fields: id, name, and age.

| id | name | age |

Now, let's say we want to copy the data from these five tables using the Copy transform with the following specific requirements:

• For tables test.abc and test.abcd, we need to copy the name field to a new field name1.
• For test.xyz, we want to copy the name field to name2.
• For test.xyzxyz, we want to copy the name field to name3.
• For test.www, no changes are needed.

We can configure this as follows:

transform {
  Copy {
    plugin_input = "fake"  // Optional dataset name to read from
    plugin_output = "fake1" // Optional dataset name for output

    table_match_regex = "test.a.*" // 1. Matches tables needing transformation, here matching `test.abc` and `test.abcd`
    src_field = "name" // Source field
    dest_field = "name1" // Destination field

    table_transform = [{
      table_path = "test.xyz" // 2. Specifies the table name for transformation
      src_field = "name"  // Source field
      dest_field = "name2" // Destination field
    }, {
      table_path = "test.xyzxyz"
      src_field = "name"
      dest_field = "name3"
    }]
  }
}

Explanation

1. With the regular expression and corresponding Copy transform options, we match tables test.abc and test.abcd and copy the name field to name1.
2. Using the table_transform configuration, we specify that for table test.xyz, the name field should be copied to name2.

This allows us to handle transformations for multiple tables within a single transform configuration.

For each table, the priority of configuration is: table_transform > table_match_regex. If no rules match a table, no transformation will be applied.

Below are the transform configurations for each table:

• test.abc and test.abcd

transform {
  Copy {
    src_field = "name"
    dest_field = "name1"
  }
}

Output structure:

| id | name | age | name1 |

• test.xyz

transform {
  Copy {
    src_field = "name"
    dest_field = "name2"
  }
}

Output structure:

| id | name | age | name2 |

• test.xyzxyz

transform {
  Copy {
    src_field = "name"
    dest_field = "name3"
  }
}

Output structure:

| id | name | age | name3 |

• test.www

transform {
  // No transformation needed
}

Output structure:

| id | name | age |

In this example, we used the Copy transform, but all transforms in SeaTunnel support multi-table transformations, and you can configure them similarly within the corresponding transform block.