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Understanding Log and Apply DDL Change Log Type in IBM Data Replication

By Pavan Gilda posted Mon September 22, 2025 02:05 PM

  

In modern data replication systems, managing schema changes efficiently is crucial to maintaining data integrity and consistency across source and target databases. One effective approach provided by IBM Data Replication on Cloud Pak for Data (CP4D) is the Log and Apply DDL Change Log Type, which captures and applies Data Definition Language (DDL) changes while maintaining a detailed change log.

Log and Apply DDL change_log Type is a powerful feature that can simplify data replication and schema evolution, ensuring that your business stays ahead of the curve.

What is Log and Apply DDL?

The Log and Apply DDL method in IBM Data Replication on CP4D involves recording all schema changes—such as creating tables, adding or dropping columns, renaming tables or columns, and altering column attributes—in a dedicated change log ddl table (CHANGE_LOG_DDL). These logged DDL statements are then applied directly to the target database schema to keep it synchronized with the source. This means that any changes made to the schema of your source database are automatically replicated to your target database, ensuring data consistency and minimizing downtime.

How Does It Work in IBM Data Replication on CP4D?

  • Change Log Table Structure: The change log table mirrors the source table structure but includes additional columns like SEQUENCE (primary key), OPTYPE (operation type), TRANSACTION_ID, COMMIT_TIMESTAMP. This allows tracking of every DML operation alongside schema changes within the IBM Data Replication.

  • Capturing DDL Changes: When a DDL event occurs (e.g., ALTER TABLE ADD COLUMN), a descriptive row is inserted into the CHANGE_LOG_DDL table. For example, if a column is added, dropped, renamed, or altered, IBM Data Replication logs this action with details such as the DDL type, description, and timestamp.

  • Applying Schema Changes: After logging, the exact DDL command is executed directly on the existing target change log table. Unlike other modes, no new change log tables are created nor are existing ones renamed. This ensures seamless schema evolution with minimal disruption.

  • Handling Constraints: Primary keys, unique keys, and check constraints are not physically added or dropped on the target table; instead, their creation or removal is recorded in the CHANGE_LOG_DDL table for audit purposes within the IBM Data Replication environment.

  • Truncate Operations: Truncation is handled by renaming the old table and creating a fresh one with the same structure, accompanied by a corresponding entry in the change log, as orchestrated by IBM Data Replication on CP4D.

Example: Adding a Column Using Log and Apply DDL in IBM Data Replication on CP4D

Suppose you have a source table named test_new with columns id and name, and you want to add a new column lname of type varchar(10).

    1. Source DDL Command:

      sql ALTER TABLE test_new ADD COLUMN lname varchar(10);

    2. What Happens Internally:

A row is inserted into the CHANGE_LOG_DDL table capturing the DDL event:

sequence_id

ddl_type

ddl_description

ddl_timestamp

1

ALTER TABLE ADD COLUMN

ALTER TABLE test_new ADD COLUMN lname varchar(10)

(ddl_timestamp)

The DDL command is applied directly on the existing change log table test_new.

    3. Resulting Change Log Table Structure:

The same change log table test_new now has columns:

id

name

lname

optype

sequence

transaction_id

The primary key remains the sequence column.

    4. Additional Notes:

    • No new change log tables are created, and no renaming occurs.

    • Constraints like Primary Key, Unique Key, and Check Constraint are only logged in CHANGE_LOG_DDL and not physically enforced on the target table.

    • This approach ensures minimal disruption and maintains schema history by applying changes directly.

Benefits of Log and Apply DDL in IBM Data Replication on CP4D

  • Schema Synchronization: Ensures that schema changes on the source are accurately reflected on the target without losing historical data, leveraging IBM’s robust replication engine.

  • Auditability: Maintains a comprehensive history of all schema modifications via the CHANGE_LOG_DDL table, providing transparency and traceability.

  • Data Integrity: By applying DDL changes carefully and replicating data accordingly, it prevents inconsistencies during schema evolution.

  • Flexibility: Supports complex operations like rename, drop, and alter column by managing underlying tables and columns systematically using IBM’s robust replication engine..

Benefits of Schema Evolution History

The change_log_ddl table provides a wealth of information about schema changes, including:

  • Schema change history: A complete record of all schema changes, including the date, time, and details of each change.

  • Change tracking: Ability to track changes to specific tables, columns, and other schema objects.

  • Pattern analysis: Ability to identify patterns and trends in schema changes, helping you to optimize your database design and improve performance.

Conclusion

The Log and Apply DDL Change Log Type feature in IBM Data Replication on CP4D offers a robust mechanism for handling schema evolution in replication environments. By combining detailed logging with direct application of DDL commands, it balances transparency, control, and operational efficiency — essential for reliable data replication workflows in enterprise-grade deployments. Whether you’re an e-commerce company, a financial institution, or a healthcare provider, Log and Apply DDL Change_Log Type can help you unlock the full potential of your data.

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