Migrate with AWS Database Migration Service (DMS)

On this page

This page has instructions for setting up AWS Database Migration Service (DMS) to migrate data to CockroachDB from an existing, publicly hosted database containing application data, such as PostgreSQL, MySQL, Oracle, or Microsoft SQL Server.

For a detailed tutorial about using AWS DMS and information about specific migration tasks, see the AWS DMS documentation site.

For any issues related to AWS DMS, aside from its interaction with CockroachDB as a migration target, contact AWS Support.

Setup

Complete the following items before starting the DMS migration:

• Configure a replication instance in AWS.

• Configure a source endpoint in AWS pointing to your source database.

• Ensure you have a secure, publicly available CockroachDB cluster running the latest v24.3 production release, and have created a SQL user that you can use for your AWS DMS target endpoint.

• Set the following session variables using ALTER ROLE ... SET {session variable}:

  ALTER ROLE {username} SET copy_from_retries_enabled = true;
  

  ALTER ROLE {username} SET copy_from_atomic_enabled = false;
  

  This prevents a potential issue when migrating especially large tables with millions of rows.

• Manually create all schema objects in the target CockroachDB cluster. If you are migrating from PostgreSQL, MySQL, Oracle, or Microsoft SQL Server, you can use the Schema Conversion Tool to convert and export your schema.

  • All tables must have an explicitly defined primary key. For more guidance, see the Migration Overview.
  • Drop all constraints per the AWS DMS best practices. You can recreate them after the full load completes. AWS DMS can create a basic schema, but does not create indexes or constraints such as foreign keys and defaults.
  • Ensure that any schema changes are also reflected on your target tables, or add transformation rules to your table mappings. If you make substantial schema changes, the AWS DMS migration can fail.

• If you are migrating to a CockroachDB Cloud cluster and plan to use replication as part of your migration strategy, you must first disable revision history for cluster backups for the migration to succeed.

  Warning:

  You will not be able to run a point-in-time restore as long as revision history for cluster backups is disabled. Once you verify that the migration succeeded, you should re-enable revision history.
  • If the output of SHOW SCHEDULES shows any backup schedules, run ALTER BACKUP SCHEDULE {schedule_id} SET WITH revision_history = 'false' for each backup schedule.
  • If the output of SHOW SCHEDULES does not show backup schedules, contact Support to disable revision history for cluster backups.

• If you are migrating to CockroachDB Standard or Advanced, enable CockroachDB log export to Amazon CloudWatch before starting the DMS migration. This makes CockroachDB logs accessible for troubleshooting. You will also need to select Enable CloudWatch logs in your DMS task settings.

Supported database technologies

As of publishing, AWS DMS supports migrations from these relational databases (for the most accurate view of what is currently supported, see Sources for AWS DMS):

• Amazon Aurora
• Amazon DocumentDB (with MongoDB compatibility)
• Amazon S3
• IBM Db2 (LUW edition only)
• MariaDB
• Microsoft Azure SQL
• Microsoft SQL Server
• MongoDB
• MySQL
• Oracle
• PostgreSQL
• SAP ASE

Best practices

• Do not issue reads while AWS DMS is running. AWS DMS runs explicit transactions, which can cause contention. If you need to issue reads, use follower reads.

• Do not run additional workloads (e.g., benchmarking) while AWS DMS is running.

• To conserve CPU, consider migrating tables in multiple replication tasks, rather than performing a full load in a single task.

• If you perform a full load, you can improve performance by defining a parallel load setting for selected columns. See Table Mappings.

Step 1. Create a target endpoint pointing to CockroachDB

1. In the AWS Console, open AWS DMS.
2. Open Endpoints in the sidebar. A list of endpoints will display, if any exist.

3. In the top-right portion of the window, select Create endpoint.

   A configuration page will open.

4. In the Endpoint type section, select Target endpoint.

5. Supply an Endpoint identifier to identify the new target endpoint.

6. In the Target engine dropdown, select PostgreSQL.

7. Under Access to endpoint database, select Provide access information manually.

   For information about where to find CockroachDB connection parameters, see Connect to a CockroachDB Cluster.

8. Enter the Server name and Port of your CockroachDB cluster.

9. Supply a User name, Password, and Database name from your CockroachDB cluster.

   Note:

   To connect to a CockroachDB Standard or Basic cluster, set the Database name to {host}.{database}. For details on how to find these parameters, see Connect to your cluster. Also set Secure Socket Layer (SSL) mode to require.
   

10. If needed, you can test the connection under Test endpoint connection (optional).

11. To create the endpoint, select Create endpoint.

Step 2. Create a database migration task

A database migration task, also known as a replication task, controls what data are moved from the source database to the target database.

Step 2.1. Task configuration

1. While in AWS DMS, select Database migration tasks in the sidebar. A list of database migration tasks will display, if any exist.

2. In the top-right portion of the window, select Create task.

   A configuration page will open.

3. Supply a Task identifier to identify the replication task.

4. Select the Replication instance and Source database endpoint you created prior to starting this tutorial.

5. For the Target database endpoint dropdown, select the CockroachDB endpoint created in the previous section.

6. Select the appropriate Migration type based on your needs.

   Warning:

   If you choose Migrate existing data and replicate ongoing changes or Replicate data changes only, you must first disable revision history for backups.

   

Step 2.2. Task settings

1. For the Editing mode radio button, keep Wizard selected.
2. To preserve the schema you manually created, select Truncate or Do nothing for the Target table preparation mode.
3. Optionally check Enable validation to compare the data in the source and target rows, and verify that the migration succeeded. You can view the results in the Table statistics for your migration task. For more information about data validation, see the AWS documentation.
4. Check the Enable CloudWatch logs option. We highly recommend this for troubleshooting potential migration issues.
5. For the Target Load, select Detailed debug.

Step 2.3. Table mappings

1. For the Editing mode radio button, keep Wizard selected.
2. Select Add new selection rule.
3. In the Schema dropdown, select Enter a schema.

4. Supply the appropriate Source name (schema name), Table name, and Action.

   Note:

   Use % as an example of a wildcard for all schemas in a PostgreSQL database. However, in MySQL, using % as a schema name imports all the databases, including the metadata/system ones, as MySQL treats schemas and databases as the same.

5. To improve full-load performance, consider defining a parallel load setting for selected columns. A parallel load splits the full-load task into multiple threads. For example:

   "parallel-load": {
      "type": "ranges",
      "columns": [
          "id"
      ],
      "boundaries": [
          [
              5000000
          ],
          [
              10000000
          ],
          ...
      ]
   }
   

   For details, see the AWS documentation.

Step 3. Verify the migration

Data should now be moving from source to target. You can analyze the Table Statistics page for information about replication.

1. In AWS DMS, open Database migration tasks in the sidebar.
2. Select the task you created in Step 2.
3. Select Table statistics below the Summary section.

If your migration succeeded, you should now:

• Re-enable revision history for cluster backups.
• Re-create any constraints that you dropped before migrating.

If your migration failed for some reason, you can check the checkbox next to the table(s) you wish to re-migrate and select Reload table data.

Optional configurations

AWS PrivateLink

If using CockroachDB Standard or Advanced, you can enable AWS PrivateLink to securely connect your AWS application with your CockroachDB Standard or Advanced cluster using a private endpoint. To configure AWS PrivateLink with CockroachDB Standard or Advanced, see Network Authorization.

BatchApplyEnabled

The BatchApplyEnabled setting can improve replication performance and is recommended for larger workloads.

1. Open the existing database migration task.
2. Choose your task, and then choose Modify.
3. From the Task settings section, switch the Editing mode from Wizard to JSON editor. Locate the BatchApplyEnabled setting and change its value to true. Information about the BatchApplyEnabled setting can be found here.

Troubleshoot common issues

• For visibility into migration problems:

  • Check the Amazon CloudWatch logs that you enabled for messages containing SQL_ERROR.

  • Check the CockroachDB SQL_EXEC logs for messages related to COPY statements and the tables you are migrating. To access CockroachDB Standard or Advanced logs, you should have configured log export to Amazon CloudWatch before beginning the DMS migration.

    Warning:

    Personally identifiable information (PII) may be exported to CloudWatch unless you redact the logs. Redacting logs may hide the data that is causing the issue, making it more difficult to troubleshoot.

• If you encounter errors like the following:

  In the Amazon CloudWatch logs:

  2022-10-21T13:24:07 [SOURCE_UNLOAD   ]W:  Value of column 'metadata' in table 'integrations.integration' was truncated to 32768 bytes, actual length: 116664 bytes  (postgres_endpoint_unload.c:1072)
  

  In the CockroachDB logs:

  could not parse JSON: unable to decode JSON: while decoding 51200 bytes at offset 51185
  

  Try selecting Full LOB mode in your task settings. If this does not resolve the error, select Limited LOB mode and gradually increase the Maximum LOB size until the error goes away. For more information about LOB (large binary object) modes, see the AWS documentation.

• The following error in the CockroachDB logs indicates that a large transaction such as an INSERT or DELETE has created more write intents than can be quickly resolved:

  a transaction has hit the intent tracking limit (kv.transaction.max_intents_bytes)
  

  This will likely cause high latency and transaction retries due to lock contention. Try raising the value of the kv.transaction_max_intents_bytes cluster setting to configure CockroachDB to use more memory for quick intent resolution. Note that this memory limit is applied per-transaction. To prevent unexpected memory usage at higher workload concurrencies, you should also have proper memory accounting.

• When using Truncate or Do nothing as a target table preparation mode, you cannot include tables with any hidden columns. You can verify which tables contain hidden columns by executing the following SQL query:

  > SELECT table_catalog, table_schema, table_name, column_name FROM information_schema.columns WHERE is_hidden = 'YES';
  

• If you are migrating from PostgreSQL, are using a STRING as a PRIMARY KEY, and have selected Enable validation in your task settings, validation can fail due to a difference in how CockroachDB handles case sensitivity in strings.

  To prevent this error, use COLLATE "C" on the relevant columns in PostgreSQL or a collation such as COLLATE "en_US" in CockroachDB.

• An AWS DMS migration can fail if the target schema has hidden columns. This includes databases with hash-sharded indexes and multi-region clusters with regional by row tables. This is because the COPY statement used by DMS is unable to process hidden columns.

  To prevent this error, set the expect_and_ignore_not_visible_columns_in_copy session variable in the DMS target endpoint configuration. Under Endpoint settings, add an AfterConnectScript setting with the value SET expect_and_ignore_not_visible_columns_in_copy=on.

  

• The following error in the CockroachDB logs indicates that AWS DMS is unable to copy into a table with a computed column:

  cannot write directly to computed column ‹"column_name"›
  

  This is expected, as PostgreSQL does not allow copying into tables with a computed column. As a workaround, drop the generated column in CockroachDB and apply a transformation in DMS to exclude the computed column. Once the full load is done, add the computed column again in CockroachDB.

• Run the following query from within the target CockroachDB cluster to identify common problems with any tables that were migrated. If problems are found, explanatory messages will be returned in the cockroach sql shell.

  > WITH
      invalid_columns
          AS (
              SELECT
                  'Table '
                  || table_schema
                  || '.'
                  || table_name
                  || ' has column '
                  || column_name
                  || ' which is hidden. Either drop the column or mark it as not hidden for DMS to work.'
                      AS fix_me
              FROM
                  information_schema.columns
              WHERE
                  is_hidden = 'YES'
                  AND table_name NOT LIKE 'awsdms_%'
          ),
      invalid_version
          AS (
              SELECT
                  'This cluster is on a version of CockroachDB which does not support AWS DMS. CockroachDB v21.2.13+ or v22.1+ is required.'
                      AS fix_me
              WHERE
                  split_part(
                      substr(
                          substring(
                              version(),
                              e'v\\d+\\.\\d+.\\d+'
                          ),
                          2
                      ),
                      '.',
                      1
                  )::INT8
                  < 22
                  AND NOT
                          (
                              split_part(
                                  substr(
                                      substring(
                                          version(),
                                          e'v\\d+\\.\\d+.\\d+'
                                      ),
                                      2
                                  ),
                                  '.',
                                  1
                              )::INT8
                              = 21
                              AND split_part(
                                      substr(
                                          substring(
                                              version(),
                                              e'v\\d+\\.\\d+.\\d+'
                                          ),
                                          2
                                      ),
                                      '.',
                                      2
                                  )::INT8
                                  = 2
                              AND split_part(
                                      substr(
                                          substring(
                                              version(),
                                              e'v\\d+\\.\\d+.\\d+'
                                          ),
                                          2
                                      ),
                                      '.',
                                      3
                                  )::INT8
                                  >= 13
                          )
          ),
      has_no_pk
          AS (
              SELECT
                  'Table '
                  || a.table_schema
                  || '.'
                  || a.table_name
                  || ' has column '
                  || a.column_name
                  || ' has no explicit PRIMARY KEY. Ensure you are not using target mode "Drop tables on target" and that this table has a PRIMARY KEY.'
                      AS fix_me
              FROM
                  information_schema.key_column_usage AS a
                  JOIN information_schema.columns AS b ON
                          a.table_schema = b.table_schema
                          AND a.table_name = b.table_name
                          AND a.column_name = b.column_name
              WHERE
                  b.is_hidden = 'YES'
                  AND a.column_name = 'rowid'
                  AND a.table_name NOT LIKE 'awsdms_%'
          )
  SELECT fix_me FROM has_no_pk
  UNION ALL SELECT fix_me FROM invalid_columns
  UNION ALL SELECT fix_me FROM invalid_version;
  

• Refer to Debugging Your AWS DMS Migrations (Part 1, Part 2, and Part 3) on the AWS Database Blog.

• If the migration is still failing, contact Support and include the following information when filing an issue:

  • Source database name.
  • CockroachDB version.
  • Source database schema.
  • CockroachDB database schema.
  • Any relevant logs (e.g., the last 100 lines preceding the AWS DMS failure).
  • Ideally, a sample dataset formatted as a database dump file or CSV.

See Also

• Migration Overview
• Schema Conversion Tool
• cockroach demo
• AWS DMS documentation
• Client connection parameters
• Third-Party Database Tools
• Learn CockroachDB SQL

Was this helpful?