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A Classic Bulk Load Migration is the simplest way of migrating data to CockroachDB. In this approach, you stop application traffic to the source database and migrate data to the target cluster using MOLT Fetch during a significant downtime window. Application traffic is then cut over to the target after schema finalization and data verification.
  • All source data is migrated to the target at once.
  • This approach does not utilize continuous replication.
  • Rollback is manual, but in most cases it’s simple, as the source database is preserved and write traffic begins on the target all at once. If you wish to roll back before the target has received any writes that are not present on the source database, nothing needs to be done. If you wish to roll back after the target has received writes that are not present on the source database, you must manually replicate these new rows on the source.
This approach is best for small databases (<100 GB), internal tools, dev/staging environments, and production environments that can handle business disruption. It’s a simple approach that guarantees full data consistency and is easy to execute with limited resources, but it can only be performed if your system can handle significant downtime. This page describes an example scenario. While the commands provided can be copy-and-pasted, they may need to be altered or reconsidered to suit the needs of your specific environment. Classic Bulk Load Migration flow

Example scenario

You have a small (50 GB) database that provides the data store for a web application. You want to migrate the entirety of this database to a new CockroachDB cluster. You schedule a maintenance window for Saturday from 2 AM to 6 AM, and announce it to your users several weeks in advance. The application runs on a Kubernetes cluster. Estimated system downtime: 4 hours.

Before the migration

  • Install the MOLT (Migrate Off Legacy Technology) tools.
  • Review the MOLT Fetch documentation.
  • Develop a migration plan and prepare for the migration.
  • Recommended: Perform a dry run of this full set of instructions in a development environment that closely resembles your production environment. This can help you get a realistic sense of the time and complexity it requires.
  • Announce the maintenance window to your users.
  • Understand the prerequisites and limitations of the MOLT tools:

Limitations

MOLT Fetch limitations

MOLT Verify limitations

  • MOLT Verify compares 20,000 rows at a time by default, and row values can change between batches, potentially resulting in temporary inconsistencies in data. To configure the row batch size, use the --row_batch_size flag.
  • MOLT Verify checks for collation mismatches on primary key columns. This may cause validation to fail when a STRING is used as a primary key and the source and target databases are using different collations.
  • MOLT Verify might give an error in case of schema changes on either the source or target database.
  • Geospatial types cannot yet be compared.
  • MOLT Verify only supports comparing one MySQL database to a whole CockroachDB schema (which is assumed to be public).

Step 1: Prepare the source database

In this step, you will:

Create migration user on source database

Create a dedicated migration user (for example, MIGRATION_USER) on the source database. This user is responsible for reading data from source tables during the migration. You will pass this username in the source connection string.
Grant the user privileges to select the tables you migrate and access GTID information for snapshot consistency:

Step 2: Prepare the target database

In this step, you will:

Provision a CockroachDB cluster

Use one of the following options to create and run a new CockroachDB cluster. This is your migration target.

Option 1: Create a secure cluster locally

If you have the CockroachDB binary installed locally, you can manually deploy a multi-node, self-hosted CockroachDB cluster on your local machine. Learn how to deploy a CockroachDB cluster locally.

Option 2: Create a CockroachDB Self-Hosted cluster on AWS

You can manually deploy a multi-node, self-hosted CockroachDB cluster on Amazon’s AWS EC2 platform, using AWS’s managed load-balancing service to distribute client traffic. Learn how to deploy a CockroachDB cluster on AWS.

Option 3: Create a CockroachDB Cloud cluster

CockroachDB Cloud is a fully-managed service run by Cockroach Labs, which simplifies the deployment and management of CockroachDB. Sign up for a CockroachDB Cloud account and create a cluster using trial credits.

Define the target tables

Convert the source table definitions into CockroachDB-compatible equivalents. CockroachDB supports the PostgreSQL wire protocol and is largely compatible with PostgreSQL syntax.
  • The source and target table definitions must match. Review Type mapping to understand which source types can be mapped to CockroachDB types. MySQL tables belong directly to the database specified in the connection string. A MySQL source table defined as CREATE TABLE tbl (id INT PRIMARY KEY); should map to CockroachDB’s default public schema:
  • Every table must have an explicit primary key.
    Avoid using sequential keys. To learn more about the performance issues that can result from their use, refer to the guidance on indexing with sequential keys. If a sequential key is necessary in your CockroachDB table, you must create it manually, after using MOLT Fetch to load and replicate the data.
  • Review Transformations to understand how computed columns and partitioned tables can be mapped to the target, and how target tables can be renamed.
  • By default on CockroachDB, INT is an alias for INT8, which creates 64-bit signed integers. PostgreSQL and MySQL default to 32-bit integers. Depending on your source database or application requirements, you may need to change the integer size to 4. For more information, refer to Considerations for 64-bit signed integers.

Schema Conversion Tool

The MOLT Schema Conversion Tool (SCT) converts source table definitions to CockroachDB-compatible syntax. It requires a free CockroachDB Cloud account.
  1. Upload a source .sql file to convert the syntax and identify unimplemented features and syntax incompatibilities in the table definitions.
  2. Import the converted table definitions to a CockroachDB cluster:
Syntax that cannot automatically be converted will be displayed in the Summary Report. These may include the following:
String case sensitivity
Strings are case-insensitive in MySQL and case-sensitive in CockroachDB. You may need to edit your MySQL data to get the results you expect from CockroachDB. For example, you may have been doing string comparisons in MySQL that will need to be changed to work with CockroachDB. For more information about the case sensitivity of strings in MySQL, refer to Case Sensitivity in String Searches from the MySQL documentation. For more information about CockroachDB strings, refer to STRING.
Identifier case sensitivity
Identifiers are case-sensitive in MySQL and case-insensitive in CockroachDB. When using the Schema Conversion Tool, you can either keep case sensitivity by enclosing identifiers in double quotes, or make identifiers case-insensitive by converting them to lowercase.
AUTO_INCREMENT attribute
The MySQL AUTO_INCREMENT attribute, which creates sequential column values, is not supported in CockroachDB. When using the Schema Conversion Tool, columns with AUTO_INCREMENT can be converted to use sequences, UUID values with gen_random_uuid(), or unique INT8 values using unique_rowid(). Cockroach Labs does not recommend using a sequence to define a primary key column. For more information, refer to Unique ID best practices.
Changing a column type during table definition conversion will cause MOLT Verify to identify a type mismatch during data validation. This is expected behavior.
ENUM type
MySQL ENUM types are defined in table columns. On CockroachDB, ENUM is a standalone type. When using the Schema Conversion Tool, you can either deduplicate the ENUM definitions or create a separate type for each column.
TINYINT type
TINYINT data types are not supported in CockroachDB. The Schema Conversion Tool automatically converts TINYINT columns to INT2 (SMALLINT).
Geospatial types
MySQL geometry types are not converted to CockroachDB geospatial types by the Schema Conversion Tool. They should be manually converted to the corresponding types in CockroachDB.
FIELD function
The MYSQL FIELD function is not supported in CockroachDB. Instead, you can use the array_position function, which returns the index of the first occurrence of element in the array. Example usage:
While MySQL returns 0 when the element is not found, CockroachDB returns NULL. So if you are using the ORDER BY clause in a statement with the array_position function, the caveat is that sort is applied even when the element is not found. As a workaround, you can use the COALESCE operator.

Drop constraints and indexes

To optimize data load performance, drop all non-PRIMARY KEY constraints and indexes on the target CockroachDB database before migrating:
Do not drop PRIMARY KEY constraints.
You can recreate the constraints and indexes after loading the data.

Create the SQL user

Create a SQL user in the CockroachDB cluster that has the necessary privileges. To create a user crdb_user in the default database (you will pass this username in the target connection string):
Grant database-level privileges for schema creation within the target database:
Grant permission to modify cluster settings:
Grant usage on schemas being migrated:
Grant user privileges to create tables in the migration_schema schema and internal MOLT tables like _molt_fetch_exceptions in the public CockroachDB schema:
Ensure that you are connected to the target database.
If you manually defined the target tables (which means that drop-on-target-and-recreate will not be used), grant the following privileges on the schema:
If you will be running Fetch with drop-on-target-and-recreate, and the target schema has pre-existing tables that were created by a different user, you may need to change table ownership to allow the migration user to drop those tables. Make the following alteration for each table:
Depending on the MOLT Fetch data load mode you will use, grant the necessary privileges to run either IMPORT INTO or COPY FROM on the target tables:

IMPORT INTO privileges

Grant SELECT, INSERT, and DROP (required because the table is taken offline during the IMPORT INTO) privileges on all tables being migrated:
If you plan to use cloud storage with implicit authentication for data load, grant the EXTERNALIOIMPLICITACCESS system-level privilege:

COPY FROM privileges

Grant admin privileges to the user:

Set session variable

Ensure that the statement_timeout session variable is set to 0s for the user:

Step 3: Stop application traffic

With both the source and target databases prepared for the data load, it’s time to stop application traffic to the source. At the start of the maintenance window, scale down the Kubernetes cluster to zero pods.
Application downtime begins now.It is strongly recommended that you perform a dry run of this migration in a test environment. This will allow you to practice using the MOLT tools in real time, and it will give you an accurate sense of how long application downtime might last.

Step 4: Load data into CockroachDB

In this step, you will:

Configure MOLT Fetch

The MOLT Fetch documentation includes detailed information about how to configure MOLT Fetch, and how to monitor MOLT Fetch metrics. When you run molt fetch, you can configure the following options for data load: Read through the documentation to understand how to configure your molt fetch command and its flags. Follow best practices, especially those related to security. At minimum, the molt fetch command should include the source, target, data path, and --ignore-replication-check flags:
However, depending on the needs of your migration, you may have many more flags set, and you may need to prepare some accompanying .json files.

Run MOLT Fetch

Perform the bulk load of the source data.
  1. Run the MOLT Fetch command to move the source data into CockroachDB. This example command passes the source and target connection strings as environment variables, writes intermediate files to S3 storage, and uses the truncate-if-exists table handling mode to truncate the target tables before loading data. It limits the migration to a single schema and filters for three specific tables. The data load mode defaults to IMPORT INTO. Include the --ignore-replication-check flag to skip replication checkpoint queries, which eliminates the need to configure the source database for logical replication.
  2. Check the output to observe fetch progress. A starting fetch message indicates that the task has started:
    data extraction messages are written for each table that is exported to the location in --bucket-path:
    data import messages are written for each table that is loaded into CockroachDB:
    A fetch complete message is written when the fetch task succeeds:

Continue MOLT Fetch after an interruption

If MOLT Fetch fails while loading data into CockroachDB from intermediate files, it exits with an error message, fetch ID, and continuation token for each table that failed to load on the target database.
You can use this information to continue the task from the continuation point where it was interrupted. Continuation is only possible under the following conditions:
Only one fetch ID and set of continuation tokens, each token corresponding to a table, are active at any time. See List active continuation tokens.
The following command reattempts the data load starting from a specific continuation file, but you can also use individual continuation tokens to reattempt the data load for individual tables.

Step 5: Verify the data

In this step, you will use MOLT Verify to confirm that the source and target data is consistent. This ensures that the data load was successful.

Run MOLT Verify

  1. Run the MOLT Verify command, specifying the source and target connection strings and the tables to validate.
  2. Check the output to observe verify progress. A verification in progress indicates that the task has started:
    starting verify messages are written for each specified table:
    A finished row verification message is written after each table is compared. If num_success equals num_truth_rows and the error counters (num_missing, num_mismatch, num_extraneous, and num_column_mismatch) are all 0, the table verified successfully. Any non-zero values in the error counters indicate data discrepancies that need investigation. For details on each field, refer to the MOLT Verify page.
    A verification complete message is written when the verify task succeeds:

Step 6: Finalize the target schema

Add constraints and indexes

Add any constraints or indexes that you previously removed from the CockroachDB schema to facilitate data load.
If you used the --table-handling drop-on-target-and-recreate option for data load, only PRIMARY KEY and NOT NULL constraints are preserved. You must manually recreate all other constraints and indexes.
For the appropriate SQL syntax, refer to ALTER TABLE ... ADD CONSTRAINT and CREATE INDEX. Review the best practices for creating secondary indexes on CockroachDB.

Step 7: Cut over application traffic

With the target cluster verified and finalized, it’s time to resume application traffic.

Modify application code

In the application back end, make sure that the application now directs traffic to the CockroachDB cluster. For example:

Resume application traffic

Scale up the Kubernetes deployment to the original number of replicas:
This ends downtime.

See also