Best practices for importing and exporting data

This page provides best practices for importing and exporting data with Cloud SQL. For step-by-step instructions for importing data into Cloud SQL, see Importing Data.

To export data from Cloud SQL for use in a MySQL instance that you manage, see Exporting and importing using SQL dump files or Export and import using CSV files.

Best practices for importing and exporting

The following are best practices to consider when importing and exporting data:

Use the same SQL Mode for import and export

The SQL Mode setting affects how Cloud SQL interprets SQL queries. For example, if you export from a database without Strict SQL enabled, then try to import to Cloud SQL (which enables Strict SQL by default), the import might fail. The best practice is to use the same SQL Mode on import that you used for export.

Review the SQL Mode on both the source and target databases for compatibility. Pay particular attention to the flags that enable Strict SQL mode. If Strict SQL is NOT set on your database, you will likely want to remove it in Cloud SQL. If you remove Strict SQL, you must set another flag.

To verify that your Cloud SQL instance has the desired mode set, run SELECT @@GLOBAL.sql_mode;.

Don't use Cloud Storage Requester Pays buckets

You cannot use a Cloud Storage bucket that has Requester Pays enabled for imports and exports from Cloud SQL.

Use serverless export to offload the export operation from the primary instance

For a standard export from Cloud SQL, the export is run while the database is online. When the databases being exported are smaller, the impact is likely to be minimal. However, when there are large databases, or large objects, such as BLOBs in the database, there's the possibility that the export might degrade database performance. This might impact the time it takes to perform database queries and operations against the database. Once you start an export, it is not possible to stop it if your database starts to respond slowly.

To prevent slow responses during an export, you can use serverless export. With serverless export, Cloud SQL creates a separate, temporary instance to offload the export operation. Offloading the export operation allows databases on the primary instance to continue to serve queries and perform operations at the usual performance rate. When the data export is complete, the temporary instance is automatically deleted.

Use the gcloud or REST API export functions, with the offload flag, to perform a serverless export operation.

During a serverless export operation you can run some other operations, such as instance edit, import, and failover. However, if you select delete, the export operation stops some time after you delete the instance, and it doesn't export any data.

A serverless export takes longer to do than a standard export, because it takes time to create the temporary instance. At a minimum, it takes longer than five minutes, but for larger databases, it might be longer. Consider the impact to time and performance before determining which type of export to use.

You can use serverless export on a primary instance or a read replica.

Use the correct flags when you create a SQL dump file

If you do not use the right flags when you export your data to a SQL dump file, your import might be unsuccessful. For information about creating a SQL dump file for import into Cloud SQL, see Creating a SQL dump file.

Compress data to reduce cost

Cloud SQL supports importing and exporting both compressed and uncompressed files. Compression can save significant storage space on Cloud Storage and reduce your storage costs, especially when you are exporting large instances.

When you export a SQL dump or CSV file, use a .gz file extension to compress the data. When you import a file with an extension of .gz, it is decompressed automatically.

Reduce long-running import and export processes

Imports and exports into Cloud SQL using the import functionality (with a Cloud Storage bucket) can take a long time to complete, depending on the size of the database. This can have the following impacts:

  • You cannot stop a long-running Cloud SQL instance operation.
  • You can perform only one import or export operation at a time for each instance.

You can decrease the amount of time it takes to complete each operation by using the Cloud SQL import or export functionality with smaller batches of data.

For exports, you can use serverless export to minimize the impact on database performance and allow other operations to run on your instance while an export is running.

For more tips, see Diagnosing Issues with Cloud SQL Instances.

Use InnoDB

InnoDB is the only supported storage engine for MySQL instances.

You can convert your tables from MyISAM to InnoDB by piping the output of mysqldump through a sed script as follows:

mysqldump --databases [DATABASE_NAME] \
--hex-blob --default-character-set=utf8mb4 | sed 's/ENGINE=MyISAM/ENGINE=InnoDB/g' > [DATABASE_FILE].sql

MySQL import and migration jobs containing metadata with DEFINER clause

Because a MySQL import or migration job doesn't migrate user data, sources and dump files which contain metadata defined by users with the DEFINER clause will fail to be imported or migrated as the users do not yet exist there.

To identify which DEFINER values exist in your metadata, use the following queries (or search in your dump file) and check if there are entries for either root%localhost or users that don't exist in the target instance.


To run an import or migration job from a source which includes such metadata, you can do one of the following:

  • Create the users on your target Cloud SQL instance before starting your import or migration job.
  • Update the DEFINER clause to INVOKER on your source MySQL instance or dump file before starting your import or migration job.

Verify the imported database

After an import operation is complete, connect to your database and run the appropriate database commands to make sure the contents are correct. For example, connect and list the databases, tables, and specific entries.

Known limitations

For a list of known limitations, see Issues with importing and exporting data.

Automating export operations

Although Cloud SQL doesn't provide a built-in way to automate database exports, you can build your own automation tool using several Google Cloud components. To learn more, see this tutorial.


Troubleshooting import operations

Issue Troubleshooting
The import operation is taking too long. Too many active connections can interfere with import operations.

Close unused operations. Check the CPU and memory usage of your Cloud SQL instance to make sure there are plenty of resources available. The best way to ensure maximum resources for the import is to restart the instance before beginning the operation.

A restart:

  • Closes all connections.
  • Ends any tasks that may be consuming resources.
An import operation can fail when one or more users referenced in the dump file don't exist. Before importing a dump file, all the database users who own objects or were granted permissions on objects in the dumped database must exist in the target database. If they don't, the import operation fails to recreate the objects with the original ownership or permissions.

Create the database users before importing.

An import operation fails with an error that a table doesn't exist. Tables can have foreign key dependencies on other tables, and depending on the order of operations, one or more of those tables might not yet exist during the import operation.

Things to try:

Add the following line at the start of the dump file:


Additionally, add this line at the end of the dump file:


These settings deactivate data integrity checks while the import operation is in progress, and reactivate them after the data is loaded. This doesn't affect the integrity of the data on the database, because the data was already validated during the creation of the dump file.

Troubleshooting export operations

Issue Troubleshooting
CSV export worked but SQL export failed. CSV and SQL formats do export differently. The SQL format exports the entire database, and likely takes longer to complete. The CSV format lets you define which elements of the database to include in the export.

Use CSV exports to export only what you need.

Export is taking too long. Cloud SQL does not support concurrent synchronous operations.

Use export offloading. At a high level, in export offloading, instead of issuing an export on the source instance, Cloud SQL spins up an offload instance to perform the export. Export offloading has several advantages, including increased performance on the source instance and the unblocking of administrative operations while the export is running. With export offloading, total latency can increase by the amount of time it takes to bring up the offload instance. Generally, for reasonably sized exports, latency is not significant. However, if your export is small enough, then you may notice the increase in latency.

You want exports to be automated. Cloud SQL does not provide a way to automate exports.

You could build your own automated export system using Google Cloud products such as Cloud Scheduler, Pub/Sub, and Cloud Functions, similar to this article on automating backups.

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