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. For step-by-step instructions for exporting your data, whether it is in Cloud SQL or an instance you manage, see Exporting Data.

Best practices for importing and exporting

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

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 procedure when you export 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 Exporting data.

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.

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

Cloud Storage supports a maximum single-object size up five terabytes. If you have databases larger than 5TB, the export operation to Cloud Storage will fail. In that case, you need to break down your export files into smaller segments.

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.

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.

Create Extension error. The dump file contains references to unsupported extension.

Edit the dump file to remove the references.

Error using pg_dumpall. The tool requires superuser role, and the superuser role is not supported in Cloud SQL for PostgreSQL.
The export operation times out before exporting anything, and you see the error message Could not receive data from client: Connection reset by peer. If Cloud Storage does not receive any data within a certain time frame, typically around seven minutes, the connection resets. It's possible the initial export query is taking too long to run.

Do a manual export using the pg_dump tool.

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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