Use Data Boost in your applications Stay organized with collections Save and categorize content based on your preferences.
Before you begin
Ensure that the principal (for example, the service account) that runs theapplication has thespanner.databases.useDataBoost Identity and Access Management (IAM)permission. For more information, seeAccess control with IAM.
APIs
For partitioned reads with Data Boost, the followingSpanner APIs have an option to enable Data Boost:
We recommend that you useExecuteStreamingSql andstreamingRead in yourapplications, becauseExecuteSql andread are limited to 10 MB ofdata in their responses.
Sample code
For examples of using Data Boost in your application code, seeRead data in parallel.
Apache Spark SQL Connect for Google Cloud Spanner
The Apache Spark SQL Connector for Google Cloud Spanner supportsreading Google Cloud Spanner tables into Spark's DataFrames usingthe Spanner Java library. For more information about the ApachaSpark SQL Connector, seeApache Spark SQL connector for Google Cloud Spanner.
What's next
- Learn about Data Boost inData Boost overview.
- Monitor Data Boost usage
- Monitor and manage Data Boost quota usage
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Last updated 2025-12-17 UTC.