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This page lists the Spanner APIs that support Spanner Data Boost and
explains how to view sample code that uses Data Boost. With
Data Boost, you can run large analytic queries with near-zero
impact to existing workloads on the provisioned Spanner instance.
Before you begin
Ensure that the principal (for example, the service account) that runs the
application has the
spanner.databases.useDataBoost Identity and Access Management (IAM)
permission. For more information, see
Access control with IAM.
APIs
For partitioned reads with Data Boost, the following
Spanner APIs have an option to enable Data Boost:
We recommend that you use ExecuteStreamingSql and streamingRead in your
applications, because ExecuteSql and read are limited to 10 MB of
data in their responses.
Sample code
For examples of using Data Boost in your application code, see
Read data in parallel.
Apache Spark SQL Connect for Google Cloud Spanner
The Apache Spark SQL Connector for Google Cloud Spanner supports
reading Google Cloud Spanner tables into Spark's DataFrames using
the Spanner Java library. For more information about the Apacha
Spark SQL Connector, see Apache Spark SQL connector for Google Cloud Spanner.
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