"Managed Service for Apache Spark" is the new name for the product formerly known as "Dataproc on Compute Engine" (cluster deployment) and "Google Cloud Serverless for Apache Spark" (serverless deployment).
Overview of APIs and Client LibrariesStay organized with collectionsSave and categorize content based on your preferences.
Available interfaces
You can use one of several programmatic interfaces when interacting with
Managed Service for Apache Spark. These are the available interfaces, in the order that
we recommend using them:
Google Cloud Client Libraries:
Managed Service for Apache Spark
(alpha and beta release)
client libraries are available in multiple languages and
are built ongRPC. These client
libraries provide a layer of abstraction on top of
gRPC and handle the details of operation polling, retries, and more.
gRPC: If a client library is not available
for your programming language of choice, you can generate gRPC client
libraries for Dataproc in any gRPC-supported language. To do this, you'll
need theprotocol buffersservice definition available fromour repository on GitHub.
You can then follow the instructions for your preferred language ongrpc.ioto generate and use your
client.
REST API: If you're unable
to use Managed Service for Apache Spark's client libraries or the gRPC API, use the REST API.
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