Java idiomatic client for Pub/Sub Lite Spark Connector.

• Product Documentation
• Client Library Documentation

If you are using Maven, add this to your pom.xml file:

<dependency>
  <groupId>com.google.cloud</groupId>
  <artifactId>pubsublite-spark-sql-streaming</artifactId>
  <version>1.0.0</version>
</dependency>

If you are using Gradle without BOM, add this to your dependencies:

implementation 'com.google.cloud:pubsublite-spark-sql-streaming:1.0.0'

If you are using SBT, add this to your dependencies:

libraryDependencies += "com.google.cloud" % "pubsublite-spark-sql-streaming" % "1.0.0"

See the Authentication section in the base directory's README.

The client application making API calls must be granted authorization scopes required for the desired Pub/Sub Lite Spark Connector APIs, and the authenticated principal must have the IAM role(s) required to access GCP resources using the Pub/Sub Lite Spark Connector API calls.

You will need a Google Cloud Platform Console project with the Pub/Sub Lite Spark Connector API enabled. You will need to enable billing to use Google Pub/Sub Lite Spark Connector. Follow these instructions to get your project set up. You will also need to set up the local development environment by installing the Google Cloud SDK and running the following commands in command line: gcloud auth login and gcloud config set project [YOUR PROJECT ID].

You'll need to obtain the pubsublite-spark-sql-streaming library. See the Quickstart section to add pubsublite-spark-sql-streaming as a dependency in your code.

Google Cloud Pub/Sub Lite is a zonal, real-time messaging service that lets you send and receive messages between independent applications. You can manually configure the throughput and storage capacity for Pub/Sub Lite systems.

The Pub/Sub Lite Spark connector supports Pub/Sub Lite as an input source to Apache Spark Structured Streaming in both the default micro-batch processing mode and the experimental continous processing mode. The connector works in all Apache Spark distributions, including Google Cloud Dataproc and manual Spark installations.

Follow the instruction to create a new subscription or use an existing subscription. If using an existing subscription, the connector will read from the oldest unacknowledged message in the subscription.

If you do not have an Apache Spark environment, you can create a Cloud Dataproc cluster with pre-configured auth. The following examples assume you are using Cloud Dataproc, but you can use spark-submit on any cluster.

MY_CLUSTER=...
gcloud dataproc clusters create "$MY_CLUSTER"

The latest version of the connector is publicly available from the Maven Central repository. You can download and pass it in the --jars option when using the spark-submit command.

There are 3 java samples (word count, simple write, simple read) under samples that shows using the connector inside Dataproc.

Here is an example in Python:

df = spark.readStream \
  .format("pubsublite") \
  .option("pubsublite.subscription", "projects/$PROJECT_NUMBER/locations/$LOCATION/subscriptions/$SUBSCRIPTION_ID") \
  .load

Here is an example in Java:

Dataset<Row> df = spark
  .readStream()
  .format("pubsublite")
  .option("pubsublite.subscription", "projects/$PROJECT_NUMBER/locations/$LOCATION/subscriptions/$SUBSCRIPTION_ID")
  .load();

Note that the connector supports both MicroBatch Processing and Continuous Processing.

Here is an example in Python:

df.writeStream \
  .format("pubsublite") \
  .option("pubsublite.topic", "projects/$PROJECT_NUMBER/locations/$LOCATION/topics/$TOPIC_ID") \
  .option("checkpointLocation", "path/to/HDFS/dir")
  .outputMode("complete") \
  .trigger(processingTime="2 seconds") \
  .start()

Here is an example in Java:

df.writeStream()
  .format("pubsublite")
  .option("pubsublite.topic", "projects/$PROJECT_NUMBER/locations/$LOCATION/topics/$TOPIC_ID")
  .option("checkpointLocation", "path/to/HDFS/dir")
  .outputMode(OutputMode.Complete())
  .trigger(Trigger.ProcessingTime(2, TimeUnit.SECONDS))
  .start();

When reading from Pub/Sub Lite, the connector supports a number of configuration options:

When writing to Pub/Sub Lite, the connector supports a number of configuration options:

When reading from Pub/Sub Lite, the connector has a fixed data schema as follows:

When writing to Pub/Sub Lite, the connetor matches the following data field and data types as follows:

Note that when a data field is present in the table but the data type mismatches, the connector will throw IllegalArgumentException that terminates the query.

The connector is built using Maven. Following command creates a JAR file with shaded dependencies:

mvn package

See the Pub/Sub Lite pricing documentation.

No, the number of Spark partitions is set to be the number of Pub/Sub Lite partitions of the topic that the subscription is attached to.

Use a service account JSON key and GOOGLE_APPLICATION_CREDENTIALS as described here.

Credentials can be provided with gcp.credentials.key option, it needs to be passed in as a base64-encoded string.

Example:

spark.readStream.format("pubsublite").option("gcp.credentials.key", "<SERVICE_ACCOUNT_JSON_IN_BASE64>")

Samples are in the samples/ directory.

Sample	Source Code	Try it
Admin Utils	source code
Common Utils	source code
Publish Words	source code
Read Results	source code
Simple Read	source code
Simple Write	source code
Word Count	source code

To get help, follow the instructions in the shared Troubleshooting document.

Pub/Sub Lite Spark Connector uses gRPC for the transport layer.

Java 8 or above is required for using this client.

Google's Java client libraries, Google Cloud Client Libraries and Google Cloud API Libraries, follow the Oracle Java SE support roadmap (see the Oracle Java SE Product Releases section).

In general, new feature development occurs with support for the lowest Java LTS version covered by Oracle's Premier Support (which typically lasts 5 years from initial General Availability). If the minimum required JVM for a given library is changed, it is accompanied by a semver major release.

Java 11 and (in September 2021) Java 17 are the best choices for new development.

Google tests its client libraries with all current LTS versions covered by Oracle's Extended Support (which typically lasts 8 years from initial General Availability).

Google's client libraries support legacy versions of Java runtimes with long term stable libraries that don't receive feature updates on a best efforts basis as it may not be possible to backport all patches.

Google provides updates on a best efforts basis to apps that continue to use Java 7, though apps might need to upgrade to current versions of the library that supports their JVM.

The latest versions and the supported Java versions are identified on the individual GitHub repository github.com/GoogleAPIs/java-SERVICENAME and on google-cloud-java.

This library follows Semantic Versioning.

Contributions to this library are always welcome and highly encouraged.

See CONTRIBUTING for more information how to get started.

Please note that this project is released with a Contributor Code of Conduct. By participating in this project you agree to abide by its terms. See Code of Conduct for more information.

Apache 2.0 - See LICENSE for more information.

Java Version	Status
Java 8
Java 8 OSX
Java 8 Windows
Java 11

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