See: Description
Package | Description |
---|---|
org.apache.beam.runners.apex |
Implementation of the Beam runner for Apache Apex.
|
org.apache.beam.runners.dataflow |
Provides a Beam runner that executes pipelines on the Google Cloud Dataflow service.
|
org.apache.beam.runners.dataflow.options |
Provides
PipelineOptions specific to Google Cloud Dataflow. |
org.apache.beam.runners.dataflow.util |
Provides miscellaneous internal utilities used by the Google Cloud Dataflow runner.
|
org.apache.beam.runners.direct |
Defines the
PipelineOptions.DirectRunner
which executes both Bounded and Unbounded Pipelines on the local machine. |
org.apache.beam.runners.flink |
Internal implementation of the Beam runner for Apache Flink.
|
org.apache.beam.runners.flink.metrics |
Internal metrics implementation of the Beam runner for Apache Flink.
|
org.apache.beam.runners.spark |
Internal implementation of the Beam runner for Apache Spark.
|
org.apache.beam.runners.spark.aggregators |
Provides internal utilities for implementing Beam aggregators using Spark accumulators.
|
org.apache.beam.runners.spark.aggregators.metrics |
Defines classes for integrating with Spark's metrics mechanism (Sinks, Sources, etc.).
|
org.apache.beam.runners.spark.coders |
Beam coders and coder-related utilities for running on Apache Spark.
|
org.apache.beam.runners.spark.io |
Spark-specific transforms for I/O.
|
org.apache.beam.runners.spark.metrics |
Provides internal utilities for implementing Beam metrics using Spark accumulators.
|
org.apache.beam.runners.spark.metrics.sink |
Spark sinks that supports beam metrics and aggregators.
|
org.apache.beam.runners.spark.stateful |
Spark-specific stateful operators.
|
org.apache.beam.runners.spark.util |
Internal utilities to translate Beam pipelines to Spark.
|
org.apache.beam.sdk |
Provides a simple, powerful model for building both batch and
streaming parallel data processing
Pipeline s. |
org.apache.beam.sdk.annotations |
Defines annotations used across the SDK.
|
org.apache.beam.sdk.coders |
Defines
Coders
to specify how data is encoded to and decoded from byte strings. |
org.apache.beam.sdk.extensions.gcp.auth |
Defines classes related to interacting with
Credentials for
pipeline creation and execution containing Google Cloud Platform components. |
org.apache.beam.sdk.extensions.gcp.options |
Defines
PipelineOptions for
configuring pipeline execution for Google Cloud Platform components. |
org.apache.beam.sdk.extensions.gcp.storage |
Defines IO connectors for Google Cloud Storage.
|
org.apache.beam.sdk.extensions.jackson |
Utilities for parsing and creating JSON serialized objects.
|
org.apache.beam.sdk.extensions.joinlibrary |
Utilities for performing SQL-style joins of keyed
PCollections . |
org.apache.beam.sdk.extensions.protobuf |
Defines a
Coder
for Protocol Buffers messages, ProtoCoder . |
org.apache.beam.sdk.extensions.sorter |
Utility for performing local sort of potentially large sets of values.
|
org.apache.beam.sdk.io | |
org.apache.beam.sdk.io.elasticsearch |
Transforms for reading and writing from Elasticsearch.
|
org.apache.beam.sdk.io.fs |
Apache Beam FileSystem interfaces and their default implementations.
|
org.apache.beam.sdk.io.gcp.bigquery |
Defines transforms for reading and writing from Google BigQuery.
|
org.apache.beam.sdk.io.gcp.bigtable |
Defines transforms for reading and writing from Google Cloud Bigtable.
|
org.apache.beam.sdk.io.gcp.common |
Defines common Google Cloud Platform IO support classes.
|
org.apache.beam.sdk.io.gcp.datastore |
Provides an API for reading from and writing to
Google Cloud Datastore over different
versions of the Cloud Datastore Client libraries.
|
org.apache.beam.sdk.io.gcp.pubsub |
Defines transforms for reading and writing from
Google Cloud Pub/Sub.
|
org.apache.beam.sdk.io.gcp.testing |
Defines utilities for unit testing Google Cloud Platform components of Apache Beam pipelines.
|
org.apache.beam.sdk.io.hadoop |
Classes shared by Hadoop based IOs.
|
org.apache.beam.sdk.io.hadoop.inputformat |
Defines transforms for reading from Data sources which implement Hadoop Input Format.
|
org.apache.beam.sdk.io.hbase |
Defines transforms for reading and writing from HBase.
|
org.apache.beam.sdk.io.hdfs |
FileSystem implementation for any Hadoop
FileSystem . |
org.apache.beam.sdk.io.jdbc |
Transforms for reading and writing from JDBC.
|
org.apache.beam.sdk.io.jms |
Transforms for reading and writing from JMS (Java Messaging Service).
|
org.apache.beam.sdk.io.kafka |
Transforms for reading and writing from Apache Kafka.
|
org.apache.beam.sdk.io.kafka.serialization |
Kafka serializers and deserializers.
|
org.apache.beam.sdk.io.kinesis |
Transforms for reading and writing from Amazon Kinesis.
|
org.apache.beam.sdk.io.mongodb |
Transforms for reading and writing from MongoDB.
|
org.apache.beam.sdk.io.mqtt |
Transforms for reading and writing from MQTT.
|
org.apache.beam.sdk.io.range |
Provides thread-safe helpers for implementing dynamic work rebalancing in position-based
bounded sources.
|
org.apache.beam.sdk.io.xml |
Transforms for reading and writing Xml files.
|
org.apache.beam.sdk.metrics |
Metrics allow exporting information about the execution of a pipeline.
|
org.apache.beam.sdk.options |
Defines
PipelineOptions for
configuring pipeline execution. |
org.apache.beam.sdk.state |
Classes and interfaces for interacting with state.
|
org.apache.beam.sdk.testing |
Defines utilities for unit testing Apache Beam pipelines.
|
org.apache.beam.sdk.transforms |
Defines
PTransform s for transforming
data in a pipeline. |
org.apache.beam.sdk.transforms.display |
Defines
HasDisplayData for annotating components
which provide display data used
within UIs and diagnostic tools. |
org.apache.beam.sdk.transforms.join |
Defines the
CoGroupByKey transform
for joining multiple PCollections. |
org.apache.beam.sdk.transforms.splittabledofn |
Defines utilities related to splittable
DoFn . |
org.apache.beam.sdk.transforms.windowing | |
org.apache.beam.sdk.values |
Defines
PCollection and other classes for
representing data in a Pipeline . |
The Apache Beam SDK for Java provides a simple and elegant programming model to express your data processing pipelines; see the Apache Beam website for more information and getting started instructions.
The easiest way to use the Apache Beam SDK for Java is via one of the released artifacts from the Maven Central Repository.
Version numbers use the form major.minor.incremental and are incremented as follows:
Please note that APIs marked
@Experimental
may change at any point and are not guaranteed to remain compatible across versions.