See: Description
Package | Description |
---|---|
com.google.cloud.dataflow.sdk |
Provides a simple, powerful model for building both batch and
streaming parallel data processing
Pipeline s. |
com.google.cloud.dataflow.sdk.annotations |
Defines annotations used across the SDK.
|
com.google.cloud.dataflow.sdk.coders |
Defines
Coders
to specify how data is encoded to and decoded from byte strings. |
com.google.cloud.dataflow.sdk.coders.protobuf | |
com.google.cloud.dataflow.sdk.io |
Defines transforms for reading and writing common storage formats, including
AvroIO ,
BigQueryIO , and
TextIO . |
com.google.cloud.dataflow.sdk.io.bigtable | |
com.google.cloud.dataflow.sdk.io.range |
Provides thread-safe helpers for implementing dynamic work rebalancing in position-based
bounded sources.
|
com.google.cloud.dataflow.sdk.options |
Defines
PipelineOptions for
configuring pipeline execution. |
com.google.cloud.dataflow.sdk.runners |
Defines runners for executing Pipelines in different modes, including
DirectPipelineRunner and
DataflowPipelineRunner . |
com.google.cloud.dataflow.sdk.testing |
Defines utilities for unit testing Dataflow pipelines.
|
com.google.cloud.dataflow.sdk.transforms |
Defines
PTransform s for transforming
data in a pipeline. |
com.google.cloud.dataflow.sdk.transforms.join |
Defines the
CoGroupByKey transform
for joining multiple PCollections. |
com.google.cloud.dataflow.sdk.transforms.windowing | |
com.google.cloud.dataflow.sdk.values |
Defines
PCollection and other classes for
representing data in a Pipeline . |
The Google Cloud Dataflow SDK for Java provides a simple and elegant programming model to express your data processing pipelines; see our product page for more information and getting started instructions.
The easiest way to use the Google Cloud Dataflow SDK for Java is via one of the released artifacts from the Maven Central Repository. See our release notes for more information about each released version.
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.