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  • Rank 41,455 (Top 0.9 %)
  • Language
    Java
  • License
    Apache License 2.0
  • Created over 6 years ago
  • Updated 2 months ago

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Repository Details

Cloud Dataflow Google-provided templates for solving in-Cloud data tasks

Google Cloud Dataflow Template Pipelines

These Dataflow templates are an effort to solve simple, but large, in-Cloud data tasks, including data import/export/backup/restore and bulk API operations, without a development environment. The technology under the hood which makes these operations possible is the Google Cloud Dataflow service combined with a set of Apache Beam SDK templated pipelines.

Google is providing this collection of pre-implemented Dataflow templates as a reference and to provide easy customization for developers wanting to extend their functionality.

Open in Cloud Shell

Note on Default Branch

As of November 18, 2021, our default branch is now named "main". This does not affect forks. If you would like your fork and its local clone to reflect these changes you can follow GitHub's branch renaming guide.

Template Pipelines

For documentation on each template's usage and parameters, please see the official docs.

Contributing

To contribute to the repository, see CONTRIBUTING.md.

Release Process

Templates are released in a weekly basis (best-effort) as part of the efforts to keep Google-provided Templates updated with latest fixes and improvements.

To learn more about this process, or how you can stage your own changes, see Release Process.

More Information

  • Dataflow - general Dataflow documentation.
  • Dataflow Templates - basic template concepts.
  • Google-provided Templates - official documentation for templates provided by Google (the source code is in this repository).
  • Dataflow Cookbook: Blog, GitHub Repository - pipeline examples and practical solutions to common data processing challenges.
  • Dataflow Metrics Collector - CLI tool to collect dataflow resource & execution metrics and export to either BigQuery or Google Cloud Storage. Useful for comparison and visualization of the metrics while benchmarking the dataflow pipelines using various data formats, resource configurations etc
  • Apache Beam
    • Overview
    • Quickstart: Java, Python, Go
    • Tour of Beam - an interactive tour with learning topics covering core Beam concepts from simple ones to more advanced ones.
    • Beam Playground - an interactive environment to try out Beam transforms and examples without having to install Apache Beam.
    • Beam College - hands-on training and practical tips, including video recordings of Apache Beam and Dataflow Templates lessons.
    • Getting Started with Apache Beam - Quest - A 5 lab series that provides a Google Cloud certified badge upon completion.

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