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O Dataflow é baseado no projeto de código aberto Apache Beam. Você pode usar o SDK do Apache Beam para criar pipelines para o Dataflow.
Neste documento, listamos alguns recursos para começar a usar a programação do Apache Beam.
Instalar o SDK do Apache Beam:
mostra como instalar o SDK do Apache Beam para executar pipelines
no serviço do Dataflow.
Tour do Apache Beam:
um guia de aprendizado para se familiarizar com o Apache Beam.
As unidades de aprendizagem são acompanhadas por exemplos de código que você pode executar e modificar.
Apache Beam Playground: um ambiente interativo para testar transformações e exemplos do Apache Beam sem precisar instalar o Apache Beam no seu ambiente.
No site do Apache Beam, também é possível encontrar informações sobre como projetar, criar e testar o pipeline:
Projetar o pipeline: mostra como determinar a estrutura do pipeline, como escolher as transformações que serão aplicadas aos dados e como determinar os métodos de entrada e de saída.
Criar o pipeline:
explica a mecânica de uso das classes nos SDKs do Apache Beam e as
etapas necessárias para criar um pipeline.
Testar o pipeline:
apresenta as práticas recomendadas para testar os pipelines.
Use os seguintes exemplos do GitHub do Apache Beam para começar
a criar um pipeline de streaming:
[[["Fácil de entender","easyToUnderstand","thumb-up"],["Meu problema foi resolvido","solvedMyProblem","thumb-up"],["Outro","otherUp","thumb-up"]],[["Difícil de entender","hardToUnderstand","thumb-down"],["Informações incorretas ou exemplo de código","incorrectInformationOrSampleCode","thumb-down"],["Não contém as informações/amostras de que eu preciso","missingTheInformationSamplesINeed","thumb-down"],["Problema na tradução","translationIssue","thumb-down"],["Outro","otherDown","thumb-down"]],["Última atualização 2025-03-24 UTC."],[[["\u003cp\u003eDataflow utilizes the open-source Apache Beam project, allowing users to construct pipelines with the Apache Beam SDK.\u003c/p\u003e\n"],["\u003cp\u003eResources are provided for installing the Apache Beam SDK, guiding users on how to run their pipelines within the Dataflow service.\u003c/p\u003e\n"],["\u003cp\u003eThe Apache Beam website offers resources covering pipeline design, creation, and testing best practices, using the classes in the Apache Beam SDK.\u003c/p\u003e\n"],["\u003cp\u003eThe Apache Beam playground offers an interactive environment to try out the Apache Beam transforms without needing to install Apache Beam.\u003c/p\u003e\n"],["\u003cp\u003eExample streaming pipelines, including word extraction, word count, and wordcap, are available on the Apache Beam GitHub repository in Java, Python, and Go.\u003c/p\u003e\n"]]],[],null,["# Use Apache Beam to build pipelines\n\nDataflow is built on the open source\n[Apache Beam](https://beam.apache.org/) project. You can\nuse the Apache Beam SDK to build pipelines for Dataflow.\nThis document lists some resources for getting started with Apache Beam\nprogramming.\n\nGet started\n-----------\n\n- [Install the Apache Beam SDK](/dataflow/docs/guides/installing-beam-sdk):\n Shows how to install the Apache Beam SDK so that you can run your\n pipelines in Dataflow.\n\n- [Create a Java pipeline](/dataflow/docs/guides/create-pipeline-java): Shows\n how to create a pipeline with the Apache Beam Java SDK and run the\n pipeline in Dataflow.\n\n- [Create a Python pipeline](/dataflow/docs/guides/create-pipeline-python):\n Shows how to create a pipeline with the Apache Beam Python SDK and run the\n pipeline in Dataflow.\n\n- [Create a Go pipeline](/dataflow/docs/guides/create-pipeline-go): Shows\n how to create a pipeline with the Apache Beam Go SDK and run the pipeline\n in Dataflow.\n\nLearn Apache Beam\n-----------------\n\nYou can use the following pages on the Apache Beam website to learn about\nApache Beam programming.\n\n- [Apache Beam programming guide](https://beam.apache.org/documentation/programming-guide/):\n Provides guidance for using the Apache Beam SDK classes to build and test\n your pipeline.\n\n- [Tour of Apache Beam](https://tour.beam.apache.org/):\n A learning guide you can use to familiarize yourself with Apache Beam.\n Learning units are accompanied by code examples that you can run and modify.\n\n- [Apache Beam playground](https://play.beam.apache.org/):\n An interactive environment to try out Apache Beam transforms and examples\n without having to install Apache Beam in your environment.\n\n- [Create your pipeline](https://beam.apache.org/documentation/pipelines/create-your-pipeline/):\n Explains the mechanics of using the classes in the Apache Beam SDKs and\n the necessary steps needed to build a pipeline.\n\nDevelop pipelines\n-----------------\n\n- [Plan your pipeline](/dataflow/docs/guides/plan-pipelines): Learn how to plan\n your pipeline before you begin code development.\n\n- [Develop and test pipelines](/dataflow/docs/guides/plan-pipelines): Learn best\n practices for developing and testing your Dataflow pipeline.\n\n- [Streaming pipelines](/dataflow/docs/concepts/streaming-pipelines): Learn\n about important design considerations for streaming pipelines, including\n windows, triggers, and watermarks.\n\nCode examples\n-------------\n\nYou can use the following examples from the Apache Beam GitHub to start\nbuilding a streaming pipeline:\n\n- [Streaming word extraction](https://github.com/apache/beam/blob/master/examples/java/src/main/java/org/apache/beam/examples/complete/StreamingWordExtract.java) (Java)\n- [Streaming word count](https://github.com/apache/beam/blob/master/sdks/python/apache_beam/examples/streaming_wordcount.py) (Python), and\n- [`streaming_wordcap`](https://github.com/apache/beam/blob/master/sdks/go/examples/streaming_wordcap/wordcap.go) (Go).\n\nWhat's next\n-----------\n\n- [Deploy Dataflow pipelines](/dataflow/docs/guides/deploying-a-pipeline).\n- [Use the Dataflow job monitoring interface](/dataflow/docs/guides/monitoring-overview)."]]
