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내 환경설정을 기준으로 콘텐츠를 저장하고 분류하세요.
Dataflow는 다양한 데이터 처리 패턴을 실행하는 관리형 서비스입니다. 이 사이트의 문서에서는 서비스 기능 사용 지침을 비롯해 Dataflow를 사용하여 일괄 및 스트리밍 데이터 처리 파이프라인을 배포하는 방법을 보여줍니다.
Apache Beam SDK는 일괄 및 스트리밍 파이프라인을 모두 개발할 수 있는 오픈소스 프로그래밍 모델입니다. Apache Beam 프로그램을 사용하여 파이프라인을 만든 다음 Dataflow 서비스에서 파이프라인을 실행합니다. Apache Beam 문서는 Apache Beam 프로그래밍 모델, SDK, 기타 실행기에 대한 심층적인 개념 정보 및 참조 자료를 제공합니다.
기본 Apache Beam 개념에 대한 내용은 Beam 둘러보기 및 Beam 플레이그라운드를 참조하세요.
Dataflow 레시피북 저장소는 바로 실행할 수 있는 자체 파이프라인과 가장 일반적인 Dataflow 사용 사례를 제공합니다.
Apache, Apache Beam, Beam, Beam 로고, Beam firefly 마스코트는 미국 또는 다른 국가에서 사용되는 Apache Software Foundation의 등록 상표입니다.
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달리 명시되지 않는 한 이 페이지의 콘텐츠에는 Creative Commons Attribution 4.0 라이선스에 따라 라이선스가 부여되며, 코드 샘플에는 Apache 2.0 라이선스에 따라 라이선스가 부여됩니다. 자세한 내용은 Google Developers 사이트 정책을 참조하세요. 자바는 Oracle 및/또는 Oracle 계열사의 등록 상표입니다.
최종 업데이트: 2025-04-03(UTC)
[[["이해하기 쉬움","easyToUnderstand","thumb-up"],["문제가 해결됨","solvedMyProblem","thumb-up"],["기타","otherUp","thumb-up"]],[["이해하기 어려움","hardToUnderstand","thumb-down"],["잘못된 정보 또는 샘플 코드","incorrectInformationOrSampleCode","thumb-down"],["필요한 정보/샘플이 없음","missingTheInformationSamplesINeed","thumb-down"],["번역 문제","translationIssue","thumb-down"],["기타","otherDown","thumb-down"]],["최종 업데이트: 2025-04-03(UTC)"],[[["\u003cp\u003eDataflow is a managed service for executing batch and streaming data processing pipelines, with comprehensive documentation available on deployment and feature usage.\u003c/p\u003e\n"],["\u003cp\u003eThe Apache Beam SDK, an open-source programming model, is used to create pipelines that can be run on the Dataflow service, and its documentation can be found on the Apache website.\u003c/p\u003e\n"],["\u003cp\u003eVarious guides, references, and resources are provided, including quickstarts for creating pipelines in Java, Python, and Go, along with troubleshooting information.\u003c/p\u003e\n"],["\u003cp\u003eDataflow supports highly parallel workloads, machine learning inference, and the creation of ecommerce streaming pipelines, which are detailed in use case examples.\u003c/p\u003e\n"],["\u003cp\u003eThe documentation provides access to code samples, pricing information, quotas, release notes, support and billing help, all relevant to the managed service.\u003c/p\u003e\n"]]],[],null,["# Dataflow documentation\n======================\n\n[Read product documentation](/dataflow/docs/overview)\nDataflow is a managed service for executing a wide variety of data\nprocessing patterns. The documentation on this site shows you how to deploy\nyour batch and streaming data processing pipelines using\nDataflow, including directions for using service features.\n\n\nThe Apache Beam SDK\nis an open source programming model that enables you to develop both batch\nand streaming pipelines. You create your pipelines with an Apache Beam\nprogram and then run them on the Dataflow service. The\n[Apache Beam\ndocumentation](https://beam.apache.org/documentation/) provides in-depth conceptual information and reference\nmaterial for the Apache Beam programming model, SDKs, and other runners.\n\nTo learn basic Apache Beam concepts, see the [Tour of Beam](https://tour.beam.apache.org/) and [Beam Playground](https://play.beam.apache.org/).\nThe [Dataflow Cookbook](https://github.com/GoogleCloudPlatform/dataflow-cookbook) repository also provides ready-to-launch and self-contained pipelines\nand the most common Dataflow use cases. \n*Apache, Apache Beam, Beam, the\nBeam logo, and the Beam firefly mascot are registered trademarks of The Apache Software Foundation in the\nUnited States and/or other countries.* [Get started for free](https://console.cloud.google.com/freetrial) \n\n#### Start your proof of concept with $300 in free credit\n\n- Get access to Gemini 2.0 Flash Thinking\n- Free monthly usage of popular products, including AI APIs and BigQuery\n- No automatic charges, no commitment \n[View free product offers](/free/docs/free-cloud-features#free-tier) \n\n#### Keep exploring with 20+ always-free products\n\n\nAccess 20+ free products for common use cases, including AI APIs, VMs, data warehouses,\nand more.\n\nDocumentation resources\n-----------------------\n\nFind quickstarts and guides, review key references, and get help with common issues. \nformat_list_numbered\n\n### Guides\n\n-\n\n [Create a Dataflow pipeline using Java](/dataflow/docs/quickstarts/create-pipeline-java)\n\n-\n\n [Create a Dataflow pipeline using Python](/dataflow/docs/quickstarts/create-pipeline-python)\n\n-\n\n [Create a Dataflow pipeline using Go](/dataflow/docs/quickstarts/create-pipeline-go)\n\n-\n\n [Create a streaming pipeline using a Dataflow template](/dataflow/docs/quickstarts/create-streaming-pipeline-template)\n\n-\n\n [Build and run a Flex Template](/dataflow/docs/guides/templates/using-flex-templates)\n\n-\n\n [Deploy Dataflow pipelines](/dataflow/docs/guides/deploying-a-pipeline)\n\n-\n\n [Develop with notebooks](/dataflow/docs/guides/interactive-pipeline-development)\n\n-\n\n [Troubleshooting and debugging](/dataflow/docs/guides/troubleshooting-your-pipeline)\n\nfind_in_page\n\n### Reference\n\n-\n\n [Install the Apache Beam SDK](/dataflow/docs/guides/installing-beam-sdk)\n\n-\n\n [Java SDK](https://beam.apache.org/documentation/sdks/javadoc/current/)\n\n-\n\n [Python SDK](https://beam.apache.org/documentation/sdks/pydoc/current/)\n\n-\n\n [Go SDK](https://pkg.go.dev/github.com/apache/beam/sdks/v2/go/pkg/beam)\n\n-\n\n [SDK version support status](/dataflow/docs/support/sdk-version-support-status)\n\n-\n\n [REST API](/dataflow/docs/reference/rest)\n\n-\n\n [gcloud command-line functions](/sdk/gcloud/reference/dataflow)\n\n-\n\n [Google-provided templates](/dataflow/docs/concepts/dataflow-templates)\n\ninfo\n\n### Resources\n\n-\n\n [Dataflow code samples](/dataflow/docs/samples)\n\n-\n\n [Pricing](/dataflow/pricing)\n\n-\n\n [Quotas and limits](/dataflow/quotas)\n\n-\n\n [Release Notes](/dataflow/docs/release-notes)\n\n-\n\n [Getting support](/dataflow/docs/support/getting-support)\n\n-\n\n [Billing questions](/dataflow/docs/support/billing-questions)\n\nRelated resources\n-----------------\n\nExplore self-paced training, use cases, reference architectures, and code samples with examples of how to use and connect Google Cloud services. Use case \nUse cases\n\n### Run HPC highly parallel workloads\n\n\nWith Dataflow, you can run your highly parallel workloads in a single pipeline, improving efficiency and making your workflow easier to manage.\n\nStreaming\n\n\u003cbr /\u003e\n\n[Learn more](/dataflow/docs/hpc-ep) \nUse case \nUse cases\n\n### Run inference with Dataflow ML\n\n\nDataflow ML lets you use Dataflow to deploy and manage complete machine learning (ML) pipelines. Use ML models to do local and remote inference with batch and streaming pipelines. Use data processing tools to prepare your data for model training and to process the results of the models.\n\nML Streaming\n\n\u003cbr /\u003e\n\n[Learn more](/dataflow/docs/machine-learning) \nUse case \nUse cases\n\n### Create an ecommerce streaming pipeline\n\n\nBuild an end-to-end ecommerce sample application that streams data from a webstore to BigQuery and Bigtable. The sample application illustrates common use cases and best practices for implementing streaming data analytics and real-time artificial intelligence (AI).\n\necommerce Streaming\n\n\u003cbr /\u003e\n\n[Learn more](/dataflow/docs/tutorials/ecommerce-retail-pipeline)\n\nRelated videos\n--------------"]]
