[[["わかりやすい","easyToUnderstand","thumb-up"],["問題の解決に役立った","solvedMyProblem","thumb-up"],["その他","otherUp","thumb-up"]],[["わかりにくい","hardToUnderstand","thumb-down"],["情報またはサンプルコードが不正確","incorrectInformationOrSampleCode","thumb-down"],["必要な情報 / サンプルがない","missingTheInformationSamplesINeed","thumb-down"],["翻訳に関する問題","translationIssue","thumb-down"],["その他","otherDown","thumb-down"]],["最終更新日 2025-08-08 UTC。"],[],[],null,["# Get started with Dataflow\n\nThe Dataflow service runs pipelines that are defined by the\nApache Beam SDK. But for many use cases, you don't need to write code\nwith the SDK, because Dataflow provides several no-code and\nlow-code options.\n\n- **Templates** . Dataflow provides\n [prebuilt templates](/dataflow/docs/guides/templates/provided-templates) for\n moving data from one product to another. For example, you can use a template\n to move data from\n [Pub/Sub to BigQuery](/dataflow/docs/guides/templates/provided/pubsub-to-bigquery).\n\n- **Job builder** . The [job builder](/dataflow/docs/guides/job-builder) is a\n visual UI for building Dataflow pipelines in the\n Google Cloud console. It supports a subset of Apache Beam sources and\n sinks, as well as transforms such as joins, Python functions, and SQL\n queries. We recommend the job builder for simple use cases such as data\n movement.\n\n- **Turnkey transforms for ML** . For machine learning (ML) pipelines,\n Dataflow provides\n turnkey transforms that require minimal code to configure. As a\n starting point, run an [example ML\n notebook](https://github.com/apache/beam/blob/master/examples/notebooks/beam-ml/README.md)\n in Google Colab. To learn more, see the [Dataflow ML\n overview](/dataflow/docs/machine-learning).\n\n- **Apache Beam SDK**. To get the full power of Apache Beam, use the\n SDK to write a custom pipeline in Python, Java, or Go.\n\nTo help your decision, the following table lists some common examples.\n\nWhat's next\n-----------\n\n- Get started with a specific Dataflow use case and approach:\n - [Quickstart: Use the job\n builder](/dataflow/docs/quickstarts/create-pipeline-job-builder).\n - [Quickstart: Run a Dataflow\n template](/dataflow/docs/quickstarts/create-streaming-pipeline-template).\n - [Dataflow ML notebook: Use RunInference for Generative AI](/dataflow/docs/notebooks/run_inference_generative_ai).\n - [Create a Dataflow pipeline using the Apache Beam SDK and Python](/dataflow/docs/guides/create-pipeline-python).\n- See more [Dataflow use cases](/dataflow/docs/use-cases).\n- Learn more about [building pipelines](/dataflow/docs/guides/build-pipelines)."]]
