์ปฌ๋ ์
์ ์ฌ์ฉํด ์ ๋ฆฌํ๊ธฐ
๋ด ํ๊ฒฝ์ค์ ์ ๊ธฐ์ค์ผ๋ก ์ฝํ
์ธ ๋ฅผ ์ ์ฅํ๊ณ ๋ถ๋ฅํ์ธ์.
Dataflow๋ ๋ค์ํ ๋ฐ์ดํฐ ์ฒ๋ฆฌ ํจํด์ ์คํํ๋ ๊ด๋ฆฌํ ์๋น์ค์
๋๋ค. ์ด ์ฌ์ดํธ์ ๋ฌธ์์์๋ ์๋น์ค ๊ธฐ๋ฅ ์ฌ์ฉ ์ง์นจ์ ๋น๋กฏํด Dataflow๋ฅผ ์ฌ์ฉํ์ฌ ์ผ๊ด ๋ฐ ์คํธ๋ฆฌ๋ฐ ๋ฐ์ดํฐ ์ฒ๋ฆฌ ํ์ดํ๋ผ์ธ์ ๋ฐฐํฌํ๋ ๋ฐฉ๋ฒ์ ๋ณด์ฌ์ค๋๋ค.
Apache Beam SDK๋ ์ผ๊ด ๋ฐ ์คํธ๋ฆฌ๋ฐ ํ์ดํ๋ผ์ธ์ ๋ชจ๋ ๊ฐ๋ฐํ ์ ์๋ ์คํ์์ค ํ๋ก๊ทธ๋๋ฐ ๋ชจ๋ธ์
๋๋ค. Apache Beam ํ๋ก๊ทธ๋จ์ ์ฌ์ฉํ์ฌ ํ์ดํ๋ผ์ธ์ ๋ง๋ ๋ค์ Dataflow ์๋น์ค์์ ํ์ดํ๋ผ์ธ์ ์คํํฉ๋๋ค. Apache Beam ๋ฌธ์๋ Apache Beam ํ๋ก๊ทธ๋๋ฐ ๋ชจ๋ธ, SDK, ๊ธฐํ ์คํ๊ธฐ์ ๋ํ ์ฌ์ธต์ ์ธ ๊ฐ๋
์ ๋ณด ๋ฐ ์ฐธ์กฐ ์๋ฃ๋ฅผ ์ ๊ณตํฉ๋๋ค.
๊ธฐ๋ณธ Apache Beam ๊ฐ๋
์ ๋ํ ๋ด์ฉ์ Beam ๋๋ฌ๋ณด๊ธฐ ๋ฐ Beam ํ๋ ์ด๊ทธ๋ผ์ด๋๋ฅผ ์ฐธ์กฐํ์ธ์.
Dataflow ๋ ์ํผ๋ถ ์ ์ฅ์๋ ๋ฐ๋ก ์คํํ ์ ์๋ ์์ฒด ํ์ดํ๋ผ์ธ๊ณผ ๊ฐ์ฅ ์ผ๋ฐ์ ์ธ Dataflow ์ฌ์ฉ ์ฌ๋ก๋ฅผ ์ ๊ณตํฉ๋๋ค.
Apache, Apache Beam, Beam, Beam ๋ก๊ณ , Beam firefly ๋ง์ค์ฝํธ๋ ๋ฏธ๊ตญ ๋๋ ๋ค๋ฅธ ๊ตญ๊ฐ์์ ์ฌ์ฉ๋๋ Apache Software Foundation์ ๋ฑ๋ก ์ํ์
๋๋ค.
๋ฌด๋ฃ๋ก ์์ํ๊ธฐ
๋ฌด๋ฃ ํฌ๋ ๋ง $300๋ก ๊ฐ๋
์ฆ๋ช
์์
-
Gemini 2.0 Flash Thinking ์ด์ฉ
-
AI API ๋ฐ BigQuery๋ฅผ ํฌํจํ์ฌ ์ธ๊ธฐ ์ ํ ์๋ณ ๋ฌด๋ฃ ์ฌ์ฉ๋
-
์๋ ์ฒญ๊ตฌ, ์ฝ์ ์์
๋ฌด๋ฃ ์ ํ ํํ ๋ณด๊ธฐ
20๊ฐ๊ฐ ๋๋ ํญ์ ๋ฌด๋ฃ ์ ํ์ ๊ณ์ ์ดํด๋ณด๊ธฐ
AI API, VM, ๋ฐ์ดํฐ ์จ์ดํ์ฐ์ค ๋ฑ ์ผ๋ฐ์ ์ธ ์ฌ์ฉ ์ฌ๋ก์ 20๊ฐ๊ฐ ๋๋ ๋ฌด๋ฃ ์ ํ์ ์ฌ์ฉํ ์ ์์ต๋๋ค.
๋ฌ๋ฆฌ ๋ช
์๋์ง ์๋ ํ ์ด ํ์ด์ง์ ์ฝํ
์ธ ์๋ Creative Commons Attribution 4.0 ๋ผ์ด์ ์ค์ ๋ฐ๋ผ ๋ผ์ด์ ์ค๊ฐ ๋ถ์ฌ๋๋ฉฐ, ์ฝ๋ ์ํ์๋ Apache 2.0 ๋ผ์ด์ ์ค์ ๋ฐ๋ผ ๋ผ์ด์ ์ค๊ฐ ๋ถ์ฌ๋ฉ๋๋ค. ์์ธํ ๋ด์ฉ์ Google Developers ์ฌ์ดํธ ์ ์ฑ
์ ์ฐธ์กฐํ์ธ์. ์๋ฐ๋ Oracle ๋ฐ/๋๋ Oracle ๊ณ์ด์ฌ์ ๋ฑ๋ก ์ํ์
๋๋ค.
์ต์ข
์
๋ฐ์ดํธ: 2025-04-03(UTC)
[[["์ดํดํ๊ธฐ ์ฌ์","easyToUnderstand","thumb-up"],["๋ฌธ์ ๊ฐ ํด๊ฒฐ๋จ","solvedMyProblem","thumb-up"],["๊ธฐํ","otherUp","thumb-up"]],[["์ดํดํ๊ธฐ ์ด๋ ค์","hardToUnderstand","thumb-down"],["์๋ชป๋ ์ ๋ณด ๋๋ ์ํ ์ฝ๋","incorrectInformationOrSampleCode","thumb-down"],["ํ์ํ ์ ๋ณด/์ํ์ด ์์","missingTheInformationSamplesINeed","thumb-down"],["๋ฒ์ญ ๋ฌธ์ ","translationIssue","thumb-down"],["๊ธฐํ","otherDown","thumb-down"]],["์ต์ข
์
๋ฐ์ดํธ: 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--------------"]]
