이 페이지에서는 BigQuery의 BigLake Iceberg 테이블로 복제하기 위해 Datastream을 구성하는 방법을 설명합니다.
BigLake Iceberg 테이블은 표준 BigQuery 테이블과 동일한 완전 관리형 환경을 제공하지만, Apache Iceberg 테이블 형식 및 Parquet 파일 형식으로 고객 소유 Cloud Storage 버킷에 데이터를 저장합니다. BigQuery 기능을 사용하여 데이터를 쿼리하고 분석하면서 데이터를 자체 스토리지 버킷에 보관할 수 있습니다.
BigLake Iceberg 테이블에 스트리밍 구성
BigLake Iceberg 테이블에 데이터를 수집하도록 스트림을 설정하려면 다음 단계를 따르세요.
[[["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: 2025-09-10(UTC)"],[],[],null,["# Configure BigLake Iceberg tables in BigQuery\n\nThis page describes how to configure Datastream for replication to\nBigLake Iceberg tables in BigQuery.\n\nBigLake Iceberg tables offer the same fully managed experience as\nstandard BigQuery tables, but store data in customer-owned Cloud Storage\nbuckets in the Apache Iceberg table format and Parquet file format. You can\nquery and analyse data using BigQuery capabilities while keeping the\ndata in your own storage buckets.\n| **Note:** Streaming to BigLake Iceberg tables is supported only in the **append-only** write mode. For more information, see [Configure write mode](/datastream/docs/destination-bigquery#configure-write-mode).\n\nConfigure streaming to BigLake Iceberg tables\n---------------------------------------------\n\nTo set up your stream to ingest data into BigLake Iceberg tables:\n\n1. [Create a Cloud Storage bucket](/storage/docs/creating-buckets) where you want to store your data.\n2. Create a Cloud resource connection in BigQuery. For information about how to create this type of connection, see [Create and set up a Cloud resource connection](/bigquery/docs/create-cloud-resource-connection).\n3. Get the identifier of the connection service account:\n\n bq show --location=\u003cvar translate=\"no\"\u003eLOCATION\u003c/var\u003e --connection --project_id=\u003cvar translate=\"no\"\u003ePROJECT_ID\u003c/var\u003e\n \u003cvar translate=\"no\"\u003eCONNECTION_NAME\u003c/var\u003e\n\n4. Grant your Cloud resource connection access to the Cloud Storage bucket that\n you created. To do this, add the `storage.admin` IAM permission\n to the connection service account:\n\n gcloud storage buckets add-iam-policy-binding gs://\u003cvar translate=\"no\"\u003eYOUR_GCS_BUCKET\u003c/var\u003e \\\n --member=serviceAccount:\u003cvar translate=\"no\"\u003eYOUR_SERVICE_ACCOUNT_ID\u003c/var\u003e \\\n --role=roles/storage.admin\n\n5. Create a BigLake Iceberg tables stream.\n\n For information about how to create a BigLake Iceberg tables stream\n using the Google Cloud console, see\n [Create a stream](/datastream/docs/create-a-stream).\n\n For information about how to create a request to stream data to\n BigLake Iceberg tables using REST, `Google Cloud CLI` or Terraform, see\n [Manage streams using the API](/datastream/docs/manage-streams#createastream-blmt).\n\n| **Note:** The Cloud Storage bucket, BigQuery dataset, and the Datastream connection must all be in the same region.\n\nWhat's next\n-----------\n\n- To learn more about streams, see [Stream lifecycle](/datastream/docs/stream-states-and-actions).\n- To learn how to create a stream, see [Create a stream](/datastream/docs/create-a-stream).\n- To learn how to create a connection profile that you can use with a BigLake Iceberg tables stream, see [Create a connection profile for BigQuery](/datastream/docs/create-connection-profiles#cp4bigquery)."]]
