이 문서에서는 Apache Spark용 서버리스 스테이징 버킷에 대해 설명합니다.
Apache Spark용 서버리스는 프로젝트에 Cloud Storage 스테이징 버킷을 만들거나 이전 배치 만들기 요청의 기존 스테이징 버킷을 재사용합니다. 이는 Compute Engine 클러스터의 Dataproc에서 생성된 기본 버킷입니다. 자세한 내용은 Dataproc 스테이징 및 임시 버킷을 참고하세요.
Apache Spark용 서버리스는 워크로드 종속 항목, 구성 파일, 작업 드라이버 콘솔 출력을 스테이징 버킷에 저장합니다.
Apache Spark용 서버리스는 워크로드가 배포되는 Compute Engine 영역에 따라 Cloud Storage 위치에 리전 스테이징 버킷을 설정한 후 이러한 프로젝트 수준의 위치별 버킷을 만들고 관리합니다.
Apache Spark용 서버리스에서 생성된 스테이징 버킷은 동일 리전에 있는 워크로드 간에 공유되며 Cloud Storage 소프트 삭제 보관 기간이 0초로 설정된 상태로 생성됩니다.
[[["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: 2025-09-04(UTC)"],[[["\u003cp\u003eDataproc Serverless utilizes Cloud Storage staging buckets to store workload dependencies, config files, and job driver console output.\u003c/p\u003e\n"],["\u003cp\u003eThese staging buckets are created by Dataproc Serverless within your project, or an existing one is reused, similar to the default bucket used with Dataproc on Compute Engine clusters.\u003c/p\u003e\n"],["\u003cp\u003eDataproc Serverless creates regional staging buckets, which are shared across workloads within the same region, based on the Compute Engine zone where the workload is deployed.\u003c/p\u003e\n"],["\u003cp\u003eThe staging buckets created by Dataproc Serverless can be identified by filtering for the \u003ccode\u003edataproc-staging-\u003c/code\u003e prefix in Cloud Storage, and they are created with a 0-second soft delete retention.\u003c/p\u003e\n"]]],[],null,["# Serverless for Apache Spark staging buckets\n\nThis document provides information about Serverless for Apache Spark staging buckets.\nServerless for Apache Spark creates a Cloud Storage staging bucket in your project\nor reuses an existing staging bucket from previous batch\ncreation requests. This is the default bucket created by\nDataproc on Compute Engine clusters. For more\ninformation, see\n[Dataproc staging and temp buckets](/dataproc/docs/concepts/configuring-clusters/staging-bucket).\n\nServerless for Apache Spark stores workload dependencies, config files, and\njob driver console output in the staging bucket.\n\nServerless for Apache Spark sets regional staging buckets in\n[Cloud Storage locations](/storage/docs/locations#location-r)\naccording to the Compute Engine zone where your workload is deployed,\nand then creates and manages these project-level, per-location buckets.\nServerless for Apache Spark-created staging buckets are shared among\nworkloads in the same region, and are created with a\nCloud Storage [soft delete retention](/storage/docs/soft-delete#retention-duration)\nduration set to 0 seconds.\n| To locate the Dataproc default staging bucket, in the Google Cloud console, go to **[Cloud Storage](https://console.cloud.google.com/storage/browser)** and filter the results using the `dataproc-staging-` prefix."]]
