이 페이지에서는 Spanner Data Boost를 지원하는 Spanner API를 나열하고 Data Boost를 사용하는 샘플 코드를 보는 방법을 설명합니다. Data Boost를 사용하면 프로비저닝된 Spanner 인스턴스의 기존 워크로드에 거의 영향을 주지 않고 대규모 분석 쿼리를 실행할 수 있습니다.
시작하기 전에
애플리케이션을 실행하는 주 구성원(예: 서비스 계정)에게 spanner.databases.useDataBoost Identity and Access Management(IAM) 권한이 있어야 합니다. 자세한 내용은 IAM으로 액세스 제어를 참조하세요.
API
Data Boost를 사용한 파티션을 나눈 읽기의 경우 다음 Spanner API에 Data Boost를 사용 설정하는 옵션이 있습니다.
ExecuteSql 및 read는 해당 응답에서 데이터가 10MB로 제한되기 때문에 애플리케이션에서 ExecuteStreamingSql 및 streamingRead를 사용하는 것이 좋습니다.
샘플 코드
애플리케이션 코드에서 Data Boost를 사용하는 예시는 병렬 데이터 읽기를 참조하세요.
Google Cloud Spanner용 Apache Spark SQL Connect
Google Cloud Spanner용 Apache Spark SQL Connector는 Spanner Java 라이브러리를 사용하여 Google Cloud Spanner 테이블을 Spark의 DataFrame으로 읽을 수 있도록 지원합니다. Apache Spark SQL Connector에 대한 자세한 내용은 Google Cloud Spanner용 Apache Spark SQL Connector를 참조하세요.
[[["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: 2025-09-05(UTC)"],[],[],null,["# Use Data Boost in your applications\n\nThis page lists the Spanner APIs that support Spanner Data Boost and explains how to view sample code that uses Data Boost. With Data Boost, you can run large analytic queries with near-zero impact to existing workloads on the provisioned Spanner instance.\n\n\u003cbr /\u003e\n\nBefore you begin\n----------------\n\nEnsure that the principal (for example, the service account) that runs the\napplication has the\n`spanner.databases.useDataBoost` Identity and Access Management (IAM)\npermission. For more information, see\n[Access control with IAM](../iam).\n\nAPIs\n----\n\nFor partitioned reads with Data Boost, the following\nSpanner APIs have an option to enable Data Boost:\n\n- `ExecuteSql` [RPC](/spanner/docs/reference/rpc/google.spanner.v1#google.spanner.v1.Spanner.ExecuteSql) \\| [REST](/spanner/docs/reference/rest/v1/projects.instances.databases.sessions/executeSql)\n- `ExecuteStreamingSql` [RPC](/spanner/docs/reference/rpc/google.spanner.v1#google.spanner.v1.Spanner.ExecuteStreamingSql) \\| [REST](/spanner/docs/reference/rest/v1/projects.instances.databases.sessions/executeStreamingSql)\n- `read` [RPC](/spanner/docs/reference/rpc/google.spanner.v1#google.spanner.v1.Spanner.Read) \\| [REST](/spanner/docs/reference/rest/v1/projects.instances.databases.sessions/read)\n- `streamingRead` [RPC](/spanner/docs/reference/rpc/google.spanner.v1#google.spanner.v1.Spanner.StreamingRead) \\| [REST](/spanner/docs/reference/rest/v1/projects.instances.databases.sessions/streamingRead)\n\nWe recommend that you use `ExecuteStreamingSql` and `streamingRead` in your\napplications, because `ExecuteSql` and `read` are limited to 10 MB of\ndata in their responses.\n\nSample code\n-----------\n\nFor examples of using Data Boost in your application code, see\n[Read data in parallel](../reads#read_data_in_parallel).\n\nApache Spark SQL Connect for Google Cloud Spanner\n-------------------------------------------------\n\nThe Apache Spark SQL Connector for Google Cloud Spanner supports\nreading Google Cloud Spanner tables into Spark's DataFrames using\nthe Spanner Java library. For more information about the Apacha\nSpark SQL Connector, see [Apache Spark SQL connector for Google Cloud Spanner](https://github.com/GoogleCloudDataproc/spark-spanner-connector).\n\nWhat's next\n-----------\n\n- Learn about Data Boost in [Data Boost overview](/spanner/docs/databoost/databoost-overview).\n- [Monitor Data Boost usage](/spanner/docs/databoost/databoost-monitor)\n- [Monitor and manage Data Boost quota usage](/spanner/docs/databoost/databoost-quotas)"]]
