컬렉션을 사용해 정리하기
내 환경설정을 기준으로 콘텐츠를 저장하고 분류하세요.
BigQuery는 Google Cloud의 페타바이트급 규모의 경제적인 완전 관리형 분석 데이터 웨어하우스로, 거의 실시간으로 방대한 양의 데이터를 분석할 수 있습니다. BigQuery를 사용하면 설정하거나 관리할 인프라가 없으므로 GoogleSQL을 사용하여 유용한 정보를 찾는 데 집중하고 주문형 옵션과 정액제 옵션에서 유연하게 가격 책정 모델을 활용할 수 있습니다.
자세히 알아보기
무료로 시작하기
무료 크레딧 $300로 개념 증명 시작
-
Gemini 2.0 Flash Thinking 이용
-
AI API 및 BigQuery를 포함하여 인기 제품 월별 무료 사용량
-
자동 청구, 약정 없음
무료 제품 혜택 보기
20개가 넘는 항상 무료 제품을 계속 살펴보기
AI API, VM, 데이터 웨어하우스 등 일반적인 사용 사례에 20개가 넘는 무료 제품을 사용할 수 있습니다.
BigQuery 직접 사용해 보기
계정을 만들어 Google 제품의 실제 성능을 평가해 보세요.
신규 고객에게는 워크로드를 실행, 테스트, 배포하는 데 사용할 수 있는 $300의 무료 크레딧이 제공됩니다.
BigQuery 무료로 사용해 보기
달리 명시되지 않는 한 이 페이지의 콘텐츠에는 Creative Commons Attribution 4.0 라이선스에 따라 라이선스가 부여되며, 코드 샘플에는 Apache 2.0 라이선스에 따라 라이선스가 부여됩니다. 자세한 내용은 Google Developers 사이트 정책을 참조하세요. 자바는 Oracle 및/또는 Oracle 계열사의 등록 상표입니다.
최종 업데이트: 2025-02-18(UTC)
[[["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: 2025-02-18(UTC)"],[[["\u003cp\u003eBigQuery is a fully managed, petabyte-scale data warehouse service by Google Cloud, designed for running real-time analytics on massive datasets.\u003c/p\u003e\n"],["\u003cp\u003eIt offers flexible pricing models, including on-demand and flat-rate options, allowing users to optimize costs based on their needs.\u003c/p\u003e\n"],["\u003cp\u003eBigQuery provides comprehensive documentation and guides for various tasks, including quickstarts, table management, data loading, and machine learning integration.\u003c/p\u003e\n"],["\u003cp\u003eResources are available for users, covering topics like pricing, release notes, locations, cost control, troubleshooting, and support.\u003c/p\u003e\n"],["\u003cp\u003eTraining, use cases, and code samples are provided to assist users with data warehousing, data analysis, machine learning, and migrating data warehouses to BigQuery, along with showcasing code for various client-side integrations.\u003c/p\u003e\n"]]],[],null,["# BigQuery documentation\n======================\n\n[Read product documentation](/bigquery/docs/introduction)\nBigQuery is Google Cloud's fully managed, petabyte-scale, and\ncost-effective analytics data warehouse that lets you run analytics over\nvast amounts of data in near real time. With BigQuery, there's\nno infrastructure to set up or manage, letting you focus on finding meaningful\ninsights using GoogleSQL and taking advantage of flexible pricing models\nacross on-demand and flat-rate options.\n[Learn more](/bigquery/docs/introduction)\n[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\n Quickstarts:\n [Console](/bigquery/docs/quickstarts/query-public-dataset-console),\n\n [Command line](/bigquery/docs/quickstarts/load-data-bq),\n or\n [Client libraries](/bigquery/docs/quickstarts/quickstart-client-libraries)\n\n\n-\n\n [Creating and using tables](/bigquery/docs/tables)\n\n-\n\n [Introduction to partitioned tables](/bigquery/docs/partitioned-tables)\n\n-\n\n [Introduction to BigQuery ML](/bigquery/docs/bqml-introduction)\n\n-\n\n [Predefined roles and permissions](/bigquery/docs/access-control)\n\n-\n\n [Introduction to loading data](/bigquery/docs/loading-data)\n\n-\n\n [Loading CSV data from Cloud Storage](/bigquery/docs/loading-data-cloud-storage-csv)\n\n-\n\n [Exporting table data](/bigquery/docs/exporting-data)\n\n-\n\n [Create machine learning models in BigQuery ML](/bigquery/docs/create-machine-learning-model)\n\n-\n\n [Querying external data sources](/bigquery/external-data-sources)\n\n-\n\n [Introduction to vector search](/bigquery/docs/vector-search-intro)\n\nfind_in_page\n\n### Reference\n\n-\n\n [Functions in GoogleSQL](/bigquery/docs/reference/standard-sql/functions-all)\n\n-\n\n [Operators in GoogleSQL](/bigquery/docs/reference/standard-sql/operators)\n\n-\n\n [Conditional expressions in GoogleSQL](/bigquery/docs/reference/standard-sql/conditional_expressions)\n\n-\n\n [Date functions in GoogleSQL](/bigquery/docs/reference/standard-sql/date_functions)\n\n-\n\n [Query syntax in GoogleSQL](/bigquery/docs/reference/standard-sql/query-syntax)\n\n-\n\n [String functions in GoogleSQL](/bigquery/docs/reference/standard-sql/string_functions)\n\n-\n\n [Using the bq command-line tool](/bigquery/docs/bq-command-line-tool)\n\n-\n\n [End-to-end journey for machine learning models](/bigquery/docs/reference/standard-sql/bigqueryml-syntax-e2e-journey)\n\n-\n\n [BigQuery API Client Libraries](/bigquery/docs/reference/libraries)\n\n-\n\n [Creating and training models](/bigquery/docs/reference/standard-sql/bigqueryml-syntax-create)\n\n-\n\n [Public datasets](/bigquery/public-data)\n\n-\n\n [Feature preprocessing](/bigquery/docs/reference/standard-sql/bigqueryml-syntax-preprocess-overview)\n\ninfo\n\n### Resources\n\n-\n\n [Pricing](/bigquery/pricing)\n\n-\n\n [Release notes](/bigquery/docs/release-notes)\n\n-\n\n [Locations](/bigquery/docs/locations)\n\n-\n\n [Getting support](/bigquery/docs/getting-support)\n\n-\n\n [Quotas and limits](/bigquery/quotas)\n\n-\n\n [Controlling costs](/bigquery/docs/controlling-costs)\n\n-\n\n [Creating custom cost controls](/bigquery/docs/custom-quotas)\n\n-\n\n [Troubleshooting BigQuery quota errors](/bigquery/docs/troubleshoot-quotas)\n\n-\n\n [Billing questions](/bigquery/docs/billing-questions)\n\nRelated resources\n-----------------\n\nTraining and tutorials \nUse cases \nCode samples \nExplore self-paced training, use cases, reference architectures, and code samples with examples of how to use and connect Google Cloud services. Training \nTraining and tutorials\n\n### Data Warehouse with BigQuery Jump Start Solution\n\n\nDeploy and use a sample data warehouse with BigQuery.\n\n\n[Learn more](https://cloud.google.com/architecture/big-data-analytics/data-warehouse) \nTraining \nTraining and tutorials\n\n### BigQuery for Data Warehousing\n\n\nLearn best practices for extracting, transforming, and loading your data into Google Cloud with BigQuery.\n\n\n[Learn more](https://www.cloudskillsboost.google/course_templates/679) \nTraining \nTraining and tutorials\n\n### Preprocessing BigQuery Data with PySpark on Dataproc\n\n\nLearn to create a data processing pipeline using Apache Spark with Dataproc on Google Cloud. It is a common use case in data science and data engineering to read data from one storage location, perform transformations on it and write it into another storage location.\n\n\n[Learn more](https://codelabs.developers.google.com/codelabs/pyspark-bigquery/) \nTraining \nTraining and tutorials\n\n### BigQuery For Data Analysis\n\n\nLearn how to query, ingest, optimize, visualize, and even build machine learning models in SQL inside of BigQuery.\n\n\n[Learn more](https://www.cloudskillsboost.google/course_templates/865) \nTraining \nTraining and tutorials\n\n### BigQuery for Marketing Analysts\n\n\nGet repeatable, scalable, and valuable insights into your data by learning how to query it using BigQuery.\n\n\n[Learn more](https://www.cloudskillsboost.google/course_templates/678) \nTraining \nTraining and tutorials\n\n### BigQuery for Machine Learning\n\n\nExperiment with different model types in BigQuery Machine Learning, and learn what makes a good model.\n\n\n[Learn more](https://www.cloudskillsboost.google/course_templates/680) \nUse case \nUse cases\n\n### Migrating data warehouses to BigQuery\n\n\nLearn patterns and recommendations for transitioning your on-premises data warehouse to BigQuery.\n\nMigration Patterns BigQuery\n\n\u003cbr /\u003e\n\n[Learn more](/solutions/migration/dw2bq/dw-bq-migration-overview) \nUse case \nUse cases\n\n### Visualizing BigQuery data in a Jupyter notebook\n\n\nUse the BigQuery Python client library and Pandas in a Jupyter notebook to visualize data in a BigQuery sample table.\n\n\n[Learn more](/bigquery/docs/visualize-jupyter) \nCode sample \nCode Samples\n\n### Client: Create credentials with scopes\n\n\nCreate credentials with Drive and BigQuery API scopes.\n\n\n[Get started](/bigquery/docs/samples/bigquery-auth-drive-scope) \nCode sample \nCode Samples\n\n### Client: Create credentials with application default credentials\n\n\nCreate a BigQuery client using application default credentials.\n\n\n[Get started](/bigquery/docs/samples/bigquery-client-default-credentials) \nCode sample \nCode Samples\n\n### Client: Create with service account key\n\n\nCreate a BigQuery client using a service account key file.\n\n\n[Get started](/bigquery/docs/samples/bigquery-client-json-credentials) \nCode sample \nCode Samples\n\n### Python samples\n\n\nWorking with BigQuery with the Google Cloud Python client library\n\n\n[Open GitHub\narrow_forward](https://github.com/googleapis/python-bigquery/tree/main/samples) \nCode sample \nCode Samples\n\n### Node.js samples\n\n\nSamples for the Node.js client library sfor BigQuery\n\n\n[Open GitHub\narrow_forward](https://github.com/googleapis/nodejs-bigquery/tree/main/samples) \nCode sample \nCode Samples\n\n### C# simple sample\n\n\nA simple C# program and code snippets for interacting with BigQuery\n\n\n[Open GitHub\narrow_forward](https://github.com/GoogleCloudPlatform/dotnet-docs-samples/tree/master/bigquery/api) \nCode sample \nCode Samples\n\n### BigQuery and Cloud Monitoring on App Engine with Java 8\n\n\nThis API Showcase demonstrates how to run an App Engine standard environment application with dependencies on both BigQuery and Cloud Monitoring.\n\n\n[Open GitHub\narrow_forward](https://github.com/GoogleCloudPlatform/java-docs-samples/tree/main/appengine-java8/bigquery) \nCode sample \nCode Samples\n\n### All samples\n\n\nBrowse all samples for BigQuery\n\n\n[Get started](/bigquery/docs/samples)\n\nRelated videos\n--------------\n\n### Try BigQuery for yourself\n\nCreate an account to evaluate how our products perform in real-world scenarios. \nNew customers also get $300 in free credits to run, test, and deploy workloads. \n[Try BigQuery free](https://console.cloud.google.com/freetrial)"]]
