์ปฌ๋ ์
์ ์ฌ์ฉํด ์ ๋ฆฌํ๊ธฐ
๋ด ํ๊ฒฝ์ค์ ์ ๊ธฐ์ค์ผ๋ก ์ฝํ
์ธ ๋ฅผ ์ ์ฅํ๊ณ ๋ถ๋ฅํ์ธ์.
BigQuery๋ Google Cloud์ ํํ๋ฐ์ดํธ๊ธ ๊ท๋ชจ์ ๊ฒฝ์ ์ ์ธ ์์ ๊ด๋ฆฌํ ๋ถ์ ๋ฐ์ดํฐ ์จ์ดํ์ฐ์ค๋ก, ๊ฑฐ์ ์ค์๊ฐ์ผ๋ก ๋ฐฉ๋ํ ์์ ๋ฐ์ดํฐ๋ฅผ ๋ถ์ํ ์ ์์ต๋๋ค. BigQuery๋ฅผ ์ฌ์ฉํ๋ฉด ์ค์ ํ๊ฑฐ๋ ๊ด๋ฆฌํ ์ธํ๋ผ๊ฐ ์์ผ๋ฏ๋ก GoogleSQL์ ์ฌ์ฉํ์ฌ ์ ์ฉํ ์ ๋ณด๋ฅผ ์ฐพ๋ ๋ฐ ์ง์คํ๊ณ ์ฃผ๋ฌธํ ์ต์
๊ณผ ์ ์ก์ ์ต์
์์ ์ ์ฐํ๊ฒ ๊ฐ๊ฒฉ ์ฑ
์ ๋ชจ๋ธ์ ํ์ฉํ ์ ์์ต๋๋ค.
์์ธํ ์์๋ณด๊ธฐ
๋ฌด๋ฃ๋ก ์์ํ๊ธฐ
๋ฌด๋ฃ ํฌ๋ ๋ง $300๋ก ๊ฐ๋
์ฆ๋ช
์์
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Gemini 2.0 Flash Thinking ์ด์ฉ
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AI API ๋ฐ BigQuery๋ฅผ ํฌํจํ์ฌ ์ธ๊ธฐ ์ ํ ์๋ณ ๋ฌด๋ฃ ์ฌ์ฉ๋
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์๋ ์ฒญ๊ตฌ, ์ฝ์ ์์
๋ฌด๋ฃ ์ ํ ํํ ๋ณด๊ธฐ
20๊ฐ๊ฐ ๋๋ ํญ์ ๋ฌด๋ฃ ์ ํ์ ๊ณ์ ์ดํด๋ณด๊ธฐ
AI API, VM, ๋ฐ์ดํฐ ์จ์ดํ์ฐ์ค ๋ฑ ์ผ๋ฐ์ ์ธ ์ฌ์ฉ ์ฌ๋ก์ 20๊ฐ๊ฐ ๋๋ ๋ฌด๋ฃ ์ ํ์ ์ฌ์ฉํ ์ ์์ต๋๋ค.
BigQuery ์ง์ ์ฌ์ฉํด ๋ณด๊ธฐ
๊ณ์ ์ ๋ง๋ค์ด Google ์ ํ์ ์ค์ ์ฑ๋ฅ์ ํ๊ฐํด ๋ณด์ธ์.
์ ๊ท ๊ณ ๊ฐ์๊ฒ๋ ์ํฌ๋ก๋๋ฅผ ์คํ, ํ
์คํธ, ๋ฐฐํฌํ๋ ๋ฐ ์ฌ์ฉํ ์ ์๋ $300์ ๋ฌด๋ฃ ํฌ๋ ๋ง์ด ์ ๊ณต๋ฉ๋๋ค.
BigQuery ๋ฌด๋ฃ๋ก ์ฌ์ฉํด ๋ณด๊ธฐ
๋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: 2025-02-18(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: 2025-02-18(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)"]]
