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Send feedback Stay organized with collections Save and categorize content based on your preferences. Legacy SQL data types This document details the data types supported by BigQuery's legacy SQL query syntax. The preferred query syntax for BigQuery is GoogleSQL. For information on data types in GoogleSQL, see the GoogleSQL data types. Legacy SQL data types Your data can include the following data
Send feedback Stay organized with collections Save and categorize content based on your preferences. Create and use tables This document describes how to create and use standard (built-in) tables in BigQuery. For information about creating other table types, see: Creating partitioned tables Creating and using clustered tables After creating a table, you can: Control access to your table data Get i
Send feedback Functions, operators, and conditionals Stay organized with collections Save and categorize content based on your preferences. This topic is a compilation of functions, operators, and conditional expressions. To learn more about how to call functions, function call rules, the SAFE prefix, and special types of arguments, see Function calls. OPERATORS AND CONDITIONALS Operators GoogleSQ
Send feedback Stay organized with collections Save and categorize content based on your preferences. Creating partitioned tables This page describes how to create partitioned tables in BigQuery. For an overview of partitioned tables, see Introduction to partitioned tables. Before you begin Grant Identity and Access Management (IAM) roles that give users the necessary permissions to perform each ta
Send feedback Stay organized with collections Save and categorize content based on your preferences. This document provides an overview of supported statements and SQL dialects in BigQuery. Overview GoogleSQL is an ANSI compliant Structured Query Language (SQL) which includes the following types of supported statements: Query statements, also known as Data Query Language (DQL) statements, are the
Send feedback Google Cloud setup checklist Stay organized with collections Save and categorize content based on your preferences. Before you run production workloads on Google Cloud, we recommend you configure an initial foundation to support your work. Google Cloud setup helps administrators configure Google Cloud for scalable workloads. The setup process guides you through an interactive procedu
Send feedback Stay organized with collections Save and categorize content based on your preferences. Introduction to external data sources This page provides an overview of querying data stored outside of BigQuery. An external data source is a data source that you can query directly from BigQuery, even though the data is not stored in BigQuery storage. For example, you might have data in a differe
Send feedback Stay organized with collections Save and categorize content based on your preferences. Introduction to loading data This document provides an overview of loading data into BigQuery. Overview There are several ways to ingest data into BigQuery: Batch load a set of data records. Stream individual records or batches of records. Use queries to generate new data and append or overwrite th
Send feedback Stay organized with collections Save and categorize content based on your preferences. BigQuery is a fully managed enterprise data warehouse that helps you manage and analyze your data with built-in features like machine learning, geospatial analysis, and business intelligence. BigQuery's serverless architecture lets you use SQL queries to answer your organization's biggest questions
Send feedback Stay organized with collections Save and categorize content based on your preferences. BigQuery public datasets A public dataset is any dataset that is stored in BigQuery and made available to the general public through the Google Cloud Public Dataset Program. The public datasets are datasets that BigQuery hosts for you to access and integrate into your applications. Google pays for
Send feedback Use the legacy streaming API Stay organized with collections Save and categorize content based on your preferences. This document describes how to stream data into BigQuery by using the legacy tabledata.insertAll method. For new projects, we recommend using the BigQuery Storage Write API instead of the tabledata.insertAll method. The Storage Write API has lower pricing and more robus
Send feedback Stay organized with collections Save and categorize content based on your preferences. Querying nested and repeated fields in legacy SQL This document details how to query nested and repeated data in legacy SQL query syntax. The preferred query syntax for BigQuery is GoogleSQL. For information on handling nested and repeated data in GoogleSQL, see the GoogleSQL migration guide. BigQu
Send feedback Stay organized with collections Save and categorize content based on your preferences. Batch loading data You can load data into BigQuery from Cloud Storage or from a local file as a batch operation. The source data can be in any of the following formats: Avro Comma-separated values (CSV) JSON (newline-delimited) ORC Parquet Datastore exports stored in Cloud Storage Firestore exports
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