Create a table definition file for an external data source | BigQuery | Google Cloud
Send feedback Stay organized with collections Save and categorize content based on your preferences. Create a table definition file for an external data source This page describes how to create a table definition file for an external data source. An external data source is a data source that you can query directly even though the data is not stored in BigQuery. A table definition file contains an
Lexical structure and syntax | BigQuery | Google Cloud
Send feedback Lexical structure and syntax Stay organized with collections Save and categorize content based on your preferences. A GoogleSQL statement comprises a series of tokens. Tokens include identifiers, quoted identifiers, literals, keywords, operators, and special characters. You can separate tokens with comments or whitespace such as spaces, backspaces, tabs, or newlines. Identifiers Iden
Analyzing Audit Logs Using BigQuery | BigQuery | Google Cloud
Send feedback Stay organized with collections Save and categorize content based on your preferences. BigQuery audit logs overview Cloud Audit Logs are a collection of logs provided by Google Cloud that provide insight into operational concerns related to your use of Google Cloud services. This page provides details about BigQuery specific log information, and it demonstrates how to use BigQuery to
Load and query data with the bq tool | BigQuery | Google Cloud
Send feedback Stay organized with collections Save and categorize content based on your preferences. Load and query data with the bq tool Learn how to create a dataset, load sample data, and query tables with the bq command-line tool. To follow step-by-step guidance for this task directly in the Google Cloud console, click Guide me: Guide me Before you begin Sign in to your Google Cloud account. I
Specify nested and repeated columns in table schemas | BigQuery | Google Cloud
Send feedback Stay organized with collections Save and categorize content based on your preferences. Specify nested and repeated columns in table schemas This page describes how to define a table schema with nested and repeated columns in BigQuery. For an overview of table schemas, see Specifying a schema. Define nested and repeated columns To create a column with nested data, set the data type of
The CREATE MODEL statement | BigQuery | Google Cloud
Send feedback Stay organized with collections Save and categorize content based on your preferences. The CREATE MODEL statement To create a model in BigQuery, use the BigQuery ML CREATE MODEL statement. This statement is similar to the CREATE TABLE DDL statement. When you run a query that contains a CREATE MODEL statement, a query job is generated for you that processes the query. For information
Use BigQuery ML to predict penguin weight | Google Cloud
Send feedback Use BigQuery ML to predict penguin weight Stay organized with collections Save and categorize content based on your preferences. In this tutorial, you use a linear regression model in BigQuery ML to predict the weight of a penguin based on the penguin's demographic information. A linear regression is a type of regression model that generates a continuous value from a linear combinati
Enable the BigQuery sandbox | Google Cloud
Send feedback Stay organized with collections Save and categorize content based on your preferences. Enable the BigQuery sandbox The BigQuery sandbox lets you explore limited BigQuery capabilities at no cost to confirm whether BigQuery fits your needs. The BigQuery sandbox lets you experience BigQuery without providing a credit card or creating a billing account for your project. If you already cr
Create and use clustered tables | BigQuery | Google Cloud
Send feedback Stay organized with collections Save and categorize content based on your preferences. Create and use clustered tables This document describes how to create and use clustered tables in BigQuery. For an overview of clustered table support in BigQuery, see Introduction to clustered tables. Create clustered tables You can create a clustered table by using the following methods: Create a
Loading ORC data from Cloud Storage | BigQuery | Google Cloud
Send feedback Stay organized with collections Save and categorize content based on your preferences. Loading ORC data from Cloud Storage This page provides an overview of loading ORC data from Cloud Storage into BigQuery. ORC is an open source column-oriented data format that is widely used in the Apache Hadoop ecosystem. When you load ORC data from Cloud Storage, you can load the data into a new
Introduction to clustered tables | BigQuery | Google Cloud
Send feedback Stay organized with collections Save and categorize content based on your preferences. Introduction to clustered tables Clustered tables in BigQuery are tables that have a user-defined column sort order using clustered columns. Clustered tables can improve query performance and reduce query costs. In BigQuery, a clustered column is a user-defined table property that sorts storage blo
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地理空間分析の概要 | BigQuery | Google Cloud
パラメータ化されたクエリの実行 | BigQuery | Google Cloud
クラスタ化テーブルの作成と使用 | BigQuery | Google Cloud
テーブル スキーマでネストされた列と繰り返し列を指定する | BigQuery | Google Cloud
ローカル データソースから BigQuery にデータを読み込む | BigQuery | Google Cloud
BigQuery ML でペンギンの体重を予測する | Google Cloud
BigQuery で承認済みビューを作成する | BigQuery | Google Cloud
API のパフォーマンスに関するヒント | BigQuery | Google Cloud
Datetime functions | BigQuery | Google Cloud