This page shows how to get started with the Cloud Client Libraries for the BigQuery API. Read more about the client libraries for Cloud APIs, including the older Google API Client Libraries, in Client Libraries Explained.
Install the client library
C#
For more information, see Setting Up a C# Development Environment.
Install-Package Google.Cloud.BigQuery.V2 -Pre
Go
For more information, see Setting Up a Go Development Environment.
go get cloud.google.com/go/bigquery
Java
For more information, see Setting Up a Java Development Environment.
If you are using Maven, add
the following to your pom.xml
file. For more information about
BOMs, see The Google Cloud Platform Libraries BOM.
If you are using Gradle, add the following to your dependencies:
If you are using sbt, add the following to your dependencies:
If you're using Visual Studio Code, IntelliJ, or Eclipse, you can add client libraries to your project using the following IDE plugins:
The plugins provide additional functionality, such as key management for service accounts. Refer to each plugin's documentation for details.
Node.js
For more information, see Setting Up a Node.js Development Environment.
npm install --save @google-cloud/bigquery
PHP
For more information, see Using PHP on Google Cloud.
composer require google/cloud-bigquery
Python
For more information, see Setting Up a Python Development Environment.
pip install --upgrade google-cloud-bigquery
Ruby
For more information, see Setting Up a Ruby Development Environment.
gem install google-cloud-bigquery
Set up authentication
When you use client libraries, you use Application Default Credentials (ADC) to authenticate. For information about setting up ADC, see Provide credentials for Application Default Credentials. For information about using ADC with client libraries, see Authenticate using client libraries.
Use the client library
The following example shows how to initialize a client and perform a query on a BigQuery API public dataset.
C#
Before trying this sample, follow the C# setup instructions in the BigQuery API quickstart using client libraries. For more information, see the BigQuery API C# API reference documentation.
Go
Before trying this sample, follow the Go setup instructions in the BigQuery API quickstart using client libraries. For more information, see the BigQuery API Go API reference documentation.
Java
Before trying this sample, follow the Java setup instructions in the BigQuery API quickstart using client libraries. For more information, see the BigQuery API Java API reference documentation.
Node.js
Before trying this sample, follow the Node.js setup instructions in the BigQuery API quickstart using client libraries. For more information, see the BigQuery API Node.js API reference documentation.
PHP
Before trying this sample, follow the PHP setup instructions in the BigQuery API quickstart using client libraries. For more information, see the BigQuery API PHP API reference documentation.
Python
Before trying this sample, follow the Python setup instructions in the BigQuery API quickstart using client libraries. For more information, see the BigQuery API Python API reference documentation.
Ruby
Before trying this sample, follow the Ruby setup instructions in the BigQuery API quickstart using client libraries. For more information, see the BigQuery API Ruby API reference documentation.
Additional resources
C#
Go
Java
Node.js
PHP
Python
Ruby
Third-party BigQuery API client libraries
In addition to the Google-supported client libraries listed in the tables above, a set of third-party libraries are available.
Language | Library |
---|---|
Python | pandas-gbq (migration guide) |
R | bigrquery, BigQueryR |
Scala | spark-bigquery-connector |
What's next?
- View available BigQuery code samples.
- Create a simple application using the client libraries.
- Visualize BigQuery API public data using a Jupyter notebook.
Try it for yourself
If you're new to Google Cloud, create an account to evaluate how BigQuery performs in real-world scenarios. New customers also get $300 in free credits to run, test, and deploy workloads.
Try BigQuery free