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Node.js client for Google Cloud BigQuery: A fast, economical and fully-managed enterprise data warehouse for large-scale data analytics.

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Google BigQuery Client Library for Node.js

A comprehensive list of changes in each version may be found in the CHANGELOG.

Read more about the client libraries for Cloud APIs, including the older Google APIs Client Libraries, in Client Libraries Explained.

Table of contents:

Quickstart

Before you begin

  1. Select or create a Cloud Platform project.
  2. Enable the Google BigQuery API.
  3. Set up authentication with a service account so you can access the API from your local workstation.

Installing the client library

npm install @google-cloud/bigquery

Using the client library

// Imports the Google Cloud client library
const {BigQuery} = require('@google-cloud/bigquery');

async function createDataset() {
  // Creates a client
  const bigqueryClient = new BigQuery();

  // Create the dataset
  const [dataset] = await bigqueryClient.createDataset(datasetName);
  console.log(`Dataset ${dataset.id} created.`);
}
createDataset();

Samples

Samples are in the samples/ directory. Each sample's README.md has instructions for running its sample.

Sample Source Code Try it
Add Column Load Append source code Open in Cloud Shell
Add Column Query Append source code Open in Cloud Shell
Add Empty Column source code Open in Cloud Shell
Auth View Tutorial source code Open in Cloud Shell
Browse Table source code Open in Cloud Shell
Cancel Job source code Open in Cloud Shell
Client JSON Credentials source code Open in Cloud Shell
Copy Table source code Open in Cloud Shell
Copy Table Multiple Source source code Open in Cloud Shell
Create Dataset source code Open in Cloud Shell
Create Job source code Open in Cloud Shell
Create Model source code Open in Cloud Shell
Create Routine source code Open in Cloud Shell
Create Routine DDL source code Open in Cloud Shell
Create Table source code Open in Cloud Shell
Create Table Clustered source code Open in Cloud Shell
Create Table Column ACL source code Open in Cloud Shell
Create Table Partitioned source code Open in Cloud Shell
Create Table Range Partitioned source code Open in Cloud Shell
Create View source code Open in Cloud Shell
Ddl Create View source code Open in Cloud Shell
Delete Dataset source code Open in Cloud Shell
Delete Label Dataset source code Open in Cloud Shell
Delete Label Table source code Open in Cloud Shell
Delete Model source code Open in Cloud Shell
Delete Routine source code Open in Cloud Shell
Delete Table source code Open in Cloud Shell
Extract Table Compressed source code Open in Cloud Shell
Extract Table JSON source code Open in Cloud Shell
Extract Table To GCS source code Open in Cloud Shell
Get Dataset source code Open in Cloud Shell
Get Dataset Labels source code Open in Cloud Shell
Get Job source code Open in Cloud Shell
BigQuery Get Model source code Open in Cloud Shell
Get Routine source code Open in Cloud Shell
BigQuery Get Table source code Open in Cloud Shell
Get Table Labels source code Open in Cloud Shell
Get View source code Open in Cloud Shell
Insert Rows As Stream source code Open in Cloud Shell
Inserting Data Types source code Open in Cloud Shell
BigQuery Label Dataset source code Open in Cloud Shell
Label Table source code Open in Cloud Shell
List Datasets source code Open in Cloud Shell
List Datasets By Label source code Open in Cloud Shell
List Jobs source code Open in Cloud Shell
BigQuery List Models source code Open in Cloud Shell
BigQuery List Models Streaming source code Open in Cloud Shell
List Routines source code Open in Cloud Shell
List Tables source code Open in Cloud Shell
Load CSV From GCS source code Open in Cloud Shell
Load CSV From GCS Autodetect source code Open in Cloud Shell
Load CSV From GCS Truncate source code Open in Cloud Shell
Load JSON From GCS source code Open in Cloud Shell
Load JSON From GCS Autodetect source code Open in Cloud Shell
Load JSON From GCS Truncate source code Open in Cloud Shell
Load Local File source code Open in Cloud Shell
Load Orc From GCS Truncate source code Open in Cloud Shell
Load Parquet From GCS Truncate source code Open in Cloud Shell
Load Table Clustered source code Open in Cloud Shell
Load Table GCS Avro source code Open in Cloud Shell
Load Table GCS Avro Truncate source code Open in Cloud Shell
Load Table GCSORC source code Open in Cloud Shell
Load Table GCS Parquet source code Open in Cloud Shell
Load Table Partitioned source code Open in Cloud Shell
Load Table URI Firestore source code Open in Cloud Shell
Nested Repeated Schema source code Open in Cloud Shell
Query source code Open in Cloud Shell
Query Batch source code Open in Cloud Shell
Query Clustered Table source code Open in Cloud Shell
Query Destination Table source code Open in Cloud Shell
Query Disable Cache source code Open in Cloud Shell
Query Dry Run source code Open in Cloud Shell
Query External GCS Perm source code Open in Cloud Shell
Query External GCS Temp source code Open in Cloud Shell
Query Legacy source code Open in Cloud Shell
Query Legacy Large Results source code Open in Cloud Shell
Query Pagination source code Open in Cloud Shell
Query Params Arrays source code Open in Cloud Shell
Query Params Named source code Open in Cloud Shell
Query Params Named Types source code Open in Cloud Shell
Query Params Positional source code Open in Cloud Shell
Query Params Positional Types source code Open in Cloud Shell
Query Params Structs source code Open in Cloud Shell
Query Params Timestamps source code Open in Cloud Shell
Query Stack Overflow source code Open in Cloud Shell
Quickstart source code Open in Cloud Shell
Relax Column source code Open in Cloud Shell
Relax Column Load Append source code Open in Cloud Shell
Relax Column Query Append source code Open in Cloud Shell
Remove Table Clustering source code Open in Cloud Shell
Set User Agent source code Open in Cloud Shell
Undelete Table source code Open in Cloud Shell
Update Dataset Access source code Open in Cloud Shell
Update Dataset Description source code Open in Cloud Shell
Update Dataset Expiration source code Open in Cloud Shell
BigQuery Update Model source code Open in Cloud Shell
Update Routine source code Open in Cloud Shell
Update Table Column ACL source code Open in Cloud Shell
Update Table Description source code Open in Cloud Shell
Update Table Expiration source code Open in Cloud Shell
Update View Query source code Open in Cloud Shell

The Google BigQuery Node.js Client API Reference documentation also contains samples.

Supported Node.js Versions

Our client libraries follow the Node.js release schedule. Libraries are compatible with all current active and maintenance versions of Node.js.

Client libraries targeting some end-of-life versions of Node.js are available, and can be installed via npm dist-tags. The dist-tags follow the naming convention legacy-(version).

Legacy Node.js versions are supported as a best effort:

  • Legacy versions will not be tested in continuous integration.
  • Some security patches may not be able to be backported.
  • Dependencies will not be kept up-to-date, and features will not be backported.

Legacy tags available

  • legacy-8: install client libraries from this dist-tag for versions compatible with Node.js 8.

Versioning

This library follows Semantic Versioning.

This library is considered to be General Availability (GA). This means it is stable; the code surface will not change in backwards-incompatible ways unless absolutely necessary (e.g. because of critical security issues) or with an extensive deprecation period. Issues and requests against GA libraries are addressed with the highest priority.

More Information: Google Cloud Platform Launch Stages

Contributing

Contributions welcome! See the Contributing Guide.

Please note that this README.md, the samples/README.md, and a variety of configuration files in this repository (including .nycrc and tsconfig.json) are generated from a central template. To edit one of these files, make an edit to its templates in directory.

License

Apache Version 2.0

See LICENSE

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Node.js client for Google Cloud BigQuery: A fast, economical and fully-managed enterprise data warehouse for large-scale data analytics.

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