@google-cloud/bigquery

What is @google-cloud/bigquery?

@google-cloud/bigquery is a Node.js client library for Google BigQuery, a fully-managed, serverless data warehouse that enables scalable analysis over petabytes of data. This package allows you to interact with BigQuery to run queries, manage datasets, tables, and jobs, and perform data manipulations.

What are @google-cloud/bigquery's main functionalities?

Running Queries

This feature allows you to run SQL queries against your BigQuery datasets. The code sample demonstrates how to run a simple query to select names and ages from a table where the age is greater than 30.

const {BigQuery} = require('@google-cloud/bigquery');
const bigquery = new BigQuery();
async function query() {
  const query = 'SELECT name, age FROM `my-dataset.my-table` WHERE age > 30';
  const options = { query: query, location: 'US' };
  const [rows] = await bigquery.query(options);
  console.log('Rows:', rows);
}
query();

Managing Datasets

This feature allows you to create and manage datasets in BigQuery. The code sample demonstrates how to create a new dataset named 'my_new_dataset'.

const {BigQuery} = require('@google-cloud/bigquery');
const bigquery = new BigQuery();
async function createDataset() {
  const [dataset] = await bigquery.createDataset('my_new_dataset');
  console.log(`Dataset ${dataset.id} created.`);
}
createDataset();

Managing Tables

This feature allows you to create and manage tables within datasets. The code sample demonstrates how to create a new table named 'my_new_table' within the 'my_new_dataset' dataset.

const {BigQuery} = require('@google-cloud/bigquery');
const bigquery = new BigQuery();
async function createTable() {
  const dataset = bigquery.dataset('my_new_dataset');
  const [table] = await dataset.createTable('my_new_table');
  console.log(`Table ${table.id} created.`);
}
createTable();

Loading Data

This feature allows you to load data from various sources into BigQuery tables. The code sample demonstrates how to load data from a local CSV file into a table named 'my_new_table' within the 'my_new_dataset' dataset.

const {BigQuery} = require('@google-cloud/bigquery');
const bigquery = new BigQuery();
async function loadData() {
  const dataset = bigquery.dataset('my_new_dataset');
  const table = dataset.table('my_new_table');
  const [job] = await table.load('local-file.csv');
  console.log(`Job ${job.id} completed.`);
}
loadData();

Other packages similar to @google-cloud/bigquery

aws-sdk

The aws-sdk package is the official AWS SDK for JavaScript, which allows you to interact with various AWS services, including Amazon Redshift, a data warehouse service similar to Google BigQuery. While aws-sdk provides a broader range of functionalities across different AWS services, it can be used to perform similar data warehousing tasks as @google-cloud/bigquery.

azure-sdk-for-js

The azure-sdk-for-js package is the official Azure SDK for JavaScript, which allows you to interact with various Azure services, including Azure Synapse Analytics, a data warehousing service similar to Google BigQuery. Like aws-sdk, azure-sdk-for-js offers a wide range of functionalities across different Azure services, including data warehousing capabilities.

snowflake-sdk

The snowflake-sdk package is the official Node.js driver for Snowflake, a cloud-based data warehousing service. It provides functionalities to connect to Snowflake, run queries, and manage data, similar to what @google-cloud/bigquery offers for Google BigQuery.

README

Google BigQuery: Node.js Client

Node.js idiomatic client for BigQuery.

BigQuery is Google's fully managed, petabyte scale, low cost analytics data warehouse. BigQuery is NoOps—there is no infrastructure to manage and you don't need a database administrator—so you can focus on analyzing data to find meaningful insights, use familiar SQL, and take advantage of our pay-as-you-go model.

• BigQuery Node.js Client API Reference
• github.com/googleapis/nodejs-bigquery
• BigQuery Documentation

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
  • Installing the client library
  • Using the client library
• Samples
• Versioning
• Contributing
• License

Quickstart

Before you begin

1. Select or create a Cloud Platform project.

   Go to the projects page

2. Enable billing for your project.

   Enable billing

3. Enable the Google BigQuery API.

   Enable the API

4. Set up authentication with a service account so you can access the API from your local workstation.

Installing the client library

npm install --save @google-cloud/bigquery

Using the client library

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

// Your Google Cloud Platform project ID
const projectId = 'YOUR_PROJECT_ID';

// Instantiates a client
const bigquery = BigQuery({
  projectId: projectId,
});

// The name for the new dataset
const datasetName = 'my_new_dataset';

// Creates the new dataset
bigquery
  .createDataset(datasetName)
  .then(results => {
    const dataset = results[0];

    console.log(`Dataset ${dataset.id} created.`);
  })
  .catch(err => {
    console.error('ERROR:', err);
  });

Samples

Samples are in the samples/ directory. The samples' README.md has instructions for running the samples.

Sample	Source Code	Try it
Datasets	source code
Tables	source code
Queries	source code

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

Versioning

This library follows Semantic Versioning.

This library is considered to be in beta. This means it is expected to be mostly stable while we work toward a general availability release; however, complete stability is not guaranteed. We will address issues and requests against beta libraries with a high priority.

More Information: Google Cloud Platform Launch Stages

Contributing

Contributions welcome! See the Contributing Guide.

License

Apache Version 2.0

See LICENSE