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apache-arrow

Apache Arrow in JS

Build Status Coverage Status

Arrow is a set of technologies that enable big-data systems to process and transfer data quickly.

install apache-arrow from npm

npm install apache-arrow

(read about how we package apache-arrow below)

Powering Columnar In-Memory Analytics

Apache Arrow is a columnar memory layout specification for encoding vectors and table-like containers of flat and nested data. The Arrow spec aligns columnar data in memory to minimize cache misses and take advantage of the latest SIMD (Single input multiple data) and GPU operations on modern processors.

Apache Arrow is the emerging standard for large in-memory columnar data (Spark, Pandas, Drill, ...). By standardizing on a common binary interchange format, big data systems can reduce the costs and friction associated with cross-system communication.

Related Projects

  • GoAI -- Arrow-powered GPU analytics
  • rxjs-mapd -- A MapD Core node-driver that returns query results as Arrow columns

Usage

Get a table from an Arrow file on disk

import { readFileSync } from 'fs';
import { Table } from 'apache-arrow';
 
const arrow = readFileSync('simple.arrow');
const table = Table.from([arrow]);
 
console.log(table.toString());
 
/*
 foo,  bar,  baz
   1,    1,   aa
null, null, null
   3, null, null
   4,    4,  bbb
   5,    5, cccc
*/

Create a Table when the Arrow file is split across buffers

import { readFileSync } from 'fs';
import { Table } from 'apache-arrow';
 
const table = Table.from([
    'latlong/schema.arrow',
    'latlong/records.arrow'
].map((file) => readFileSync(file)));
 
console.log(table.toString());
 
/*
        origin_lat,         origin_lon
35.393089294433594,  -97.6007308959961
35.393089294433594,  -97.6007308959961
35.393089294433594,  -97.6007308959961
29.533695220947266, -98.46977996826172
29.533695220947266, -98.46977996826172
*/

Columns are what you'd expect

import { readFileSync } from 'fs';
import { Table } from 'apache-arrow';
 
const table = Table.from([
    'latlong/schema.arrow',
    'latlong/records.arrow'
].map(readFileSync));
 
const column = table.col('origin_lat');
const typed = column.slice();
 
assert(typed instanceof Float32Array);
 
for (let i = -1, n = column.length; ++i < n;) {
    assert(column.get(i) === typed[i]);
}

Usage with MapD Core

import MapD from 'rxjs-mapd';
import { Table } from 'apache-arrow';
 
const port = 9091;
const host = `localhost`;
const db = `mapd`;
const user = `mapd`;
const password = `HyperInteractive`;
 
MapD.open(host, port)
  .connect(db, user, password)
  .flatMap((session) =>
    // queryDF returns Arrow buffers
    session.queryDF(`
      SELECT origin_city
      FROM flights
      WHERE dest_city ILIKE 'dallas'
      LIMIT 5`
    ).disconnect()
  )
  .map(([schema, records]) =>
    // Create Arrow Table from results
    Table.from(schema, records))
  .map((table) =>
    // Stringify the table to CSV with row numbers
    table.toString({ index: true }))
  .subscribe((csvStr) =>
    console.log(csvStr));
/*
Index,   origin_city
    0, Oklahoma City
    1, Oklahoma City
    2, Oklahoma City
    3,   San Antonio
    4,   San Antonio
*/

Getting involved

See develop.md

Even if you do not plan to contribute to Apache Arrow itself or Arrow integrations in other projects, we'd be happy to have you involved:

We prefer to receive contributions in the form of GitHub pull requests. Please send pull requests against the github.com/apache/arrow repository.

If you are looking for some ideas on what to contribute, check out the JIRA issues for the Apache Arrow project. Comment on the issue and/or contact dev@arrow.apache.org with your questions and ideas.

If you’d like to report a bug but don’t have time to fix it, you can still post it on JIRA, or email the mailing list dev@arrow.apache.org

Packaging

apache-arrow is written in TypeScript, but the project is compiled to multiple JS versions and common module formats.

The base apache-arrow package includes all the compilation targets for convenience, but if you're conscientious about your node_modules footprint, we got you.

The targets are also published under the @apache-arrow namespace:

npm install apache-arrow # <-- combined es5/CommonJS + UMD, es2015/ESModules + UMD, and TypeScript package 
npm install @apache-arrow/ts # standalone TypeScript package 
npm install @apache-arrow/es5-cjs # standalone es5/CommonJS package 
npm install @apache-arrow/es5-esm # standalone es5/ESModules package 
npm install @apache-arrow/es5-umd # standalone es5/UMD package 
npm install @apache-arrow/es2015-cjs # standalone es2015/CommonJS package 
npm install @apache-arrow/es2015-esm # standalone es2015/ESModules package 
npm install @apache-arrow/es2015-umd # standalone es2015/UMD package 
npm install @apache-arrow/esnext-esm # standalone esNext/CommonJS package 
npm install @apache-arrow/esnext-esm # standalone esNext/ESModules package 
npm install @apache-arrow/esnext-umd # standalone esNext/UMD package 

Why we package like this

The JS community is a diverse group with a varied list of target environments and tool chains. Publishing multiple packages accommodates projects of all stripes.

If you think we missed a compilation target and it's a blocker for adoption, please open an issue.

License

Apache 2.0