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Examples

Some short examples

Get a table from an Arrow file on disk (in IPC format)​

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
*/

Create a Table from JavaScript arrays​

import {Table, FloatVector, DateVector} from 'apache-arrow';

const LENGTH = 2000;

const rainAmounts = Float32Array.from({length: LENGTH}, () =>
  Number((Math.random() * 20).toFixed(1))
);

const rainDates = Array.from(
  {length: LENGTH},
  (_, i) => new Date(Date.now() - 1000 * 60 * 60 * 24 * i)
);

const rainfall = Table.new(
  [FloatVector.from(rainAmounts), DateVector.from(rainDates)],
  ['precipitation', 'date']
);

Load data with fetch​

import {Table} from 'apache-arrow';

const table = await Table.from(fetch('/simple.arrow'));
console.log(table.toString());

Columns look like JS Arrays​

import {readFileSync} from 'fs';
import {Table} from 'apache-arrow';

const table = Table.from(['latlong/schema.arrow', 'latlong/records.arrow'].map(readFileSync));

const column = table.getColumn('origin_lat');

// Copy the data into a TypedArray
const typed = column.toArray();
assert(typed instanceof Float32Array);

for (let i = -1, n = column.length; ++i < n; ) {
  assert(column.get(i) === typed[i]);
}