High performance Zstandard decompression in a pure JavaScript, 8kB package
Import:
// I will assume that you use the following for the rest of this guide
import * as fzstd from 'fzstd';
If your environment doesn't support ES Modules (e.g. Node.js):
const fzstd = require('fzstd');
If you want to load from a CDN in the browser:
<!--
You should use either UNPKG or jsDelivr (i.e. only one of the following)
-->
<script src="https://unpkg.com/fzstd@0.1.1"></script>
<script src="https://cdn.jsdelivr.net/npm/fzstd@0.1.1/umd/index.js"></script>
<!-- Now, the global variable fzstd contains the library -->
<!-- If you're going buildless but want ESM, import from Skypack -->
<script type="module">
import * as fzstd from 'https://cdn.skypack.dev/fzstd@0.1.1?min';
</script>
If you are using Deno:
// Don't use the ?dts Skypack flag; it isn't necessary for Deno support
// The @deno-types comment adds TypeScript typings
// @deno-types="https://cdn.skypack.dev/fzstd@0.1.1/lib/index.d.ts"
import * as fzstd from 'https://cdn.skypack.dev/fzstd@0.1.1?min';
And use:
// This is an ArrayBuffer of data
const compressedBuf = await fetch('/compressedData.zst').then(
res => res.arrayBuffer()
);
// To use fzstd, you need a Uint8Array
const compressed = new Uint8Array(compressedBuf);
// Note that Node.js Buffers work just fine as well:
// const massiveFile = require('fs').readFileSync('aMassiveFile.txt');
const decompressed = fzstd.decompress(compressed);
// Second argument is optional: custom output buffer
const outBuf = new Uint8Array(100000);
// IMPORTANT: fzstd will assume the buffer is sufficiently sized, so it
// will yield corrupt data if the buffer is too small. It is highly
// recommended to only specify this if you know the maximum output size.
fzstd.decompress(compressed, outBuf);
You can also use data streams to minimize memory usage while decompressing.
let outChunks = [];
const stream = new fzstd.Decompress((chunk, isLast) => {
// Add to list of output chunks
outChunks.push(chunk);
// Log after all chunks decompressed
if (isLast) {
console.log('Output chunks:', outChunks);
}
});
// You can also attach the data handler separately if you don't want to
// do so in the constructor.
stream.ondata = (chunk, final) => { ... }
// Since this is synchronous, all errors will be thrown by stream.push()
stream.push(chunk1);
stream.push(chunk2);
...
// Last chunk must have the second parameter true
stream.push(chunkLast, true);
// Alternatively, you can push every data chunk normally and push an empty
// chunk at the end:
// stream.push(chunkLast);
// stream.push(new Uint8Array(0), true);
Unlike my Zlib implementation fflate
, WebAssembly ports of Zstandard are usually significantly (30-40%) faster than fzstd
. For very large decompression payloads (>100 MB), you'll usually want to use a WebAssembly port instead. However, fzstd
has a few advantages.
fzstd
decides how much memory to allocate from the frame headers.fzstd
is absolutely tiny: at 8kB minified and 3.8kB after gzipping, it's much smaller than most WASM implementations.Please note that unlike the reference implementation, fzstd
only supports a maximum backreference distance of 225 bytes. If you need to decompress files with an "ultra" compression level (20 or greater) AND your files can be above 32MB decompressed, fzstd
may fail to decompress properly. Consider using a WebAssembly port for files this large.