`highland-diverge` is a building block to enable splitting a Highland stream into two or more other streams that each apply *separate* back-pressure.

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highland-diverge is a building block to enable splitting a Highland stream into two or more other streams that each apply separate back-pressure.
You could think of this as being like Highland's fork except that progress is made at the rate of the fastest stream, rather than the slowest.
The primary use-case for this is to deal with a slow stream by splitting the input items across multiple instances that can each move as fast as they are able, thereby allowing items to be processed concurrently.


The following example shows a typical (though also rather contrived) use of diverge:
var _ = require('highland');
var diverge = require('highland-diverge');
var fs = require('fs');
var request = require('request');
var streamPost = _.wrapCallback(request.post);

var inStream = _(fs.createReadStream('lines.txt'));

    .through(diverge(10)) // spread the input lines over 10 different streams
    .map(function (stream) {
        // In here, do any operations that should be done concurrently
        // across all of our divergent streams. This will generally be
        // something asynchronous that creates back-pressure, and in
        // this example that's an HTTP request via the 'request' library
        // from npm. Since we diverged to 10 streams, we'll do a maximum
        // of 10 concurrent requests to this endpoint.
        return stream.flatMap(function (line) {
            return streamPost(
                  {form: {line: line}}
    .merge() // combine the 10 separate streams back together again
        function (err) {
        function (resp) {
            console.log('got response', resp.statusCode);

The key pattern from the above example is the following:
.map(function (stream) {
    // Create a separate pipeline for each of the n streams,
    // with any highland methods you like.
    return stream.anything();

diverge returns a stream of streams, with the number of streams given in its argument. These are the output streams.
Each item or error that is written to the source stream will be written to exactly one of the output streams. The output streams will be used in the order they become ready for writing, so the allocation of items to streams is generally orderly but rather unpredictable, depending on how quickly each of the streams is able to process the items it is given.
Generally one will use map to apply the same set of follow-on transforms to each of the generated streams, thus allowing the operations in that stream to happen concurrently across n instances. This will increase throughput by n times, as long as there are no other slower elements in the outer pipeline.


Copyright 2016 Martin Atkins.
This library is distributed under the terms of the MIT license; for details, see LICENSE.