jotaelesalinas/php-mapreduce

A local implementation of the map-reduce strategy in PHP

v2.0.0 2022-07-31 04:55 UTC

Requires

• php: >=8.0

Requires (Dev)

• phpunit/phpunit: ^9.5
• squizlabs/php_codesniffer: ^3.7

MIT

• José Luis Salinas

• php
• map
• mapreduce
• reduce
• map-reduce
• php-mapreduce
• non-distributed

README

PHP PSR-4 compliant library to easily do non-distributed local map-reduce.

Install

Via Composer

$ composer require jotaelesalinas/php-mapreduce

Basic usage

require_once __DIR__ . '/vendor/autoload.php';

$source = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10];
$mapper = fn($item) => $item * 2;
$reducer = fn($carry, $item) => ($carry ?? 0) + $item;

$result = MapReduce\MapReduce::create()
    ->setInput($source)
    ->setMapper($mapper)
    ->setReducer($reducer)
    ->run();

print_r($result);

The output is:

Array
(
    [0] => 110
)

Filters

$odd_numbers = fn($item) => $item % 2 === 0;
$greater_than_10 = fn($item) => $item > 10;

$result = MapReduce\MapReduce::create([
        "input" => $source, 
        "mapper" => $mapper, 
        "reducer" => $reducer, 
    ])
    // only odd numbers are passed to the mapper function
    ->setPreFilter($odd_numbers)
    // only numbers greater than 10 are passed to the reducer function
    ->setPostFilter($greater_than_10)
    ->run();

print_r($result);

The output is:

Array
(
    [0] => 48
)

Groups

Group by the value of a field (valid for arrays and objects):

$source = [
    [ "first_name" => "Susanna", "last_name" => "Connor",  "member" => "y", "age" => 20],
    [ "first_name" => "Adrian",  "last_name" => "Smith",   "member" => "n", "age" => 22],
    [ "first_name" => "Mike",    "last_name" => "Mendoza", "member" => "n", "age" => 24],
    [ "first_name" => "Linda",   "last_name" => "Duguin",  "member" => "y", "age" => 26],
    [ "first_name" => "Bob",     "last_name" => "Svenson", "member" => "n", "age" => 28],
    [ "first_name" => "Nancy",   "last_name" => "Potier",  "member" => "y", "age" => 30],
    [ "first_name" => "Pete",    "last_name" => "Adams",   "member" => "n", "age" => 32],
    [ "first_name" => "Susana",  "last_name" => "Zommers", "member" => "y", "age" => 34],
    [ "first_name" => "Adrian",  "last_name" => "Deville", "member" => "n", "age" => 36],
    [ "first_name" => "Mike",    "last_name" => "Cole",    "member" => "n", "age" => 38],
    [ "first_name" => "Mike",    "last_name" => "Angus",   "member" => "n", "age" => 40],
];

// mapper does nothing
$mapper = fn($x) => $x;

// number of persons and sum of ages
$reduceAgeSum = function ($carry, $item) {
    if (is_null($carry)) {
        return [
            'count' => 1,
            'age_sum' => $item['age'],
        ];
    }
    
    $count = $carry['count'] + 1;
    $age_sum = $carry['age_sum'] + $item['age'];
    
    return compact('count', 'age_sum');
};

$result = MapReduce\MapReduce::create([
        "input" => $source, 
        "mapper" => $mapper, 
        "reducer" => $reduceAgeSum, 
    ])
    // group by field 'member'
    ->setGroupBy('member')
    ->run();

print_r($result);

The output is:

Array
(
    [y] => Array
        (
            [count] => 4
            [age_sum] => 110
        )

    [n] => Array
        (
            [count] => 7
            [age_sum] => 220
        )

)

Group by a custom value generated from each item:

$closestTen = fn($x) => floor($x['age'] / 10) * 10;

$result = MapReduce\MapReduce::create([
        "input" => $source, 
        "mapper" => $mapper, 
        "reducer" => $reduceAgeSum, 
    ])
    // group by age ranges of 10
    ->setGroupBy($closestTen)
    ->run();

print_r($result);

The output is:

Array
(
    [20] => Array
        (
            [count] => 5
            [age_sum] => 120
        )

    [30] => Array
        (
            [count] => 5
            [age_sum] => 170
        )

    [40] => Array
        (
            [count] => 1
            [age_sum] => 40
        )

)

Input

MapReduce accepts as input any data of type iterable. That means, arrays and traversables, e.g. generators.

This is very handy when reading from big files that do not fit in memory.

$result = MapReduce\MapReduce::create([
        "mapper" => $mapper, 
        "reducer" => $reducer, 
    ])
    ->setInput(csvReadGenerator('myfile.csv'))
    ->run();

Multiple inputs can be specified, passing several arguments to setInput(), as long as all of them are iterable:

$result = MapReduce\MapReduce::create([
        "mapper" => $mapper, 
        "reducer" => $reducer, 
    ])
    ->setInput($arrayData, csvReadGenerator('myfile.csv'))
    ->run();

Output

MapReduce can be configured to write the final data to one or more destinations.

Each destination has to be a Generator:

$result = MapReduce\MapReduce::create([
        "mapper" => $mapper, 
        "reducer" => $reducer, 
    ])
    ->setOutput(csvWriteGenerator('results.csv'))
    ->run();

Multiple outputs can be specified as well:

$result = MapReduce\MapReduce::create([
        "mapper" => $mapper, 
        "reducer" => $reducer, 
    ])
    ->setOutput(csvWriteGenerator('results.csv'), consoleGenerator())
    ->run();

To help working with input and output generators, it is recommended to use the package jotaelesalinas/php-generators, but it is not mandatory.

You can see more elaborated examples under the folder examples.

Change log

Please see CHANGELOG for more information what has changed recently.

Testing

$ composer test

Contributing

Please see CONTRIBUTING and CONDUCT for details.

Security

If you discover any security related issues, please DM me to @jotaelesalinas instead of using the issue tracker.

To do

• Add events to help see progress in large batches
• Add docs
• Insurance example
  • adapt to new library
  • add insured values
  • improve kml output (info, markers)

Credits

• José Luis Salinas
• All Contributors

License

The MIT License (MIT). Please see License File for more information.