kastiglione / concurrentcollectionoperations

Map & filter using GCD for NSArray, NSDictionary, NSSet, etc.

Concurrent Collection Operations

A set of categories for performing concurrent map and filter operations on Foundation data structures. NSArray, NSDictionary, NSSet, NSOrderedSet, and NSMapTable (OS X) are currently supported.

Concurrency is achieved using Grand Central Dispatch's dispatch_apply. By default, operations are run on the default priority global concurrent queue (DISPATCH_QUEUE_PRIORITY_DEFAULT). The operations can be performed on any concurrent queue, see the category header files.

Please note that using this code could actually result in slower performance. For example, if a map or filter operation uses up a large amount of memory, then performing it concurrently could cause memory thrashing. Currently, this API does not offer a way to limit the amount of concurrency, but doing so explicitly with dispatch_semaphore is straight forward.

This library is based off code and ideas from @alloy and @seanlilmateus.

Installation

Install via CocoaPods, or by adding the Xcode project to your project.

Examples

These examples are taken from the tests.

Doubling the values of an array:

NSArray *doubled = [numbersArray cco_concurrentMap:^(NSNumber *number) {
    return @(2 * number.unsignedIntegerValue);
}];

Filtering even numbers out of a dictionary:

NSDictionary *filtered = [numbersDictionary cco_concurrentFilter:^BOOL (NSNumber *number) {
    return number.unsignedIntegerValue % 2 == 1;
}];

Contributors

ConcurrentCollectionOperations has been made by @alloy, @CodaFi, @jballanc, @kastiglione, and @seanlilmateus.

TODO

1. Write heavier/stressing tests.

License

Concurrent Collection Operations is released under the MIT License. See LICENSE.txt.

Contributing

1. Fork it
2. Create your feature branch (git checkout -b my-new-feature)
3. Commit your changes (git commit -am 'Add some feature')
4. Push to the branch (git push origin my-new-feature)
5. Create new Pull Request

concurrentcollectionoperations's Issues

Memory pressure handling

As brought to attention in #2, concurrently executing memory intensive tasks can be detrimental to performance.

• Document issue in README.
• Provide API to limit number of tasks?
• Use new GCD API to detect memory pressure and respond by scaling down concurrency?