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Summary: Change ghc-8.4.3 to ghc-8.4.4 and add ghc-8.6.2. Reviewed By: karen Differential Revision: D13363035 fbshipit-source-id: 988f13f0a0022d2deec6d03c30cc8ee17a85d252
60 lines
2.7 KiB
Markdown
60 lines
2.7 KiB
Markdown
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# Haxl
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[](https://travis-ci.org/facebook/Haxl)
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Haxl is a Haskell library that simplifies access to remote data, such
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as databases or web-based services. Haxl can automatically
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* batch multiple requests to the same data source,
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* request data from multiple data sources concurrently,
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* cache previous requests,
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* memoize computations.
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Having all this handled for you behind the scenes means that your
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data-fetching code can be much cleaner and clearer than it would
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otherwise be if it had to worry about optimizing data-fetching. We'll
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give some examples of how this works in the pages linked below.
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There are two Haskell packages here:
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* `haxl`: The core Haxl framework
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* `haxl-facebook` (in [https://github.com/facebook/Haxl/tree/master/example/facebook](example/facebook)): An (incomplete) example data source for accessing the Facebook Graph API
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To use Haxl in your own application, you will likely need to build one or more
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*data sources*: the thin layer between Haxl and the data that you want
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to fetch, be it a database, a web API, a cloud service, or whatever.
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There is a generic datasource in "Haxl.DataSource.ConcurrentIO" that
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can be used for performing arbitrary IO operations concurrently, given
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a bit of boilerplate to define the IO operations you want to perform.
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The `haxl-facebook` package shows how we might build a Haxl data
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source based on the existing `fb` package for talking to the Facebook
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Graph API.
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## Where to go next?
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* [The Story of Haxl](https://code.facebook.com/posts/302060973291128/open-sourcing-haxl-a-library-for-haskell/)
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explains how Haxl came about at Facebook, and discusses our
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particular use case.
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* [An example Facebook data source](https://github.com/facebook/Haxl/blob/master/example/facebook/readme.md) walks
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through building an example data source that queries the Facebook
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Graph API concurrently.
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* [Fun with Haxl (part 1)](https://simonmar.github.io/posts/2015-10-20-Fun-With-Haxl-1.html)
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Walks through using Haxl from scratch for a simple SQLite-backed
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blog engine.
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* [The N+1 Selects Problem](https://github.com/facebook/Haxl/blob/master/example/sql/readme.md) explains how Haxl
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can address a common performance problem with SQL queries by
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automatically batching multiple queries into a single query,
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without the programmer having to specify this behavior.
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* [Haxl Documentation](http://hackage.haskell.org/package/haxl) on
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Hackage.
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* [There is no Fork: An Abstraction for Efficient, Concurrent, and Concise Data Access](http://simonmar.github.io/bib/papers/haxl-icfp14.pdf), our paper on Haxl, accepted for publication at ICFP'14.
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