By Stephen Cleary
If you're one of many many builders doubtful approximately concurrent and multithreaded improvement, this sensible cookbook will switch your brain. With greater than seventy five code-rich recipes, writer Stephen Cleary demonstrates parallel processing and asynchronous programming options, utilizing libraries and language good points in .NET 4.5 and C# 5.0.
Concurrency is turning into extra universal in responsive and scalable software improvement, yet it's been tremendous tricky to code. The particular recommendations during this cookbook convey you ways sleek instruments bring up the extent of abstraction, making concurrency a lot more uncomplicated than earlier than.
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Extra info for Concurrency in C# Cookbook: Asynchronous, Parallel, and Multithreaded Programming
3 covers invoking a sequence of methods in parallel, when all the methods are known at the start of the parallel work. 5. Parallel LINQ Problem You have parallel processing to perform on a sequence of data, producing another se‐ quence of data or a summary of that data. Solution Most developers are familiar with LINQ, which you can use to write pull-based calcu‐ lations over sequences. Parallel LINQ (PLINQ) extends this LINQ support with parallel processing. PLINQ works well in streaming scenarios, when you have a sequence of inputs and are producing a sequence of outputs.
Avoiding Context for Continuations Problem When an async method resumes after an await, by default it will resume executing within the same context. This can cause performance problems if that context was a UI context and a large number of async methods are resuming on the UI context. FromSeconds(1)); // This method resumes within the same context. ConfigureAwait(false); // This method discards its context when it resumes. } Discussion Having too many continuations run on the UI thread can cause a performance problem.
This is just an example of using a lock to protect shared state. Sum(); } OK, that was a cheap shot, since PLINQ has built-in support for many common oper‐ ators (such as Sum). Aggregate( seed: 0, func: (sum, item) => sum + item ); } Discussion If you are already using the Parallel class, you may want to use its aggregation support. Otherwise, in most scenarios, the PLINQ support is more expressive and has shorter code. 5 covers the basics of PLINQ. 3. Parallel Invocation Problem You have a number of methods to call in parallel, and these methods are (mostly) in‐ dependent of each other.