Azure Functions and Data Parallelism: things to know.
Parallel programming and data parallelism can improve code performance by allowing multiple threads to operate on different segments of a source collection or array. The Task Parallel Library (TPL) in .NET Framework supports data parallelism through the System.Threading.Tasks.Parallel class. This class provides method-based parallel implementations of for and foreach loops. By using Parallel.For and Parallel.ForEach, you can write loop logic that can utilize the full power of your CPU without having to create threads or take locks. In a real-world scenario, using Parallel.ForEach instead of a sequential foreach loop improved the processing time of a data file by 7 times. However, when deploying this code in an Azure Function, the processing time between the single-threaded and parallel approaches was the same. This is because Azure Functions in the Consumption plan do not distribute a single execution over multiple threads or machines.
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