Parallel.ForEach vs. Task.Factory.StartNew: Which is Best for Parallel Collection Processing?

Parallel.ForEach vs. Task.Factory.StartNew: Subtle differences in parallel collection processing

When processing collection operations in parallel, developers often choose Parallel.ForEach or Task.Factory.StartNew. While both provide parallel execution, their approach and impact on execution differ.

Comparison of Parallel.ForEach and Task.Factory.StartNew

Parallel.ForEach uses Partitioner to divide the collection into work items. It batches projects to reduce overhead, ensuring efficient execution. In contrast, Task.Factory.StartNew schedules a new Task for each item, which incurs higher overhead for large collections.

Efficiency considerations

To maximize efficiency, Parallel.ForEach is the better choice. Its use of partitioning significantly reduces overhead, especially in large collections. In contrast, Task.Factory.StartNew creates a single task, but may add unnecessary overhead and slow down execution.

Asynchronous execution

Task.Factory.StartNew runs asynchronously, allowing the calling code to continue executing without blocking. This behavior can be replicated by wrapping Parallel.ForEach in a Task.Factory.StartNew call. However, partitions are still used to ensure efficiency.

Custom partition

Parallel.ForEach provides additional control over partitioning by allowing custom Partitioner implementations. This makes it possible to optimize for specific scenarios.

Summary

When parallel processing of collection tasks is required, Parallel.ForEach is a more efficient choice. However, if asynchronous execution is required, using Task.Factory.StartNew in conjunction with Parallel.ForEach can provide a suitable solution that balances efficiency and asynchronous functionality.

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