Should I Always Use Parallel Streams in Java 8?

Weighing the Use of Parallel Streams

Java 8's parallel streams offer a convenient way to parallelize processing over collections, raising the question of whether they should always be used.

Assessing the Benefits and Drawbacks

Parallel streams can potentially improve performance by distributing work across multiple cores. However, this parallelization comes at a cost.

Overhead

Coordinating threads introduces an overhead that can negate any potential speedup. Sequential streams typically have a lower overhead, making them more suitable for small collections or operations that are not parallelizable.

Other Considerations

Beyond performance, other factors influence the decision to use parallel streams:

• Data Size: Parallel streams are most beneficial when processing large collections. Small collections may not gain significant performance improvement.
• Parallelizable Operations: The operations being performed should be easily parallelizable. If the operations rely heavily on synchronization, parallelization may be counterproductive.
• Multi-Threading Environment: If the process is already running in a multi-threaded environment (e.g., a web container), adding additional parallelism may have negative effects.

When to Use Parallel Streams

Based on these considerations, parallel streams should be considered when:

• The collection is massive or operations are time-consuming and parallelizable.
• There is a demonstrated performance bottleneck.
• The process is not already running in a multi-threaded environment.

Synchronization Issues

While parallel streams can improve performance, they introduce the need for thread-safe code. Accessing shared resources or using side effects must be carefully synchronized to avoid concurrency issues.

Empirical Measurement

Ultimately, the decision to use parallel streams should be based on empirical measurement. Conducting performance testing can determine whether parallelism provides a tangible benefit for a specific scenario.

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