When Do Parallel Streams in Java Actually Improve Performance?

Assessing the Efficacy of Parallel Streams

In the realm of Java, lambda expressions have facilitated seamless iteration over collections using streams. The advent of parallel streams further simplifies this process. However, the question arises: are parallel streams always advantageous?

Consider the following scenario: a collection of shapes is being filtered to identify those with a specific color, and the order of traversal is not crucial. Intriguingly, one might assume that utilizing a parallel stream would expedite the filtering process.

Factors to Consider

While parallel streams offer potential performance gains, they also introduce additional considerations.

1. Overheads: Compared to sequential streams, parallel streams incur significant overhead due to thread coordination.
2. Suitability: Parallelization is only beneficial if the workload is substantial or if item processing is both time-consuming and parallelizable.
3. Existing Parallelism: If the process already operates in a multi-threaded environment, such as a web container, introducing additional parallelism may have detrimental effects.

Assessment Guidelines

Given these factors, the following guidelines can assist you in determining the suitability of parallel streams:

• Utilize sequential streams as the default.

• Consider parallel streams only if:

  • The workload is massive.
  • Performance bottlenecks necessitate optimization.
  • There is no parallel processing at the application level.

In the example provided, the performance is constrained by the synchronized access to System.out.println(). Parallelizing the process would yield no benefits.

Cautionary Notes

• Parallelizing a stream does not eliminate the need for synchronization in the underlying code.
• Side effects can pose significant challenges in parallel processing.
• Empirical measurements are indispensable for gauging the efficacy of parallel streams.

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