This article examines the question of whether it is always advisable to use a parallel stream when possible.

Parallel streams in Java 8 offer the advantage of faster execution by distributing work across multiple cores. However, the decision to employ parallelism should not be taken lightly, as there are various factors to consider.

Firstly, the benefits of using parallel streams are contingent upon the availability of additional cores and may not be applicable in all situations.

Moreover, the implementation of parallelism entails additional responsibilities, such as task dispatching and coordination, which can incur overheads. It is crucial to assess the advantages of parallelism against the costs of sequential processing.

Additionally, there are several limitations and concerns to address, including thread safety and the potential impact of side effects.

Furthermore, cost considerations encompass various aspects, such as splitting and decomposition costs, task dispatch and management costs, result combination costs, and locality.

Ultimately, the decision to utilize parallel streams should be made after careful evaluation of the specific context and the potential performance benefits.

When to use parallel streams?

The decision to use parallel streams should be based on factors such as the size of the data set, the computation needed per element, and the potential trade-offs in terms of additional work for dispatching and coordinating sub-tasks.

While parallel streams can offer faster execution by dividing work across multiple cores, there are no inherent benefits other than this. It is important to consider the nature of the data set and the specific computations being performed.

Additionally, parallel processing can introduce nondeterminism and may not always provide the expected performance improvement. Therefore, it is recommended to develop using sequential execution and apply parallelism only where there is a proven benefit.

Sequential processing should be considered as the default approach, with parallelism being measured and applied judiciously.

Benefits and considerations

One important aspect to consider when deciding whether to utilize parallel streams is the potential benefits and considerations associated with parallelism.

Parallel streams offer the advantage of faster execution by dividing the workload across multiple cores, thereby taking advantage of the available processing power.

However, it is crucial to note that there are no benefits to using parallel streams other than faster execution when there are more cores available.

Additionally, using parallel streams introduces additional work for dispatching and coordinating sub-tasks, which can incur overhead.

The actual benefit of parallelism depends on factors such as the size of the data set and the computation required for each element.

It is important to develop using sequential execution and apply parallelism only where there is a measurable benefit.

Sequential processing should always be considered first before considering parallelism.

Performance factors

Performance factors in parallel streams can be influenced by several factors.

The size of the data set and the computation required per element are two important factors. The number of elements multiplied by the computation per element, known as the NQ model, determines the potential performance benefit of using parallelism.

However, the breakeven point for this benefit can vary depending on the specific scenario. It is important to identify situations where sequential processing is costly before considering parallelism.

Additionally, it is crucial to measure the actual performance improvement achieved by parallel processing. This measurement is necessary to determine if the overhead of splitting and decomposing tasks, task dispatch and management, result combination, and locality, including cache misses, is worth the potential speedup.

It’s important to consider these performance factors before deciding to use parallel streams.