16.9 Parallel Streams

The Stream API makes it possible to execute a sequential stream in parallel without rewriting the code. The primary reason for using parallel streams is to improve performance, but at the same time ensuring that the results obtained are the same, or at least compatible, regardless of the mode of execution. Although the API goes a long way to achieve its aim, it is important to understand the pitfalls to avoid when executing stream pipelines in parallel.

Building Parallel Streams

The execution mode of an existing stream can be set to parallel by calling the parallel() method on the stream (p. 933). The parallelStream() method of the Collection interface can be used to create a parallel stream with a collection as the data source (p. 897). No other code is necessary for parallel execution, as the data partitioning and thread management for a parallel stream are handled by the API and the JVM. As with any stream, the stream is not executed until a terminal operation is invoked on it.

The isParallel() method of the stream interfaces can be used to determine whether the execution mode of a stream is parallel (p. 933).

Parallel Stream Execution

The Stream API allows a stream to be executed either sequentially or in parallel— meaning that all stream operations can execute either sequentially or in parallel. A sequential stream is executed in a single thread running on one CPU core. The elements in the stream are processed sequentially in a single pass by the stream operations that are executed in the same thread (p. 891).

A parallel stream is executed by different threads, running on multiple CPU cores in a computer. The stream elements are split into substreams that are processed by multiple instances of the stream pipeline being executed in multiple threads. The partial results from processing of each substream are merged (or combined) into a final result (p. 891).

Parallel streams utilize the Fork/Join Framework (§23.3, p. 1447) under the hood for executing parallel tasks. This framework provides support for the thread management necessary to execute the substreams in parallel. The number of threads employed during parallel stream execution is dependent on the CPU cores in the computer.

Figure 16.12, p. 963, illustrates parallel functional reduction using the three-argument reduce(identity, accumulator, combiner) terminal operation (p. 962).

Figure 16.14, p. 967, illustrates parallel mutable reduction using the three-argument collect(supplier, accumulator, combiner) terminal operation (p. 966).