Should I always use a parallel stream when possible?

Question

With Java 8 and lambdas it\'s easy to iterate over collections as streams, and just as easy to use a parallel stream. Two examples from the docs, the second one using parall

Answer 1

Other answers have already covered profiling to avoid premature optimization and overhead cost in parallel processing. This answer explains the ideal choice of data structures for parallel streaming.

As a rule, performance gains from parallelism are best on streams over ArrayList , HashMap , HashSet , and ConcurrentHashMap instances; arrays; int ranges; and long ranges. What these data structures have in common is that they can all be accurately and cheaply split into subranges of any desired sizes, which makes it easy to divide work among parallel threads. The abstraction used by the streams library to perform this task is the spliterator , which is returned by the spliterator method on Stream and Iterable.

Another important factor that all of these data structures have in common is that they provide good-to-excellent locality of reference when processed sequentially: sequential element references are stored together in memory. The objects referred to by those references may not be close to one another in memory, which reduces locality-of-reference. Locality-of-reference turns out to be critically important for parallelizing bulk operations: without it, threads spend much of their time idle, waiting for data to be transferred from memory into the processor’s cache. The data structures with the best locality of reference are primitive arrays because the data itself is stored contiguously in memory.

Source: Item #48 Use Caution When Making Streams Parallel, Effective Java 3e by Joshua Bloch