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

I watched one of the presentations of Brian Goetz (Java Language Architect & specification lead for Lambda Expressions). He explains in detail the following 4 points to consider before going for parallelization:

Splitting / decomposition costs
– Sometimes splitting is more expensive than just doing the work!
Task dispatch / management costs
– Can do a lot of work in the time it takes to hand work to another thread.
Result combination costs
– Sometimes combination involves copying lots of data. For example, adding numbers is cheap whereas merging sets is expensive.
Locality
– The elephant in the room. This is an important point which everyone may miss. You should consider cache misses, if a CPU waits for data because of cache misses then you wouldn't gain anything by parallelization. That's why array-based sources parallelize the best as the next indices (near the current index) are cached and there are fewer chances that CPU would experience a cache miss.

He also mentions a relatively simple formula to determine a chance of parallel speedup.

NQ Model:

N x Q > 10000

where,
N = number of data items
Q = amount of work per item