java8对stream串、并行流的测试性能的用例

上一篇文章说到，对于在java8中使用stream中的并行流的几个建议的说明。下面我们就写一个测试用例测量一下（在性能优化时，遵循的三个黄金规则：测量、测量、测量）

com.kisszero.one.paralleljava.util.stream.LongStreamjava.util.stream.StreamParallelStreamsUtils {

(n) {
result = (i = i <= ni++) {
result += i}
result}

(n) {
Stream.(i -> i + ).limit(n).reduce(Long::).get()}

(n) {
Stream.(i -> i + ).limit(n).parallel().reduce(Long::).get()}

(n) {
LongStream.(n).reduce(Long::).getAsLong()}

(n) {
LongStream.(n).parallel().reduce(Long::).getAsLong()}

(n) {
Accumulator accumulator = Accumulator()LongStream.(n).forEach(accumulator::add)accumulator.}

(n) {
Accumulator accumulator = Accumulator()LongStream.(n).parallel().forEach(accumulator::add)accumulator.}

Accumulator {
= (value) {
+= value}
}
}

com.kisszero.one.paralleljava.util.concurrent.ForkJoinPooljava.util.function.FunctionParallelStreamsTest {
ForkJoinPool = ForkJoinPool()(String[] args) {
System..println(+ (ParallelStreamsUtils::) + )System..println(+ (ParallelStreamsUtils::) + )System..println(+ (ParallelStreamsUtils::) + )System..println(+ (ParallelStreamsUtils::) + )System..println(+ (ParallelStreamsUtils::) + )System..println(+ (ParallelStreamsUtils::) + )System..println(+ (ParallelStreamsUtils::) + )}

<> (Function<> finput) {
fastest = Long.(i = i < i++) {
start = System.()result = f.apply(input)duration = (System.() - start) / System..println(+ result)(duration < fastest) fastest = duration}
fastest}
}

结果：
Iterative Sum done in: 5 msecs
Sequential Sum done in: 154 msecs
Parallel forkJoinSum done in: 376 msecs
Range forkJoinSum done in: 13 msecs
Parallel range forkJoinSum done in: 8 msecs
SideEffect sum done in: 4 msecs
Result: 22454695176953
Result: 20121132009947
Result: 16076928917786
Result: 16957805754284
Result: 13642545729260
Result: 12997343158699
Result: 13761162440338
Result: 17902422526976
Result: 21642228116467
Result: 17496039228969
SideEffect prallel sum done in: 47 msecs

Stream中的LongStream.rangClosed方法比iterate在这种求和的情况下效率更好，因为前者直接产生原始类型的long数字，没有装箱拆箱的开销，还有就是前者生成的数字范围，很容易的拆分为独立的小块。