Stream.toList() 会比 Collectors.toList() 表现更好吗
JDK 正在引入 API Stream.toList() 与 JDK-8180352.这是我尝试将其性能与现有 Collectors.toList 进行比较的基准代码:
JDK is introducing an API Stream.toList() with JDK-8180352. Here is a benchmarking code that I have attempted to compare its performance with the existing Collectors.toList:
@BenchmarkMode(Mode.All)
@Fork(1)
@State(Scope.Thread)
@Warmup(iterations = 20, time = 1, batchSize = 10000)
@Measurement(iterations = 20, time = 1, batchSize = 10000)
public class CollectorsVsStreamToList {
@Benchmark
public List<Integer> viaCollectors() {
return IntStream.range(1, 1000).boxed().collect(Collectors.toList());
}
@Benchmark
public List<Integer> viaStream() {
return IntStream.range(1, 1000).boxed().toList();
}
}
结果汇总如下:
Benchmark Mode Cnt Score Error Units
CollectorsVsStreamToList.viaCollectors thrpt 20 17.321 ± 0.583 ops/s
CollectorsVsStreamToList.viaStream thrpt 20 23.879 ± 1.682 ops/s
CollectorsVsStreamToList.viaCollectors avgt 20 0.057 ± 0.002 s/op
CollectorsVsStreamToList.viaStream avgt 20 0.040 ± 0.001 s/op
CollectorsVsStreamToList.viaCollectors sample 380 0.054 ± 0.001 s/op
CollectorsVsStreamToList.viaCollectors:viaCollectors·p0.00 sample 0.051 s/op
CollectorsVsStreamToList.viaCollectors:viaCollectors·p0.50 sample 0.054 s/op
CollectorsVsStreamToList.viaCollectors:viaCollectors·p0.90 sample 0.058 s/op
CollectorsVsStreamToList.viaCollectors:viaCollectors·p0.95 sample 0.058 s/op
CollectorsVsStreamToList.viaCollectors:viaCollectors·p0.99 sample 0.062 s/op
CollectorsVsStreamToList.viaCollectors:viaCollectors·p0.999 sample 0.068 s/op
CollectorsVsStreamToList.viaCollectors:viaCollectors·p0.9999 sample 0.068 s/op
CollectorsVsStreamToList.viaCollectors:viaCollectors·p1.00 sample 0.068 s/op
CollectorsVsStreamToList.viaStream sample 525 0.039 ± 0.001 s/op
CollectorsVsStreamToList.viaStream:viaStream·p0.00 sample 0.037 s/op
CollectorsVsStreamToList.viaStream:viaStream·p0.50 sample 0.038 s/op
CollectorsVsStreamToList.viaStream:viaStream·p0.90 sample 0.040 s/op
CollectorsVsStreamToList.viaStream:viaStream·p0.95 sample 0.042 s/op
CollectorsVsStreamToList.viaStream:viaStream·p0.99 sample 0.050 s/op
CollectorsVsStreamToList.viaStream:viaStream·p0.999 sample 0.051 s/op
CollectorsVsStreamToList.viaStream:viaStream·p0.9999 sample 0.051 s/op
CollectorsVsStreamToList.viaStream:viaStream·p1.00 sample 0.051 s/op
CollectorsVsStreamToList.viaCollectors ss 20 0.060 ± 0.007 s/op
CollectorsVsStreamToList.viaStream ss 20 0.043 ± 0.006 s/op
当然，领域专家的第一个问题是基准测试程序是否正确?测试类在 MacOS 上执行.如果需要任何进一步的详细信息，请告诉我.
Of course, the first question to the domain experts would be if the benchmarking procedure is correct or not? The test class was executed on MacOS. Do let me know for any further details required.
跟进，据我所知，Stream.toList 的平均时间、吞吐量和采样时间看起来比 Collectors.toList.这种理解正确吗?
Follow-up, as far as I could infer from the readings the average time, throughput, and sampling time of the Stream.toList looks better than the Collectors.toList. Is that understanding correct?
推荐答案
Stream::toList 构建在 toArray 之上，而不是 collect.toArray 中有许多优化，使其可能比收集更快，尽管这在很大程度上取决于细节.如果流管道(从源到最终中间操作)是 SIZED，则可以预先确定目标数组的大小(而不是像 toList 收集器必须做的那样重新分配.)如果管道进一步SUBSIZED，那么并行执行不仅可以预先确定结果数组的大小，还可以计算每个分片的精确偏移量，因此每个子任务都可以将其结果放在正确的位置，从而无需将中间结果复制到最终结果中.
Stream::toList is built atop toArray, not collect. There are a number of optimizations in toArray that make it potentially faster than collecting, though this depends heavily on the details. If the stream pipeline (from source through final intermediate operation) is SIZED, the target array can be presized (rather than potentially reallocating as the toList collector must do.) If the pipeline is further SUBSIZED, then parallel executions can not only presize the result array, but can compute exact per-shard offsets so each sub-task can drop its results in exactly the right place, eliminating the need for copying intermediate results into the final result.
因此，根据细节，toList 可能比 collect 快得多.
So, depending on the details, toList may well be considerably faster than collect.
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