You probably want a different summary. + * @summary Tests counting of streams containing Integer.MAX_VALUE + 1 elements
Will this fail if common pool parallelism is odd? + int splitsForPHalfC = countSplits(new ForkJoinPool(ForkJoinPool.getCommonPoolParallelism() / 2)); I would drop the word "factor" below: + * Default target factor of leaf tasks for parallel decomposition. Do you ever test with -Djava.util.concurrent.ForkJoinPool.common.parallelism=0 * @run junit/othervm/timeout=1000 * --add-opens java.base/java.util.concurrent=ALL-UNNAMED * --add-opens java.base/java.lang=ALL-UNNAMED * -Djsr166.testImplementationDetails=true * -Djava.util.concurrent.ForkJoinPool.common.parallelism=0 * JSR166TestCase On Wed, Nov 8, 2017 at 1:01 PM, Paul Sandoz <paul.san...@oracle.com> wrote: > Hi, > > Please review this patch to ensure that a parallel stream obeys the > parallelism of a custom fork join pool when it is executed within that pool: > > http://cr.openjdk.java.net/~psandoz/jdk10/JDK-8190974-par- > stream-custom-pool/webrev/ <http://cr.openjdk.java.net/~ > psandoz/jdk10/JDK-8190974-par-stream-custom-pool/webrev/> > > Streams currently do not support capabilities to control the level of > parallelism and therefore resources utilised (tricky API design problem to > get right). > > At the moment the trick is to run stream executions within a custom pool, > however the number of fork join tasks created will be in proportion to the > parallelism of the common pool thus the execution will be over-provisioned. > This can be especially noticeable on large machines with many cores. > > Paul.
