Initial request for review of JDK-8006572 DoubleStream.sum()/average() implementations that reduce numerical errors

[Paul Sandoz]

Hi Joe,

You can use the three arg form of collect for DoublePipeline.sum/average impls, which is already used for average:

    public final OptionalDouble average() {
        double[] avg = collect(() -> new double[2],
                               (ll, i) -> {
                                   ll[0]++;
                                   ll[1] += i;
                               },
                               (ll, rr) -> {
                                   ll[0] += rr[0];
                                   ll[1] += rr[1];
                               });
        return avg[0] > 0
               ? OptionalDouble.of(avg[1] / avg[0])
               : OptionalDouble.empty();
    }

That would be the most expedient way. However, for sum() it is somewhat unfortunate to have to create a double[1] box for each leaf. If you are willing to write a little more more code you can create your own double sum ReducingSink implementation as Brian suggests.


Testing wise you don't need to implement an Iterator, you can do the following:

  DoubleStream.iterate(base, e -> increment).limit(count)

It might be more convenient to test as follows:
 
  Stream<Boolean> s = Stream.iterate(false, e -> true).limit(count); // [*]
  DoubleSummaryStatistics stats = s.collect(Collectors.summarizingDouble(e -> e ? increment : base)); // Cross fingers that compiles!

  Stream<Boolean> s = Stream.iterate(false, e -> true).limit(count);
  Double d = s.iterate(false, e -> true).limit(count)..collect(Collectors.summingDouble(e ? increment : base));

Thereby covering both Collector implementations.

I guess it might be harder to test the combining step using parallel streams since combining will be platform dependent (depends on #cores) unless you track how things are combined. Perhaps the Collector instance could be tested directly with combination?

Paul.

[*] Another way is to use stream concatenation: 

  Stream.concat(Stream.of(false), IntStream.range(1, count).mapToObj(e -> true))
  Stream.concat(Stream.of(false), Stream.generate(() -> true)).limit(count)


On Nov 14, 2013, at 9:08 AM, Joe Darcy <joe.darcy at oracle.com> wrote:

> Hello,
> 
> Please take an initial look over a fix for
> 
>    JDK-8006572 DoubleStream.sum() & DoubleSummaryStats implementations that reduce numerical errors
>    http://cr.openjdk.java.net/~darcy/8006572.0/
> 
> The basic approach is to use compensated summation
> 
>    http://en.wikipedia.org/wiki/Kahan_summation_algorithm
> 
> to computed streams-related sum and average statistics in the various locations that this can be done.
> 
> All existing streams tests pass and new newly-written test passes too.
> 
> I believe the DoubleSummaryStatistics.java portion, including the test, is fully review-worthy. In the test, for the sample computation in question, the naive summation implementation had a error of 500,000 ulps compared to 2 ups with the new implementation.
> 
> Two other locations I've found where this summation technique should be used are in
> 
>    java.util.stream.Collectors.{summingDouble, averagingDouble}
> 
> and
> 
>    java.util.stream.DoublePipeline.{sum, average}
> 
> DoublePipeline is the primary implementation class of DoubleStream.
> 
> For Collectors, the proposed code is a fairly clear adaptation of how the current code passes state around; there is not currently a dedicated test for the new summation technique in this location.
> 
> I'm new to the streams API so for DoublePipeline I don't know the idiomatic way to phrase the collect I want to perform over the code. (Based on my current understanding, I believe I want to perform a collect rather than a reduce since for the compensated summation I need to maintain some additional state.) Guidance here welcome.
> 
> Thanks,
> 
> -Joe