Why does Java stream map reduce count my result twice?

Question

I have this code a:

        ComparisonResults comparisonResults = requestsList
                .stream()
                .map(item -> getResponse(item))
                .map(item -> compareToBl(item))
                .reduce(new ComparisonResults(), (result1, result2) ->
                {
                     result1.addSingleResult(result2);
                 //   return result1;
                    return new ComparisonResults(result1);
                });

and this code b:

        ComparisonResults comparisonResults = requestsList
                .parallelStream()
                .map(item -> getResponse(item))
                .map(item -> compareToBl(item))
                .reduce(new ComparisonResults(), (result1, result2) ->
                {
                     result1.addSingleResult(result2);
                 //   return result1;
                    return new ComparisonResults(result1);
                });

All I do is to create response objects, then transform them to comaprisonResult objects and to reduce them to one comaprisonResult.

code a shows an int class member comparisonResults.num_of_sub_responses==5 which is correct

code b shows an int class member comparisonResults.num_of_sub_responses==10 which is double the correct result.

java 8 reduce should be thread safe, right?

am i missing anything?

getResponse and compareToBl are thread safe

Answer 1

Your are mutating an incoming object in reduce. This is wrong. It doesn’t help that you are creating a new object after modifying the incoming object.

What you want to do, is

.collect(ComparisonResults::new, ComparisonResults::addSingleResult,
         (a,b)->/* code to merge two ComparisonResults instances*/);

If the result of .map(item -> compareToBl(item)) is ComparisonResults or, in other words, addSingleResult merges two ComparisonResults instances, you can use ComparisonResults::addSingleResult as merge function, though it’s name is a bit misleading then.

You should carefully read the “Reduction” chapter of the documentation and its follow-up, “Mutable reduction”.