Java Streams API summing Lists at index

Question

i would like to know if there is a more efficient way to sum all tree lists - summing their values at the same index.

The reason why i am asking its because, probably using Streams API, its possible to make it more generic, for any number of lists.

List<Double> listA = getListA();
List<Double> listB = getListB();
List<Double> listC = getListC();

int listsSize = listA.size();

    List<?> collect = IntStream.range(0, listsSize)
            .mapToObj(i -> listA.get(i) + listB.get(i) + list(C).get(i))
            .collect(toList());

thanks for any insight.

@ChiefTwoPencils Yes you are right i just missed the obvious there, i edited it, the question is still valid for any number of lists, thanks — dotmindlabs
– dotmindlabs, Commented May 22, 2015 at 18:18
@sodik i mean for any number of lists, if i have lets say 100 lists, using index from a range and get their values 100 times seems overkilling. — dotmindlabs
– dotmindlabs, Commented May 22, 2015 at 18:21

Brian Goetz · Accepted Answer · 2015-05-22 20:07:27Z

5

How about this:

List<List<Double>> lists = ...;

// ensure all lists are same size, and get size
int[] sizes = lists.stream().mapToInt(List::size).distinct().toArray();
if (sizes.length != 1)
    throw ...
int size = sizes[0];

double[] sums =
    IntStream.range(0, size)
             .mapToDouble(i -> lists.stream().mapToDouble(list -> list.get(i)).sum())
             .toArray();

edited May 22, 2015 at 20:07

answered May 22, 2015 at 19:01

Brian Goetz

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2 Comments

user2336315 Over a year ago

small typo, it should be lists.stream().mapToInt(...), :-) Also couldn't you make this more performant with a .distinct().limit(2), so that as soon as you find more than 2 different sizes you stop the computations?

Brian Goetz Over a year ago

@user2336315 Fixed typo. Your suggestion of "limit" is OK, but frankly I wouldn't bother; the extra "cost" only shows up right before you are going to throw an exception anyway. Small optimizations on the will-fail paths are rarely worth the additional complexity.

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