Parallel Stream Examples

The Stream API allows running in parallel in multiple CPU cores to speed up processing when the algorithm requires a very large number of loops.  Below are some examples that I created as mnemonic and experimental usage.

Note that list.stream().parallel() can also be written as list.parallelStream().

Function<Integer, List<Integer>> getList = (n) -> {
    return Stream.iterate(1, i -> i + 1)
                 .limit(n)
                 .collect(Collectors.toList());
};

List<Integer> dataList = getList.apply(20);        

// Run in sequence to print
dataList.forEach(x -> System.out.print (x + " "));
System.out.println();

// Run in parallel to print
dataList.stream()
        .parallel()
        .forEach(x -> System.out.print(x + " "));
System.out.println();

// Run in paraellel to map, collect, and print
dataList.stream()
        .parallel()
        .map(x -> x + " ")
        .collect(Collectors.toList())
        .forEach(System.out::print);
System.out.println();


int iResult;

// Run in sequence to sum
iResult = dataList.stream()
                  .reduce(0, Integer::sum);
System.out.println(iResult);


// Run in parallel to sum
iResult = dataList.stream()
                  .parallel()
                  .reduce(0, Integer::sum);
System.out.println(iResult);


// Run in paraellel to find the max
iResult = dataList.stream()
                  .parallel()
                  .reduce(Integer::max)
                  .get();
System.out.println(iResult);

// Run in paraellel to find the min
iResult = dataList.stream()
                  .parallel()
                  .reduce(Integer::min)
                  .get();
System.out.println(iResult);


double dResult;

// Run parallel() then mapToDouble(ToDoubleFunction<? super T> mapper), and calculate the average
dResult = dataList.stream()
                  .parallel()
                  .mapToDouble(x -> x)
                  .average()
                  .getAsDouble();                         
System.out.println(dResult);

// Run mapToDouble(ToDoubleFunction<? super T> mapper) then parallel(), and calculate the average
dResult = dataList.stream()
                  .mapToDouble(x -> x)
                  .parallel()
                  .average()
                  .getAsDouble();                         
System.out.println(dResult);

Output:

 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
13 15 14 18 7 12 17 11 6 9 10 8 19 1 5 4 3 16 20 2
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
210
210
20
1
10.5
10.5










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