Java Sum Methods: IntStream and reduce

Use IntStream, reduce and Integer sum to add up ints. Test a for-loop that sums.

Sum. An array contains numbers (such as ints). In Java, methods can be used to sum these. A for-loop can instead be used. The approaches have different advantages.

With reduce, a method from the IntStream class, we apply a method to all elements. With an accumulator, we sum the numbers. This approach is more complex than the for-loop.

Reduce example. We first convert our int array into an IntStream with Arrays.stream. We then call reduce—the first should be left as 0. The second is the accumulator method.Int Arrays

Lambda: To specify the accumulator we use a lambda expression. The ints a and b are added together.

Lambda

Java program that uses array, IntStream and reduce import java.util.Arrays; import java.util.stream.IntStream; public class Program { public static void main(String[] args) { // This is an array. int[] array = { 1, 2, 3 }; // Convert array to a stream. IntStream s = Arrays.stream(array); // Use reduce to sum all elements in the array. int sum = s.reduce(0, (a, b) -> a + b); // Display our result. System.out.println(sum); } } Output 6

Integer sum. We do not need to directly specify the lambda. We can use the Integer::sum method provided in Java. This does the same thing as the previous example.

Java program that uses Integer sum method import java.util.Arrays; import java.util.stream.IntStream; public class Program { public static void main(String[] args) { int[] array = { 1, 2, 3 }; IntStream s = Arrays.stream(array); // Use Integer sum method. int sum = s.reduce(0, Integer::sum); System.out.println(sum); } } Output 6

For-loop sum. This program uses a for-loop to sum all the ints in the array. A for-each loop, with no index, could instead be used.For Each

Java program that uses for-loop, int public class Program { public static void main(String[] args) { int[] array = { 1, 2, 3 }; int sum = 0; // Use a for-loop to sum the elements. for (int i = 0; i < array.length; i++) { sum += array[i]; } System.out.println(sum); } } Output 6

Sum benchmark. You can probably guess which version of summing integers is faster. The for-loop is far faster on small arrays. Here I test this.

Version 1: The sum1 method sums with stream() and reduce. It uses only three lines of code.

Version 2: Sum2 sums with a for-loop and a local variable. It uses five lines of code.

Result: The sum1 method, despite having shorter code, is far slower. It requires about 100x the time of sum2.

Java program that benchmarks sum methods import java.util.Arrays; import java.util.stream.IntStream; public class Program { static int sum1(int[] array) { // Uses reduce method. IntStream s = Arrays.stream(array); int sum = s.reduce(0, Integer::sum); return sum; } static int sum2(int[] array) { // Uses for-loop. int sum = 0; for (int i = 0; i < array.length; i++) { sum += array[i]; } return sum; } public static void main(String[] args) { int[] array = { 10, 20, 30, 40, 50, 60, 70, 80, 90 }; long t1 = System.currentTimeMillis(); // Version 1: use reduce method. for (int i = 0; i < 10000000; i++) { sum1(array); } long t2 = System.currentTimeMillis(); // Version 2: use for-loop. for (int i = 0; i < 10000000; i++) { sum2(array); } long t3 = System.currentTimeMillis(); // ... Times. System.out.println(t2 - t1); System.out.println(t3 - t2); } } Output 524 ms, stream, reduce 4 ms, for-loop

Concept. The Java documentation notes how using functional constructs (like reduce) is slower than for-loops. It is also more complex. But these constructs have an advantage.

Parallel: With functional constructs, we can place large computations on multiple threads. At some point this would become faster.

Quote: Reduction operations parallelize more gracefully, without needing additional synchronization and with greatly reduced risk of data races (Java Documentation).

A review. We saw ways to sum an array of integers. With reduce() we can sum ints in a stream. With a for-loop we sum numbers in an imperative way.

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Java Sum Methods: IntStream and reduce

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