निर्भर करता है। आप कितने नंबर जोड़ रहे हैं? उपरोक्त सुझावों में से कई का परीक्षण:
import java.text.NumberFormat;
import java.util.Arrays;
import java.util.Locale;
public class Main {
public static final NumberFormat FORMAT = NumberFormat.getInstance(Locale.US);
public static long sumParallel(int[] array) {
final long start = System.nanoTime();
int sum = Arrays.stream(array).parallel().reduce(0,(a,b)-> a + b);
final long end = System.nanoTime();
System.out.println(sum);
return end - start;
}
public static long sumStream(int[] array) {
final long start = System.nanoTime();
int sum = Arrays.stream(array).reduce(0,(a,b)-> a + b);
final long end = System.nanoTime();
System.out.println(sum);
return end - start;
}
public static long sumLoop(int[] array) {
final long start = System.nanoTime();
int sum = 0;
for (int v: array) {
sum += v;
}
final long end = System.nanoTime();
System.out.println(sum);
return end - start;
}
public static long sumArray(int[] array) {
final long start = System.nanoTime();
int sum = Arrays.stream(array) .sum();
final long end = System.nanoTime();
System.out.println(sum);
return end - start;
}
public static long sumStat(int[] array) {
final long start = System.nanoTime();
int sum = 0;
final long end = System.nanoTime();
System.out.println(sum);
return end - start;
}
public static void test(int[] nums) {
System.out.println("------");
System.out.println(FORMAT.format(nums.length) + " numbers");
long p = sumParallel(nums);
System.out.println("parallel " + FORMAT.format(p));
long s = sumStream(nums);
System.out.println("stream " + FORMAT.format(s));
long ar = sumArray(nums);
System.out.println("arrays " + FORMAT.format(ar));
long lp = sumLoop(nums);
System.out.println("loop " + FORMAT.format(lp));
}
public static void testNumbers(int howmany) {
int[] nums = new int[howmany];
for (int i =0; i < nums.length;i++) {
nums[i] = (i + 1)%100;
}
test(nums);
}
public static void main(String[] args) {
testNumbers(3);
testNumbers(300);
testNumbers(3000);
testNumbers(30000);
testNumbers(300000);
testNumbers(3000000);
testNumbers(30000000);
testNumbers(300000000);
}
}
मैंने पाया, एक 8 कोर, 16 G Ubuntu18 मशीन का उपयोग करते हुए, लूप छोटे मूल्यों के लिए सबसे तेज़ था और बड़े के लिए समानांतर था। लेकिन निश्चित रूप से यह आपके द्वारा चलाए जा रहे हार्डवेयर पर निर्भर करेगा:
------
3 numbers
6
parallel 4,575,234
6
stream 209,849
6
arrays 251,173
6
loop 576
------
300 numbers
14850
parallel 671,428
14850
stream 73,469
14850
arrays 71,207
14850
loop 4,958
------
3,000 numbers
148500
parallel 393,112
148500
stream 306,240
148500
arrays 335,795
148500
loop 47,804
------
30,000 numbers
1485000
parallel 794,223
1485000
stream 1,046,927
1485000
arrays 366,400
1485000
loop 459,456
------
300,000 numbers
14850000
parallel 4,715,590
14850000
stream 1,369,509
14850000
arrays 1,296,287
14850000
loop 1,327,592
------
3,000,000 numbers
148500000
parallel 3,996,803
148500000
stream 13,426,933
148500000
arrays 13,228,364
148500000
loop 1,137,424
------
30,000,000 numbers
1485000000
parallel 32,894,414
1485000000
stream 131,924,691
1485000000
arrays 131,689,921
1485000000
loop 9,607,527
------
300,000,000 numbers
1965098112
parallel 338,552,816
1965098112
stream 1,318,649,742
1965098112
arrays 1,308,043,340
1965098112
loop 98,986,436