এটা নির্ভর করে. আপনি কত নম্বর যুক্ত করছেন? উপরোক্ত অনেক পরামর্শের পরীক্ষা করা:
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);
}
}
আমি পেয়েছি, একটি 8 কোর, 16 জি উবুন্টু 18 মেশিন ব্যবহার করে লুপটি ছোট মানগুলির জন্য দ্রুত এবং বৃহত্তর সমান্তরাল ছিল। তবে অবশ্যই এটি আপনি যে হার্ডওয়্যারটি চালাচ্ছেন তার উপর নির্ভর করবে:
------
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