Merge Sort - Implementation Improvements

Sorting Algorithm Tutorials - Herong's Tutorial Examples

∟Merge Sort Algorithm and Java Implementation

∟Merge Sort - Implementation Improvements

This section provides a tutorial on how to improve the performance of the Merge Sort implementation by dividing data elements into 3 sections.

One way to improve the performance is to divide data elements into 3 sections. Sort them separately, then merge them. Merging 3 sorted sections is more efficient than merging 2 sections. Here my improved implementation:

/* HyArrays.java
 * This class contains sorting methods similar to java.util.Arrays.sort().
 * All sorting methods should have a signature of
 * %Sort(Object[] a, int fromIndex, int toIndex)
 * where "fromIndex" is inclusive, and "toIndex" is exclusive.
 * Copyright (c) 2011 HerongYang.com. All Rights Reserved.
 */
public class HyArrays {
  public static void mergeSort3(HyObject[] a, int fromIndex,
     int toIndex) {
     HyObject[] b = new HyObject[toIndex];
     for (int i=fromIndex; i<toIndex; i++) {
        b[i] = a[i];
     }
     mergeSortInternal3(b, a, fromIndex, toIndex);
  }
  private static void mergeSortInternal3(HyObject[] a, HyObject[] b,
     int fromIndex, int toIndex) {
     if (toIndex-fromIndex<=1) {
        return;
     } else if (toIndex-fromIndex==2) {
        if ((a[fromIndex]).compareTo(a[toIndex-1])>0) {
           b[toIndex-1] = a[fromIndex];
           b[fromIndex] = a[toIndex-1];
        }
     } else {
        int iLeft = (toIndex-fromIndex)/3 + fromIndex;
        int iRight = (toIndex-iLeft)/2 + iLeft;
        mergeSortInternal3(b,a,fromIndex,iLeft);
        mergeSortInternal3(b,a,iLeft,iRight);
        mergeSortInternal3(b,a,iRight,toIndex);
        int iFirst = fromIndex;
        int iSecond = iLeft;
        int iThird = iRight;
        int i = fromIndex;
        while (iFirst<iLeft && iSecond<iRight && iThird<toIndex) {
           if ((a[iFirst]).compareTo(a[iSecond])<0) {
              if ((a[iFirst]).compareTo(a[iThird])<0) {
                 b[i] = a[iFirst];
                 iFirst++;
              } else {
                 b[i] = a[iThird];
                 iThird++;
              }
           } else {
              if ((a[iSecond]).compareTo(a[iThird])<0) {
                 b[i] = a[iSecond];
                 iSecond++;
              } else {
                 b[i] = a[iThird];
                 iThird++;
              }
           }
           i++;
        }
        while (iFirst<iLeft && iSecond<iRight) {
           if ((a[iFirst]).compareTo(a[iSecond])<0) {
              b[i] = a[iFirst];
              iFirst++;
           } else {
              b[i] = a[iSecond];
              iSecond++;
           }
           i++;
        }
        while (iSecond<iRight && iThird<toIndex) {
           if ((a[iSecond]).compareTo(a[iThird])<0) {
              b[i] = a[iSecond];
              iSecond++;
           } else {
              b[i] = a[iThird];
              iThird++;
           }
           i++;
        }
        while (iThird<toIndex && iFirst<iLeft) {
           if ((a[iFirst]).compareTo(a[iThird])<0) {
              b[i] = a[iFirst];
              iFirst++;
           } else {
              b[i] = a[iThird];
              iThird++;
           }
           i++;
        }
        while (iFirst<iLeft) {
           b[i] = a[iFirst];
           iFirst++;
           i++;
        }
        while (iSecond<iRight) {
           b[i] = a[iSecond];
           iSecond++;
           i++;
        }
        while (iThird<toIndex) {
           b[i] = a[iThird];
           iThird++;
           i++;
        }
     }
  }
}

Performance was indeed improved:

Array size: 100000
Average sorting time: 14 milliseconds
Number of tests: 1000
Performance: 0.14 O(N) microseconds
Performance: 0.008428839878591473 O(N*Log2(N)) microseconds
Performance: 1.4E-6 O(N*N) microseconds

Array size: 200000
Average sorting time: 43 milliseconds
Number of tests: 1000
Performance: 0.215 O(N) microseconds
Performance: 0.012209221438229055 O(N*Log2(N)) microseconds
Performance: 1.075E-6 O(N*N) microseconds

Array size: 300000
Average sorting time: 84 milliseconds
Number of tests: 1000
Performance: 0.28 O(N) microseconds
Performance: 0.015389178889052897 O(N*Log2(N)) microseconds
Performance: 9.333333333333333E-7 O(N*N) microseconds

Please also note that merge sort requires a working array to do the merge. Another direction of improving this implementation is to try to reduce or eliminate the working array.

In case you are using older versions of Java that support only the raw "Comparable" interface type, here is my old implementation:

/* HyArrays.java
 * This class contains sorting methods similar to java.util.Arrays.
 * All sorting methods should have a signature of
 * %Sort(Object[] a, int fromIndex, int toIndex)
 * where "fromIndex" is inclusive, and "toIndex" is exclusive.
 * Copyright (c) 2011 HerongYang.com. All Rights Reserved.
 */
public class HyArrays {
   public static void mergeSort3(Object[] a, int fromIndex,
      int toIndex) {
      Object[] b = new Object[toIndex];
      for (int i=fromIndex; i<toIndex; i++) {
         b[i] = a[i];
      }
      mergeSortInternal3(b, a, fromIndex, toIndex);
   }
   private static void mergeSortInternal3(Object[] a, Object[] b,
      int fromIndex, int toIndex) {
      if (toIndex-fromIndex<=1) {
         return;
      } else if (toIndex-fromIndex==2) {
         if (((Comparable)a[fromIndex]).compareTo(a[toIndex-1])>0) {
            b[toIndex-1] = a[fromIndex];
            b[fromIndex] = a[toIndex-1];
         }
      } else {
         int iLeft = (toIndex-fromIndex)/3 + fromIndex;
         int iRight = (toIndex-iLeft)/2 + iLeft;
         mergeSortInternal3(b,a,fromIndex,iLeft);
         mergeSortInternal3(b,a,iLeft,iRight);
         mergeSortInternal3(b,a,iRight,toIndex);
         int iFirst = fromIndex;
         int iSecond = iLeft;
         int iThird = iRight;
         int i = fromIndex;
         while (iFirst<iLeft && iSecond<iRight && iThird<toIndex) {
            if (((Comparable)a[iFirst]).compareTo(a[iSecond])<0) {
               if (((Comparable)a[iFirst]).compareTo(a[iThird])<0) {
                  b[i] = a[iFirst];
                  iFirst++;
               } else {
                  b[i] = a[iThird];
                  iThird++;
               }
            } else {
               if (((Comparable)a[iSecond]).compareTo(a[iThird])<0) {
                  b[i] = a[iSecond];
                  iSecond++;
               } else {
                  b[i] = a[iThird];
                  iThird++;
               }
            }
            i++;
         }
         while (iFirst<iLeft && iSecond<iRight) {
            if (((Comparable)a[iFirst]).compareTo(a[iSecond])<0) {
               b[i] = a[iFirst];
               iFirst++;
            } else {
               b[i] = a[iSecond];
               iSecond++;
            }
            i++;
         }
         while (iSecond<iRight && iThird<toIndex) {
            if (((Comparable)a[iSecond]).compareTo(a[iThird])<0) {
               b[i] = a[iSecond];
               iSecond++;
            } else {
               b[i] = a[iThird];
               iThird++;
            }
            i++;
         }
         while (iThird<toIndex && iFirst<iLeft) {
            if (((Comparable)a[iFirst]).compareTo(a[iThird])<0) {
               b[i] = a[iFirst];
               iFirst++;
            } else {
               b[i] = a[iThird];
               iThird++;
            }
            i++;
         }
         while (iFirst<iLeft) {
            b[i] = a[iFirst];
            iFirst++;
            i++;
         }
         while (iSecond<iRight) {
            b[i] = a[iSecond];
            iSecond++;
            i++;
         }
         while (iThird<toIndex) {
            b[i] = a[iThird];
            iThird++;
            i++;
         }
      }
   }
}