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In this article, the editor introduces in detail "how to achieve random quick sorting in java". The content is detailed, the steps are clear, and the details are handled properly. I hope this article "how to achieve random quick sorting in java" can help you solve your doubts.

Brief introduction

Quick sorting also adopts the idea of division and system. So what's the difference between quick sort and merge sort?

Merge sorting is to split all the elements into ordered arrays and then merge them.

The left part is smaller than the middle node, and the right part is larger than the middle node.

Then deal with the array on the left and the array on the right of the combination.

An example of quick sorting

If we have an array: 29, 10, 14, 37, 20, 25, 4, 15, how to sort it quickly?

Take a look at an animation first:

Let's analyze the steps of quick sorting again.

We chose the leftmost element 29 as the middle point element, and then divided the array into three parts: [0, 14, 15, 20, 25], [29], [44, 37].

The intermediate node 29 has been sorted and does not need to be processed.

Next we will quickly sort the left and right respectively. You end up with an array in which all elements are sorted.

Java Code implementation of Quick sort

Let's first look at the core part of partition, how to divide the array into left and right parts with the middle node as the boundary?

Our end result is to split the array into three parts.

First, we select the leftmost element as the value of the intermediate node. Then iterate through the other elements in the array.

Suppose that the element index to be traversed is massively indexed.

Consider two cases. The first case is that the element in the array is larger than the value of the intermediate node.

In this case, m does not need to be moved, and karm1 can continue to traverse.

In the second case, the elements in the array are smaller than the values of the intermediate nodes.

Because the element on the left of m is smaller than the value of the middle node, in this case m needs to be + 1, that is, move one bit to the right.

At present, the element in mroom1 position has not yet been compared, or it is larger than the value of the intermediate node. We can skillfully swap the position between the element in mroom1 position and the element in k position. This still ensures that the element on the left side of m is smaller than the value of the intermediate node.

Summarize the above analysis into the java code as follows:

Private int partition (int [] array, int I, int j) {/ / chooses the leftmost element as the center point, and middleValue is the value of the center point int middleValue = array [I]; int middleIndex = I; / / traverses the entire array for (int k = iCo1) K a [low.. m-1], pivot, a [m+1..high] / / recursively traverses the left part of doQuickSort (array, low, middleIndex-1); / / a [m] is the central node and has been ordered, so there is no need to continue traversing / / recursively traverse the right part of doQuickSort (array, middleIndex+1, high). Log.info ("array after QuickSort: {}", array);}}

The code for divide is simple. After finding the location of the intermediate node, we can iterate through the left and right sides of the array. Finally, we get a sorted array.

Java implementation of Random Quick sort

In the above example, the selection of our intermediate node is the leftmost element of the array. In order to ensure the efficiency of sorting, we can randomly select an element from the array as the intermediate node.

Private int partition (int [] array, int I, int j) {/ / randomly selects an element as the central point, and middleValue is the value of the central point int randomIndex=i+new Random (). NextInt (jmuri); log.info ("randomIndex: {}", randomIndex); / / first, the logical swap of QuickSort (array, I, randomIndex) can be reused by exchanging the value of randomIndex and I. Int middleValue = array [I]; int middleIndex = I; / / traverses the entire array for from I (int k = iDefin1; k

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