java實現(xiàn)的各種排序算法代碼示例
折半插入排序
折半插入排序是對直接插入排序的簡單改進。此處介紹的折半插入,其實就是通過不斷地折半來快速確定第i個元素的
插入位置,這實際上是一種查找算法:折半查找。Java的Arrays類里的binarySearch()方法,就是折半查找的實現(xiàn),用
于從指定數(shù)組中查找指定元素,前提是該數(shù)組已經(jīng)處于有序狀態(tài)。與直接插入排序的效果相同,只是更快了一些,因
為折半插入排序可以更快地確定第i個元素的插入位置
代碼:
package interview; /** * @author Administrator * 折半插入排序 */ public class BinaryInsertSort { public static void binaryInsertSort(DataWrap[] data) { System.out.println("開始排序"); int arrayLength = data.length; for (int i = 1; i < arrayLength; i++) { DataWrap temp = data[i]; int low = 0; int high = i - 1; while (low <= high) { int mid = (low + high) / 2; if (temp.compareTo(data[mid]) > 0) { low = mid + 1; } else { high = mid - 1; } } for (int j = i; j > low; j--) { data[j] = data[j - 1]; } data[low] = temp; System.out.println(java.util.Arrays.toString(data)); } } public static void main(String[] args) { DataWrap[] data = { new DataWrap(9, ""), new DataWrap(-16, ""), new DataWrap(21, "*"), new DataWrap(23, ""), new DataWrap(-30, ""), new DataWrap(-49, ""), new DataWrap(21, ""), new DataWrap(30, "*"), new DataWrap(30, "")}; System.out.println("排序之前:\n" + java.util.Arrays.toString(data)); binaryInsertSort(data); System.out.println("排序之后:\n" + java.util.Arrays.toString(data)); } }
結(jié)果:
排序之前: [9, -16, 21*, 23, -30, -49, 21, 30*, 30] 開始排序 [-16, 9, 21*, 23, -30, -49, 21, 30*, 30] [-16, 9, 21*, 23, -30, -49, 21, 30*, 30] [-16, 9, 21*, 23, -30, -49, 21, 30*, 30] [-30, -16, 9, 21*, 23, -49, 21, 30*, 30] [-49, -30, -16, 9, 21*, 23, 21, 30*, 30] [-49, -30, -16, 9, 21, 21*, 23, 30*, 30] [-49, -30, -16, 9, 21, 21*, 23, 30*, 30] [-49, -30, -16, 9, 21, 21*, 23, 30, 30*] 排序之后: [-49, -30, -16, 9, 21, 21*, 23, 30, 30*]
冒泡排序
代碼:
package interview; /** * @author Administrator * 冒泡排序 */ public class BubbleSort { public static void bubbleSort(DataWrap[] data) { System.out.println("開始排序"); int arrayLength = data.length; for (int i = 0; i < arrayLength - 1; i++) { boolean flag = false; for (int j = 0; j < arrayLength - 1 - i; j++) { if (data[j].compareTo(data[j + 1]) > 0) { DataWrap temp = data[j + 1]; data[j + 1] = data[j]; data[j] = temp; flag = true; } } System.out.println(java.util.Arrays.toString(data)); if (!flag) break; } } public static void main(String[] args) { DataWrap[] data = { new DataWrap(9, ""), new DataWrap(-16, ""), new DataWrap(21, "*"), new DataWrap(23, ""), new DataWrap(-30, ""), new DataWrap(-49, ""), new DataWrap(21, ""), new DataWrap(30, "*"), new DataWrap(30, "")}; System.out.println("排序之前:\n" + java.util.Arrays.toString(data)); bubbleSort(data); System.out.println("排序之后:\n" + java.util.Arrays.toString(data)); } }
運行結(jié)果:
排序之前: [9, -16, 21*, 23, -30, -49, 21, 30*, 30] 開始排序 [-16, 9, 21*, -30, -49, 21, 23, 30*, 30] [-16, 9, -30, -49, 21*, 21, 23, 30*, 30] [-16, -30, -49, 9, 21*, 21, 23, 30*, 30] [-30, -49, -16, 9, 21*, 21, 23, 30*, 30] [-49, -30, -16, 9, 21*, 21, 23, 30*, 30] [-49, -30, -16, 9, 21*, 21, 23, 30*, 30] 排序之后: [-49, -30, -16, 9, 21*, 21, 23, 30*, 30]
桶式排序
算法的時間效率:時間效率極高,只需經(jīng)過兩輪遍歷即可算法的空間效率:空間開銷較大,需要兩個數(shù)組來完成,算
法的穩(wěn)定性:穩(wěn)定
代碼:
package interview; import java.util.Arrays; /** * @author Administrator * 桶式排序 */ public class BucketSort { public static void bucketSort(DataWrap[] data, int min, int max) { System.out.println("開始排序"); int arrayLength = data.length; DataWrap[] temp = new DataWrap[arrayLength]; int[] buckets = new int[max - min]; for (int i = 0; i < arrayLength; i++) { buckets[data[i].data - min]++; } System.out.println(Arrays.toString(buckets)); for (int i = 1; i < max - min; i++) { buckets[i] = buckets[i] + buckets[i - 1]; } System.out.println(Arrays.toString(buckets)); System.arraycopy(data, 0, temp, 0, arrayLength); for (int k = arrayLength - 1; k >= 0; k--) { data[--buckets[temp[k].data - min]] = temp[k]; } } public static void main(String[] args) { DataWrap[] data = { new DataWrap(9, ""), new DataWrap(5, ""), new DataWrap(-1, ""), new DataWrap(8, ""), new DataWrap(5, "*"), new DataWrap(7, ""), new DataWrap(3, ""), new DataWrap(-3, ""), new DataWrap(1, ""),new DataWrap(3, "*")}; System.out.println("排序之前:\n" + java.util.Arrays.toString(data)); bucketSort(data, -3, 10); System.out.println("排序之后:\n" + java.util.Arrays.toString(data)); } }
結(jié)果
排序之前: [9, 5, -1, 8, 5*, 7, 3, -3, 1, 3*] 開始排序 [1, 0, 1, 0, 1, 0, 2, 0, 2, 0, 1, 1, 1] [1, 1, 2, 2, 3, 3, 5, 5, 7, 7, 8, 9, 10] 排序之后: [-3, -1, 1, 3, 3*, 5, 5*, 7, 8, 9]
堆排序
代碼:
package interview; /** * @author Administrator * 堆排序 */ public class HeapSort { public static void heapSort(DataWrap[] data) { System.out.println("開始排序"); int arrayLength = data.length; // 循環(huán)建堆 for (int i = 0; i < arrayLength - 1; i++) { // 建堆 builMaxdHeap(data, arrayLength - 1 - i); // 交換堆頂和最后一個元素 swap(data, 0, arrayLength - 1 - i); System.out.println(java.util.Arrays.toString(data)); } } // 對data數(shù)組從0到lastIndex建大頂堆 private static void builMaxdHeap(DataWrap[] data, int lastIndex) { // 從lastIndex處節(jié)點(最后一個節(jié)點)的父節(jié)點開始 for (int i = (lastIndex - 1) / 2; i >= 0; i--) { // k保存當(dāng)前正在判斷的節(jié)點 int k = i; // 如果當(dāng)前k節(jié)點的子節(jié)點存在 while (k * 2 + 1 <= lastIndex) { // k節(jié)點的左子節(jié)點的索引 int biggerIndex = 2 * k + 1; // 如果biggerIndex小于lastIndex,即biggerIndex +1 // 代表k節(jié)點的右子節(jié)點存在 if (biggerIndex < lastIndex) { // 如果右子節(jié)點的值較大 if (data[biggerIndex].compareTo(data[biggerIndex + 1]) < 0) { // biggerIndex總是記錄較大子節(jié)點的索引 biggerIndex++; } } // 如果k節(jié)點的值小于其較大子節(jié)點的值 if (data[k].compareTo(data[biggerIndex]) < 0) { // 交換它們 swap(data, k, biggerIndex); // 將biggerIndex賦給k,開始while循環(huán)的下一次循環(huán) // 重新保證k節(jié)點的值大于其左、右節(jié)點的值 k = biggerIndex; } else { break; } } } } // 交換data數(shù)組中i、j兩個索引處的元素 private static void swap(DataWrap[] data, int i, int j) { DataWrap temp = data[i]; data[i] = data[j]; data[j] = temp; } public static void main(String[] args) { DataWrap[] data = { new DataWrap(9, ""), new DataWrap(-16, ""), new DataWrap(21, "*"), new DataWrap(23, ""), new DataWrap(-30, ""), new DataWrap(-49, ""), new DataWrap(21, ""), new DataWrap(30, "*"), new DataWrap(30, "")}; System.out.println("排序之前:\n" + java.util.Arrays.toString(data)); heapSort(data); System.out.println("排序之后:\n" + java.util.Arrays.toString(data)); } }
結(jié)果:
排序之前: [9, -16, 21*, 23, -30, -49, 21, 30*, 30] 開始排序 [-16, 30, 21*, 23, -30, -49, 21, 9, 30*] [-16, 23, 21*, 9, -30, -49, 21, 30, 30*] [21, 9, 21*, -16, -30, -49, 23, 30, 30*] [-49, 9, 21*, -16, -30, 21, 23, 30, 30*] [-30, 9, -49, -16, 21*, 21, 23, 30, 30*] [-30, -16, -49, 9, 21*, 21, 23, 30, 30*] [-49, -30, -16, 9, 21*, 21, 23, 30, 30*] [-49, -30, -16, 9, 21*, 21, 23, 30, 30*] 排序之后: [-49, -30, -16, 9, 21*, 21, 23, 30, 30*]
直接插入排序
package interview; public class InsertSort { public static void insertSort(DataWrap[] data){ System.out.println("開始排序"); int arrayLength = data.length; for(int i = 1;i < arrayLength;i++){ DataWrap temp = data[i]; if(data[i].compareTo(data[i-1]) < 0){ int j = i -1; for(;j >= 0 && data[j].compareTo(temp) > 0;j--){ data[j +1] = data[j]; } data[j + 1] = temp; } System.out.println(java.util.Arrays.toString(data)); } } public static void main(String[] args) { DataWrap[] data = { new DataWrap(9, ""), new DataWrap(-16, ""), new DataWrap(21, "*"), new DataWrap(23, ""), new DataWrap(-30, ""), new DataWrap(-49, ""), new DataWrap(21, ""), new DataWrap(30, "*"), new DataWrap(30, "")}; System.out.println("排序之前:\n" + java.util.Arrays.toString(data)); insertSort(data); System.out.println("排序之后:\n" + java.util.Arrays.toString(data)); } }
結(jié)果
排序之前: [9, -16, 21*, 23, -30, -49, 21, 30*, 30] 開始排序 [-16, 9, 21*, 23, -30, -49, 21, 30*, 30] [-16, 9, 21*, 23, -30, -49, 21, 30*, 30] [-16, 9, 21*, 23, -30, -49, 21, 30*, 30] [-30, -16, 9, 21*, 23, -49, 21, 30*, 30] [-49, -30, -16, 9, 21*, 23, 21, 30*, 30] [-49, -30, -16, 9, 21*, 21, 23, 30*, 30] [-49, -30, -16, 9, 21*, 21, 23, 30*, 30] [-49, -30, -16, 9, 21*, 21, 23, 30*, 30] 排序之后: [-49, -30, -16, 9, 21*, 21, 23, 30*, 30]
歸并排序
算法的時間效率:歸并算法需要遞歸地進行分解、合并,每進行一趟歸并排序,需要merge()方法一次,每次執(zhí)行
merge()需要比較n次,較差,需要一個與原始序列同樣大小的輔助序列。算法的穩(wěn)定性:穩(wěn)定
代碼:
package interview; /** * @author Administrator * 歸并排序 */ public class MergeSort { public static void mergeSort(DataWrap[] data) { // 歸并排序 sort(data, 0, data.length - 1); } // 將索引從left到right范圍的數(shù)組元素進行歸并排序 private static void sort(DataWrap[] data, int left, int right) { if(left < right){ //找出中間索引 int center = (left + right)/2; sort(data,left,center); sort(data,center+1,right); //合并 merge(data,left,center,right); } } // 將兩個數(shù)組進行歸并,歸并前兩個數(shù)組已經(jīng)有序,歸并后依然有序 private static void merge(DataWrap[] data, int left, int center, int right) { DataWrap[] tempArr = new DataWrap[data.length]; int mid = center + 1; int third = left; int temp = left; while (left <= center && mid <= right) { if (data[left].compareTo(data[mid]) <= 0) { tempArr[third++] = data[left++]; } else { tempArr[third++] = data[mid++]; } } while (mid <= right) { tempArr[third++] = data[mid++]; } while (left <= center) { tempArr[third++] = data[left++]; } while (temp <= right) { data[temp] = tempArr[temp++]; } } public static void main(String[] args) { DataWrap[] data = { new DataWrap(9, ""), new DataWrap(-16, ""), new DataWrap(21, "*"), new DataWrap(23, ""), new DataWrap(-30, ""), new DataWrap(-49, ""), new DataWrap(21, ""), new DataWrap(30, "*"), new DataWrap(30, "") }; System.out.println("排序之前:\n" + java.util.Arrays.toString(data)); mergeSort(data); System.out.println("排序之后:\n" + java.util.Arrays.toString(data)); } }
結(jié)果:
排序之前: [9, -16, 21*, 23, -30, -49, 21, 30*, 30] 排序之后: [-49, -30, -16, 9, 21*, 21, 23, 30*, 30]
基數(shù)排序
基數(shù)排序已經(jīng)不再是一種常規(guī)的排序方法,它更多地像是一種排序方法的應(yīng)用,基數(shù)排序必須依賴于另外的排序方法。
基數(shù)排序的總體思路就是將待排數(shù)據(jù)拆分成多個關(guān)鍵字進行排序,也就是說,基數(shù)排序的實質(zhì)是多關(guān)鍵字排序。
多關(guān)鍵字排序的思路是將待排數(shù)據(jù)里的排序關(guān)鍵字拆分成多個排序關(guān)鍵字:第1個子關(guān)鍵字、第2個子關(guān)鍵字、第3個子
關(guān)鍵字。。。然后,根據(jù)子關(guān)鍵字對待排數(shù)據(jù)進行排序。在進行多關(guān)鍵字排序時有兩種解決方案:
最高位優(yōu)先法MSD
最低位優(yōu)先法LSD
比較MSD法和LSD法,一般來講,LSD法要比MSD法來得簡單,因為LSD法是從頭到尾進行若干次分配和收集,執(zhí)行
的次數(shù)取決于構(gòu)成關(guān)鍵字值的成分為多少;而MSD法則要處理各序列與子序列的獨立排序問題,就可能復(fù)雜一些。
代碼:
package interview; import java.util.Arrays; /** * @author Administrator * 基數(shù)排序 */ public class MultiKeyRadixSort { public static void radixSort(int[] data, int radix, int d) { System.out.println("開始排序:"); int arrayLength = data.length; int[] temp = new int[arrayLength]; int[] buckets = new int[radix]; for (int i = 0, rate = 1; i < d; i++) { // 重置count數(shù)組,開始統(tǒng)計第二個關(guān)鍵字 Arrays.fill(buckets, 0); // 當(dāng)data數(shù)組的元素復(fù)制到temp數(shù)組中進行緩存 System.arraycopy(data, 0, temp, 0, arrayLength); for (int j = 0; j < arrayLength; j++) { int subKey = (temp[j] / rate) % radix; buckets[subKey]++; } for (int j = 1; j < radix; j++) { buckets[j] = buckets[j] + buckets[j - 1]; } for (int m = arrayLength - 1; m >= 0; m--) { int subKey = (temp[m] / rate) % radix; data[--buckets[subKey]] = temp[m]; } System.out.println("對" + rate + "位上子關(guān)鍵字排序:" + java.util.Arrays.toString(data)); rate *= radix; } } public static void main(String[] args) { int[] data = { 1100, 192, 221, 12, 13 }; System.out.println("排序之前:\n" + java.util.Arrays.toString(data)); radixSort(data, 10, 4); System.out.println("排序之后:\n" + java.util.Arrays.toString(data)); } }
結(jié)果
排序之前: [1100, 192, 221, 12, 13] 開始排序: 對1位上子關(guān)鍵字排序:[1100, 221, 192, 12, 13] 對10位上子關(guān)鍵字排序:[1100, 12, 13, 221, 192] 對100位上子關(guān)鍵字排序:[12, 13, 1100, 192, 221] 對1000位上子關(guān)鍵字排序:[12, 13, 192, 221, 1100] 排序之后: [12, 13, 192, 221, 1100]
快速排序
代碼:
package interview; /** * @author Administrator * 快速排序 */ public class QuickSort { private static void swap(DataWrap[] data, int i, int j) { DataWrap temp = data[i]; data[i] = data[j]; data[j] = temp; } private static void subSort(DataWrap[] data, int start, int end) { if (start < end) { DataWrap base = data[start]; int i = start; int j = end + 1; while (true) { while (i < end && data[++i].compareTo(base) <= 0) ; while (j > start && data[--j].compareTo(base) >= 0) ; if (i < j) { swap(data, i, j); } else { break; } } swap(data, start, j); subSort(data, start, j - 1); subSort(data, j + 1, end); } } public static void quickSort(DataWrap[] data){ subSort(data,0,data.length-1); } public static void main(String[] args) { DataWrap[] data = { new DataWrap(9, ""), new DataWrap(-16, ""), new DataWrap(21, "*"), new DataWrap(23, ""), new DataWrap(-30, ""), new DataWrap(-49, ""), new DataWrap(21, ""), new DataWrap(30, "*"), new DataWrap(30, "") }; System.out.println("排序之前:\n" + java.util.Arrays.toString(data)); quickSort(data); System.out.println("排序之后:\n" + java.util.Arrays.toString(data)); } }
結(jié)果
排序之前: [9, -16, 21*, 23, -30, -49, 21, 30*, 30] 排序之后: [-49, -30, -16, 9, 21, 21*, 23, 30*, 30]
直接選擇排序
代碼:
package interview; /** * @author Administrator * 直接選擇排序 */ public class SelectSort { public static void selectSort(DataWrap[] data) { System.out.println("開始排序"); int arrayLength = data.length; for (int i = 0; i < arrayLength - 1; i++) { for (int j = i + 1; j < arrayLength; j++) { if (data[i].compareTo(data[j]) > 0) { DataWrap temp = data[i]; data[i] = data[j]; data[j] = temp; } } System.out.println(java.util.Arrays.toString(data)); } } public static void main(String[] args) { DataWrap[] data = { new DataWrap(9, ""), new DataWrap(-16, ""), new DataWrap(21, "*"), new DataWrap(23, ""), new DataWrap(-30, ""), new DataWrap(-49, ""), new DataWrap(21, ""), new DataWrap(30, "*"), new DataWrap(30, "") }; System.out.println("排序之前:\n" + java.util.Arrays.toString(data)); selectSort(data); System.out.println("排序之后:\n" + java.util.Arrays.toString(data)); } }
排序之前: [9, -16, 21*, 23, -30, -49, 21, 30*, 30] 開始排序 [-49, 9, 21*, 23, -16, -30, 21, 30*, 30] [-49, -30, 21*, 23, 9, -16, 21, 30*, 30] [-49, -30, -16, 23, 21*, 9, 21, 30*, 30] [-49, -30, -16, 9, 23, 21*, 21, 30*, 30] [-49, -30, -16, 9, 21*, 23, 21, 30*, 30] [-49, -30, -16, 9, 21*, 21, 23, 30*, 30] [-49, -30, -16, 9, 21*, 21, 23, 30*, 30] [-49, -30, -16, 9, 21*, 21, 23, 30*, 30] 排序之后: [-49, -30, -16, 9, 21*, 21, 23, 30*, 30]
希爾排序
代碼:
package interview; /** * @author Administrator * Shell排序 */ public class ShellSort { public static void ShellSort(DataWrap[] data) { System.out.println("開始排序"); int arrayLength = data.length; int h = 1; /** * 將數(shù)組分割成若干個子序列 */ while (h <= arrayLength / 3) { h = h * 3 + 1; System.out.println("h的結(jié)果:" + h); } while (h > 0) { System.out.println("===h的值:" + h + "==="); /** * 將分成的若干子序列進行直接插入排序 */ for (int i = h; i < arrayLength; i++) { DataWrap temp = data[i]; if (data[i].compareTo(data[i - h]) < 0) { int j = i - h; for (; j >= 0 && data[j].compareTo(temp) > 0; j -= h) { data[j + h] = data[j]; } data[j + h] = temp; } System.out.println(java.util.Arrays.toString(data)); } h = (h - 1) / 3; } } public static void main(String[] args) { DataWrap[] data = { new DataWrap(9, ""), new DataWrap(-16, ""), new DataWrap(21, "*"), new DataWrap(23, ""), new DataWrap(-30, ""), new DataWrap(-49, ""), new DataWrap(21, ""), new DataWrap(30, "*"), new DataWrap(30, "")}; System.out.println("排序之前:\n" + java.util.Arrays.toString(data)); ShellSort(data); System.out.println("排序之后:\n" + java.util.Arrays.toString(data)); } }
結(jié)果:
排序之前: [9, -16, 21*, 23, -30, -49, 21, 30*, 30] 開始排序 h的結(jié)果:4 ===h的值:4=== [-30, -16, 21*, 23, 9, -49, 21, 30*, 30] [-30, -49, 21*, 23, 9, -16, 21, 30*, 30] [-30, -49, 21*, 23, 9, -16, 21, 30*, 30] [-30, -49, 21*, 23, 9, -16, 21, 30*, 30] [-30, -49, 21*, 23, 9, -16, 21, 30*, 30] ===h的值:1=== [-49, -30, 21*, 23, 9, -16, 21, 30*, 30] [-49, -30, 21*, 23, 9, -16, 21, 30*, 30] [-49, -30, 21*, 23, 9, -16, 21, 30*, 30] [-49, -30, 9, 21*, 23, -16, 21, 30*, 30] [-49, -30, -16, 9, 21*, 23, 21, 30*, 30] [-49, -30, -16, 9, 21*, 21, 23, 30*, 30] [-49, -30, -16, 9, 21*, 21, 23, 30*, 30] [-49, -30, -16, 9, 21*, 21, 23, 30*, 30] 排序之后: [-49, -30, -16, 9, 21*, 21, 23, 30*, 30]
所需要的工具類:
package interview; public class DataWrap implements Comparable<DataWrap>{ int data; String flag; public DataWrap(int data, String flag) { this.data = data; this.flag = flag; } public String toString(){ return data + flag; } @Override public int compareTo(DataWrap dw) { return this.data > dw.data ? 1 : (this.data == dw.data ? 0 : -1); } }
以上代碼親測可用,供大家參考。
關(guān)于java實現(xiàn)的各種排序算法代碼示例的內(nèi)容,就到這里,希望對大家有所幫助。感興趣的朋友可以繼續(xù)參閱本站:Java 蒙特卡洛算法求圓周率近似值實例詳解、Java編程實現(xiàn)遞增排序鏈表的合并、Java編程ssh整合常見錯誤解析等,有什么問題可以隨時留言,小編會及時回復(fù)大家的。這里推薦本站幾本關(guān)于Java的書籍,免費下載,供廣大編程愛好及工作者參考。
Java經(jīng)典實例(第三版) 完整版 ([美]達爾文) 中文pdf掃描版
http://www.dbjr.com.cn/books/577859.html
數(shù)據(jù)挖掘:實用機器學(xué)習(xí)技術(shù)及Java實現(xiàn)(英文第2版)高清PDF
www.dbjr.com.cn/books/577815.html
Java初級開發(fā)工程師面試題匯總.PDF
http://www.dbjr.com.cn/books/576989.html
希望大家能夠喜歡。
相關(guān)文章
基于mybatis?plus實現(xiàn)數(shù)據(jù)源動態(tài)添加、刪除、切換,自定義數(shù)據(jù)源的示例代碼
這篇文章主要介紹了基于mybatis?plus實現(xiàn)數(shù)據(jù)源動態(tài)添加、刪除、切換,自定義數(shù)據(jù)源,本文通過實例代碼給大家介紹的非常詳細(xì),對大家的學(xué)習(xí)或工作具有一定的參考借鑒價值,需要的朋友可以參考下2022-03-03詳解Spring Cloud Finchley版中Consul多實例注冊的問題處理
這篇文章主要介紹了詳解Spring Cloud Finchley版中Consul多實例注冊的問題處理,小編覺得挺不錯的,現(xiàn)在分享給大家,也給大家做個參考。一起跟隨小編過來看看吧2018-08-08SpringBoot集成logback打印彩色日志的代碼實現(xiàn)
Logback是由log4j創(chuàng)始人設(shè)計的另一個開源日志組件,默認(rèn)情況下,Spring?Boot會用Logback來記錄日志,并用INFO級別輸出到控制臺,本文給大家介紹了SpringBoot集成logback打印彩色日志,需要的朋友可以參考下2024-03-03詳解java中Reference的實現(xiàn)與相應(yīng)的執(zhí)行過程
不知道大家知不知道特殊的reference對象都是被jvm專門處理的,所以這篇文章就相應(yīng)的工作流程和referencequeue之間的協(xié)作進行梳理.有需要的朋友們可以參考借鑒。2016-09-09Hibernate用ThreadLocal模式(線程局部變量模式)管理Session
今天小編就為大家分享一篇關(guān)于Hibernate用ThreadLocal模式(線程局部變量模式)管理Session,小編覺得內(nèi)容挺不錯的,現(xiàn)在分享給大家,具有很好的參考價值,需要的朋友一起跟隨小編來看看吧2019-03-03mybatis入門_動力節(jié)點Java學(xué)院整理
這篇文章主要為大家詳細(xì)介紹了mybatis入門的相關(guān)資料,具有一定的參考價值,感興趣的小伙伴們可以參考一下2017-09-09