基於Zookeeper實現分佈式鎖詳解
1、什麼是Zookeeper？
Zookeeper是一個分佈式的，開源的分佈式應用程序協調服務，是Hadoop和hbase的重要組件。
引用官網的圖例：
特征：
- zookeeper的數據機構是一種節點樹的數據結構，zNode是基本的單位，znode是一種和unix文件系統相似的節點，可以往這個節點存儲或向這個節點獲取數據
- 通過客戶端可以對znode進行數據操作，還可以註冊watcher監控znode的改變
2、Zookeeper節點類型
- 持久節點（Persistent）
- 持久順序節點（Persistent_Sequential）
- 臨時節點（Ephemeral）
- 臨時順序節點（Ephemeral_Sequential）
3、Zookeeper環境搭建
下載zookeeper，官網鏈接，https://zookeeper.apache.org/releases.html#download，去官網找到對應的軟件下載到本地
修改配置文件，${ZOOKEEPER_HOME}\conf，找到zoo_sample.cfg文件，先備份一份，另外一份修改為zoo.cfg
解壓後點擊zkServer.cmd運行服務端：
4、Zookeeper基本使用
在cmd窗口或者直接在idea編輯器裡的terminal輸入命令：
zkCli.cmd -server 127.0.0.1:2181
輸入命令help查看幫助信息：
ZooKeeper -server host:port -client-configuration properties-file cmd args
addWatch [-m mode] path # optional mode is one of [PERSISTENT, PERSISTENT_RECURSIVE] - default is PERSISTENT_RECURSIVE
addauth scheme auth
close
config [-c] [-w] [-s]
connect host:port
create [-s] [-e] [-c] [-t ttl] path [data] [acl]
delete [-v version] path
deleteall path [-b batch size]
delquota [-n|-b|-N|-B] path
get [-s] [-w] path
getAcl [-s] path
getAllChildrenNumber path
getEphemerals path
history
listquota path
ls [-s] [-w] [-R] path
printwatches on|off
quit
reconfig [-s] [-v version] [[-file path] | [-members serverID=host:port1:port2;port3[,...]*]] | [-add serverId=host:port1:port2;port3[,...]]* [-remove serverId[,...]*]
redo cmdno
removewatches path [-c|-d|-a] [-l]
set [-s] [-v version] path data
setAcl [-s] [-v version] [-R] path acl
setquota -n|-b|-N|-B val path
stat [-w] path
sync path
version
whoami
create [-s] [-e] [-c] [-t ttl] path [data] [acl]，-s表示順序節點，-e表示臨時節點，若不指定表示持久節點，acl是來進行權限控制的
[zk: 127.0.0.1:2181(CONNECTED) 1] create -s /zk-test 0 Created /zk-test0000000000
查看
[zk: 127.0.0.1:2181(CONNECTED) 4] ls / [zk-test0000000000, zookeeper]
設置修改節點數據
set /zk-test 123
獲取節點數據
get /zk-test
ps，zookeeper命令詳情查看help幫助文檔，也可以去官網看看文檔
ok，然後java寫個例子，進行watcher監聽
package com.example.concurrent.zkSample;
import org.I0Itec.zkclient.IZkDataListener;
import org.I0Itec.zkclient.ZkClient;
/**
* <pre>
* Zookeeper 例子
* </pre>
*
* <pre>
* @author mazq
* 修改記錄
* 修改後版本: 修改人： 修改日期: 2021/12/09 16:57 修改內容:
* </pre>
*/
public class ZookeeperSample {
public static void main(String[] args) {
ZkClient client = new ZkClient("localhost:2181");
client.setZkSerializer(new MyZkSerializer());
client.subscribeDataChanges("/zk-test", new IZkDataListener() {
@Override
public void handleDataChange(String dataPath, Object data) throws Exception {
System.out.println("監聽到節點數據改變!");
}
@Override
public void handleDataDeleted(String dataPath) throws Exception {
System.out.println("監聽到節點數據被刪除瞭");
}
});
try {
Thread.sleep(1000 * 60 * 2);
} catch (InterruptedException e) {
e.printStackTrace();
}
}
}
5、Zookeeper應用場景
Zookeeper有什麼典型的應用場景：
- 註冊中心（Dubbo）
- 命名服務
- Master選舉
- 集群管理
- 分佈式隊列
- 分佈式鎖
6、Zookeeper分佈式鎖
Zookeeper適合用來做分佈式鎖，然後具體實現是利用什麼原理？我們知道zookeeper是類似於unix的文件系統，文件系統我們也知道在一個文件夾下面，會有文件名稱不能一致的特性的，也就是互斥的特性。同樣zookeeper也有這個特性，在同個znode節點下面，子節點命名不能重復。所以利用這個特性可以來實現分佈式鎖
業務場景：在高並發的情況下面進行訂單場景，這是一個典型的電商場景
自定義的Zookeeper序列化類：
package com.example.concurrent.zkSample;
import org.I0Itec.zkclient.exception.ZkMarshallingError;
import org.I0Itec.zkclient.serialize.ZkSerializer;
import java.io.UnsupportedEncodingException;
public class MyZkSerializer implements ZkSerializer {
private String charset = "UTF-8";
@Override
public byte[] serialize(Object o) throws ZkMarshallingError {
return String.valueOf(o).getBytes();
}
@Override
public Object deserialize(byte[] bytes) throws ZkMarshallingError {
try {
return new String(bytes , charset);
} catch (UnsupportedEncodingException e) {
throw new ZkMarshallingError();
}
}
}
訂單編號生成器類，因為SimpleDateFormat是線程不安全的，所以還是要加上ThreadLocal
package com.example.concurrent.zkSample;
import java.text.DateFormat;
import java.text.SimpleDateFormat;
import java.util.Date;
import java.util.concurrent.atomic.AtomicInteger;
public class OrderCodeGenerator {
private static final String DATE_FORMAT = "yyyyMMddHHmmss";
private static AtomicInteger ai = new AtomicInteger(0);
private static int i = 0;
private static ThreadLocal<SimpleDateFormat> threadLocal = new ThreadLocal<SimpleDateFormat>() {
@Override
protected SimpleDateFormat initialValue() {
return new SimpleDateFormat(DATE_FORMAT);
}
};
public static DateFormat getDateFormat() {
return (DateFormat) threadLocal.get();
}
public static String generatorOrderCode() {
try {
return getDateFormat().format(new Date(System.currentTimeMillis()))
+ i++;
} finally {
threadLocal.remove();
}
}
}
pom.xml加上zookeeper客戶端的配置：
<dependency>
<groupId>com.101tec</groupId>
<artifactId>zkclient</artifactId>
<version>0.10</version>
</dependency>
實現一個zookeeper分佈式鎖，思路是獲取節點，這個是多線程競爭的，能獲取到鎖，也就是創建節點成功，就執行業務，其它搶不到鎖的線程，阻塞等待，註冊watcher監聽鎖是否釋放瞭，釋放瞭，取消註冊watcher，繼續搶鎖
package com.example.concurrent.zkSample;
import lombok.extern.slf4j.Slf4j;
import org.I0Itec.zkclient.IZkDataListener;
import org.I0Itec.zkclient.ZkClient;
import org.I0Itec.zkclient.exception.ZkNodeExistsException;
import java.util.concurrent.CountDownLatch;
import java.util.concurrent.TimeUnit;
import java.util.concurrent.locks.Condition;
import java.util.concurrent.locks.Lock;
@Slf4j
public class ZKDistributeLock implements Lock {
private String localPath;
private ZkClient zkClient;
ZKDistributeLock(String localPath) {
super();
this.localPath = localPath;
zkClient = new ZkClient("localhost:2181");
zkClient.setZkSerializer(new MyZkSerializer());
}
@Override
public void lock() {
while (!tryLock()) {
waitForLock();
}
}
private void waitForLock() {
// 創建countdownLatch協同
CountDownLatch countDownLatch = new CountDownLatch(1);
// 註冊watcher監聽
IZkDataListener listener = new IZkDataListener() {
@Override
public void handleDataChange(String path, Object o) throws Exception {
//System.out.println("zookeeper data has change!!!");
}
@Override
public void handleDataDeleted(String s) throws Exception {
// System.out.println("zookeeper data has delete!!!");
// 監聽到鎖釋放瞭，釋放線程
countDownLatch.countDown();
}
};
zkClient.subscribeDataChanges(localPath , listener);
// 線程等待
if (zkClient.exists(localPath)) {
try {
countDownLatch.await();
} catch (InterruptedException e) {
e.printStackTrace();
}
}
// 取消註冊
zkClient.unsubscribeDataChanges(localPath , listener);
}
@Override
public void unlock() {
zkClient.delete(localPath);
}
@Override
public boolean tryLock() {
try {
zkClient.createEphemeral(localPath);
} catch (ZkNodeExistsException e) {
return false;
}
return true;
}
@Override
public boolean tryLock(long time, TimeUnit unit) throws InterruptedException {
return false;
}
@Override
public void lockInterruptibly() throws InterruptedException {
}
@Override
public Condition newCondition() {
return null;
}
}
訂單服務api
package com.example.concurrent.zkSample;
public interface OrderService {
void createOrder();
}
訂單服務實現類，加上zookeeper分佈式鎖
package com.example.concurrent.zkSample;
import java.util.concurrent.locks.Lock;
public class OrderServiceInvoker implements OrderService{
@Override
public void createOrder() {
Lock zkLock = new ZKDistributeLock("/zk-test");
//Lock zkLock = new ZKDistributeImproveLock("/zk-test");
String orderCode = null;
try {
zkLock.lock();
orderCode = OrderCodeGenerator.generatorOrderCode();
} finally {
zkLock.unlock();
}
System.out.println(String.format("thread name : %s , orderCode : %s" ,
Thread.currentThread().getName(),
orderCode));
}
}
因為搭建分佈式環境比較繁瑣，所以這裡使用juc裡的並發協同工具類，CyclicBarrier模擬多線程並發的場景，模擬分佈式環境的高並發場景
package com.example.concurrent.zkSample;
import java.util.concurrent.BrokenBarrierException;
import java.util.concurrent.CyclicBarrier;
public class ConcurrentDistributeTest {
public static void main(String[] args) {
// 多線程數
int threadSize = 30;
// 創建多線程循環屏障
CyclicBarrier cyclicBarrier = new CyclicBarrier(threadSize , ()->{
System.out.println("準備完成！");
}) ;
// 模擬分佈式集群的場景
for (int i = 0 ; i < threadSize ; i ++) {
new Thread(()->{
OrderService orderService = new OrderServiceInvoker();
// 所有線程都等待
try {
cyclicBarrier.await();
} catch (InterruptedException e) {
e.printStackTrace();
} catch (BrokenBarrierException e) {
e.printStackTrace();
}
// 模擬並發請求
orderService.createOrder();
}).start();
}
}
}
跑多幾次，沒有發現訂單號重復的情況，分佈式鎖還是有點效果的
thread name : Thread-6 , orderCode : 202112100945110
thread name : Thread-1 , orderCode : 202112100945111
thread name : Thread-13 , orderCode : 202112100945112
thread name : Thread-11 , orderCode : 202112100945113
thread name : Thread-14 , orderCode : 202112100945114
thread name : Thread-0 , orderCode : 202112100945115
thread name : Thread-8 , orderCode : 202112100945116
thread name : Thread-17 , orderCode : 202112100945117
thread name : Thread-10 , orderCode : 202112100945118
thread name : Thread-5 , orderCode : 202112100945119
thread name : Thread-2 , orderCode : 2021121009451110
thread name : Thread-16 , orderCode : 2021121009451111
thread name : Thread-19 , orderCode : 2021121009451112
thread name : Thread-4 , orderCode : 2021121009451113
thread name : Thread-18 , orderCode : 2021121009451114
thread name : Thread-3 , orderCode : 2021121009451115
thread name : Thread-9 , orderCode : 2021121009451116
thread name : Thread-12 , orderCode : 2021121009451117
thread name : Thread-15 , orderCode : 2021121009451118
thread name : Thread-7 , orderCode : 2021121009451219
package com.example.concurrent.zkSample;
import java.util.concurrent.locks.Lock;
public class OrderServiceInvoker implements OrderService{
@Override
public void createOrder() {
//Lock zkLock = new ZKDistributeLock("/zk-test");
//Lock zkLock = new ZKDistributeImproveLock("/zk-test");
String orderCode = null;
try {
//zkLock.lock();
orderCode = OrderCodeGenerator.generatorOrderCode();
} finally {
//zkLock.unlock();
}
System.out.println(String.format("thread name : %s , orderCode : %s" ,
Thread.currentThread().getName(),
orderCode));
}
}
跑多幾次，發現出現訂單號重復的情況，所以分佈式鎖是可以保證分佈式環境的線程安全的
7、公平式Zookeeper分佈式鎖
上面例子是一種非公平鎖的方式，一旦監聽到鎖釋放瞭，所有線程都會去搶鎖，所以容易出現“驚群效應”：
- 巨大的服務器性能損耗
- 網絡沖擊
- 可能造成宕機
所以，需要改進分佈式鎖，改成一種公平鎖的模式
公平鎖：多個線程按照申請鎖的順序去獲取鎖，線程會在隊列裡排隊，按照順序去獲取鎖。隻有隊列第1個線程才能獲取到鎖，獲取到鎖之後，其它線程都會阻塞等待，等到持有鎖的線程釋放鎖，其它線程才會被喚醒。
非公平鎖：多個線程都會去競爭獲取鎖，獲取不到就進入隊列等待，競爭得到就直接獲取鎖；然後持有鎖的線程釋放鎖之後，所有等待的線程就都會去競爭鎖。
流程圖：
代碼改進：
package com.example.concurrent.zkSample;
import org.I0Itec.zkclient.IZkDataListener;
import org.I0Itec.zkclient.ZkClient;
import org.I0Itec.zkclient.exception.ZkNodeExistsException;
import java.util.Collections;
import java.util.List;
import java.util.concurrent.CountDownLatch;
import java.util.concurrent.TimeUnit;
import java.util.concurrent.locks.Condition;
import java.util.concurrent.locks.Lock;
public class ZKDistributeImproveLock implements Lock {
private String localPath;
private ZkClient zkClient;
private String currentPath;
private String beforePath;
ZKDistributeImproveLock(String localPath) {
super();
this.localPath = localPath;
zkClient = new ZkClient("localhost:2181");
zkClient.setZkSerializer(new MyZkSerializer());
if (!zkClient.exists(localPath)) {
try {
this.zkClient.createPersistent(localPath);
} catch (ZkNodeExistsException e) {
}
}
}
@Override
public void lock() {
while (!tryLock()) {
waitForLock();
}
}
private void waitForLock() {
CountDownLatch countDownLatch = new CountDownLatch(1);
// 註冊watcher
IZkDataListener listener = new IZkDataListener() {
@Override
public void handleDataChange(String dataPath, Object data) throws Exception {
}
@Override
public void handleDataDeleted(String dataPath) throws Exception {
// 監聽到鎖釋放，喚醒線程
countDownLatch.countDown();
}
};
zkClient.subscribeDataChanges(beforePath, listener);
// 線程等待
if (zkClient.exists(beforePath)) {
try {
countDownLatch.await();
} catch (InterruptedException e) {
e.printStackTrace();
}
}
// 取消註冊
zkClient.unsubscribeDataChanges(beforePath , listener);
}
@Override
public void unlock() {
zkClient.delete(this.currentPath);
}
@Override
public boolean tryLock() {
if (this.currentPath == null) {
currentPath = zkClient.createEphemeralSequential(localPath +"/" , "123");
}
// 獲取Znode節點下面的所有子節點
List<String> children = zkClient.getChildren(localPath);
// 列表排序
Collections.sort(children);
if (currentPath.equals(localPath + "/" + children.get(0))) { // 當前節點是第1個節點
return true;
} else {
//得到當前的索引號
int index = children.indexOf(currentPath.substring(localPath.length() + 1));
//取到前一個
beforePath = localPath + "/" + children.get(index - 1);
}
return false;
}
@Override
public boolean tryLock(long time, TimeUnit unit) throws InterruptedException {
return false;
}
@Override
public void lockInterruptibly() throws InterruptedException {
}
@Override
public Condition newCondition() {
return null;
}
}
thread name : Thread-13 , orderCode : 202112100936140
thread name : Thread-3 , orderCode : 202112100936141
thread name : Thread-14 , orderCode : 202112100936142
thread name : Thread-16 , orderCode : 202112100936143
thread name : Thread-1 , orderCode : 202112100936144
thread name : Thread-9 , orderCode : 202112100936145
thread name : Thread-4 , orderCode : 202112100936146
thread name : Thread-5 , orderCode : 202112100936147
thread name : Thread-7 , orderCode : 202112100936148
thread name : Thread-2 , orderCode : 202112100936149
thread name : Thread-17 , orderCode : 2021121009361410
thread name : Thread-15 , orderCode : 2021121009361411
thread name : Thread-0 , orderCode : 2021121009361412
thread name : Thread-10 , orderCode : 2021121009361413
thread name : Thread-18 , orderCode : 2021121009361414
thread name : Thread-19 , orderCode : 2021121009361415
thread name : Thread-8 , orderCode : 2021121009361416
thread name : Thread-12 , orderCode : 2021121009361417
thread name : Thread-11 , orderCode : 2021121009361418
thread name : Thread-6 , orderCode : 2021121009361419
8、zookeeper和Redis鎖對比？
Redis和Zookeeper都可以用來實現分佈式鎖，兩者可以進行對比：
基於Redis實現分佈式鎖
- 實現比較復雜
- 存在死鎖的可能
- 性能比較好，基於內存 ，而且保證的是高可用，redis優先保證的是AP(分佈式CAP理論)
基於Zookeeper實現分佈式鎖
- 實現相對簡單
- 可靠性高，因為zookeeper保證的是CP(分佈式CAP理論)
- 性能相對較好 並發1~2萬左右，並發太高，還是redis性能好
本博客代碼可以在GitHub找到下載鏈接
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