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基于Zookeeper怎么实现分布式锁

发表于:2025-01-24 作者:千家信息网编辑
千家信息网最后更新 2025年01月24日,这篇文章主要介绍"基于Zookeeper怎么实现分布式锁",在日常操作中,相信很多人在基于Zookeeper怎么实现分布式锁问题上存在疑惑,小编查阅了各式资料,整理出简单好用的操作方法,希望对大家解答
千家信息网最后更新 2025年01月24日基于Zookeeper怎么实现分布式锁

这篇文章主要介绍"基于Zookeeper怎么实现分布式锁",在日常操作中,相信很多人在基于Zookeeper怎么实现分布式锁问题上存在疑惑,小编查阅了各式资料,整理出简单好用的操作方法,希望对大家解答"基于Zookeeper怎么实现分布式锁"的疑惑有所帮助!接下来,请跟着小编一起来学习吧!

1、什么是Zookeeper?

Zookeeper是一个分布式的,开源的分布式应用程序协调服务,是Hadoop和hbase的重要组件。

引用官网的图例:

特征:

  1. zookeeper的数据机构是一种节点树的数据结构,zNode是基本的单位,znode是一种和unix文件系统相似的节点,可以往这个节点存储或向这个节点获取数据

  2. 通过客户端可以对znode进行数据操作,还可以注册watcher监控znode的改变

2、Zookeeper节点类型

  • 持久节点(Persistent)

  • 持久顺序节点(Persistent_Sequential)

  • 临时节点(Ephemeral)

  • 临时顺序节点(Ephemeral_Sequential)

3、Zookeeper环境搭建

下载zookeeper,官网链接,https://zookeeper.apache.org/releases.html#download,去官网找到对应的软件下载到本地

修改配置文件,${ZOOKEEPER_HOME}\conf,找到zoo_sample.cfg文件,先备份一份,另外一份修改为zoo.cfg

解压后点击zkServer.cmd运行服务端:

4、Zookeeper基本使用

在cmd窗口或者直接在idea编辑器里的terminal输入命令:

zkCli.cmd -server 127.0.0.1:2181

输入命令help查看帮助信息:

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表示顺序节点,-e表示临时节点,若不指定表示持久节点,acl是来进行权限控制的

[zk: 127.0.0.1:2181(CONNECTED) 1] create -s /zk-test 0Created /zk-test0000000000

查看

[zk: 127.0.0.1:2181(CONNECTED) 4] ls /[zk-test0000000000, zookeeper]

设置修改节点数据

set /zk-test 123

获取节点数据

get /zk-test

ps,zookeeper命令详情查看help帮助文档,也可以去官网看看文档

ok,然后java写个例子,进行watcher监听

package com.example.concurrent.zkSample;import org.I0Itec.zkclient.IZkDataListener;import org.I0Itec.zkclient.ZkClient;/** * 
 *      Zookeeper 例子 * 
* *
 * @author mazq * 修改记录 *    修改后版本:     修改人:  修改日期: 2021/12/09 16:57  修改内容: * 
*/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("监听到节点数据改变!"); } @Override public void handleDataDeleted(String dataPath) throws Exception { System.out.println("监听到节点数据被删除了"); } }); try { Thread.sleep(1000 * 60 * 2); } catch (InterruptedException e) { e.printStackTrace(); } }}

5、Zookeeper应用场景

Zookeeper有什么典型的应用场景:

  1. 注册中心(Dubbo)

  2. 命名服务

  3. Master选举

  4. 集群管理

  5. 分布式队列

  6. 分布式锁

6、Zookeeper分布式锁

Zookeeper适合用来做分布式锁,然后具体实现是利用什么原理?我们知道zookeeper是类似于unix的文件系统,文件系统我们也知道在一个文件夹下面,会有文件名称不能一致的特性的,也就是互斥的特性。同样zookeeper也有这个特性,在同个znode节点下面,子节点命名不能重复。所以利用这个特性可以来实现分布式锁

业务场景:在高并发的情况下面进行订单场景,这是一个典型的电商场景

自定义的Zookeeper序列化类:

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();        }    }}

订单编号生成器类,因为SimpleDateFormat是线程不安全的,所以还是要加上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 threadLocal = new ThreadLocal() {        @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客户端的配置:

    com.101tec    zkclient    0.10

实现一个zookeeper分布式锁,思路是获取节点,这个是多线程竞争的,能获取到锁,也就是创建节点成功,就执行业务,其它抢不到锁的线程,阻塞等待,注册watcher监听锁是否释放了,释放了,取消注册watcher,继续抢锁

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;@Slf4jpublic 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() {        // 创建countdownLatch协同        CountDownLatch countDownLatch = new CountDownLatch(1);        // 注册watcher监听        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!!!");                // 监听到锁释放了,释放线程                countDownLatch.countDown();            }        };        zkClient.subscribeDataChanges(localPath , listener);        // 线程等待        if (zkClient.exists(localPath)) {            try {                countDownLatch.await();            } catch (InterruptedException e) {                e.printStackTrace();            }        }        // 取消注册        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;    }}

订单服务api

package com.example.concurrent.zkSample;public interface OrderService {    void createOrder();}

订单服务实现类,加上zookeeper分布式锁

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));    }}

因为搭建分布式环境比较繁琐,所以这里使用juc里的并发协同工具类,CyclicBarrier模拟多线程并发的场景,模拟分布式环境的高并发场景

package com.example.concurrent.zkSample;import java.util.concurrent.BrokenBarrierException;import java.util.concurrent.CyclicBarrier;public class ConcurrentDistributeTest {    public static void main(String[] args) {        // 多线程数        int threadSize = 30;        // 创建多线程循环屏障        CyclicBarrier cyclicBarrier = new CyclicBarrier(threadSize , ()->{            System.out.println("准备完成!");        }) ;        // 模拟分布式集群的场景        for (int i = 0 ; i < threadSize ; i ++) {            new Thread(()->{                OrderService orderService = new OrderServiceInvoker();                // 所有线程都等待                try {                    cyclicBarrier.await();                } catch (InterruptedException e) {                    e.printStackTrace();                } catch (BrokenBarrierException e) {                    e.printStackTrace();                }                // 模拟并发请求                orderService.createOrder();            }).start();        }    }}

跑多几次,没有发现订单号重复的情况,分布式锁还是有点效果的

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

注释加锁的代码,再加大并发数,模拟一下

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));    }}

跑多几次,发现出现订单号重复的情况,所以分布式锁是可以保证分布式环境的线程安全的

7、公平式Zookeeper分布式锁

上面例子是一种非公平锁的方式,一旦监听到锁释放了,所有线程都会去抢锁,所以容易出现"惊群效应":

  • 巨大的服务器性能损耗

  • 网络冲击

  • 可能造成宕机

所以,需要改进分布式锁,改成一种公平锁的模式

公平锁:多个线程按照申请锁的顺序去获取锁,线程会在队列里排队,按照顺序去获取锁。只有队列第1个线程才能获取到锁,获取到锁之后,其它线程都会阻塞等待,等到持有锁的线程释放锁,其它线程才会被唤醒。

非公平锁:多个线程都会去竞争获取锁,获取不到就进入队列等待,竞争得到就直接获取锁;然后持有锁的线程释放锁之后,所有等待的线程就都会去竞争锁。

流程图:

代码改进:

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);        // 注册watcher        IZkDataListener listener = new IZkDataListener() {            @Override            public void handleDataChange(String dataPath, Object data) throws Exception {            }            @Override            public void handleDataDeleted(String dataPath) throws Exception {                // 监听到锁释放,唤醒线程                countDownLatch.countDown();            }        };        zkClient.subscribeDataChanges(beforePath, listener);        // 线程等待        if (zkClient.exists(beforePath)) {            try {                countDownLatch.await();            } catch (InterruptedException e) {                e.printStackTrace();            }        }        // 取消注册        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");        }        // 获取Znode节点下面的所有子节点        List children = zkClient.getChildren(localPath);        // 列表排序        Collections.sort(children);        if (currentPath.equals(localPath + "/" + children.get(0))) { // 当前节点是第1个节点            return true;        } else {            //得到当前的索引号            int index = children.indexOf(currentPath.substring(localPath.length() + 1));            //取到前一个            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锁对比?

Redis和Zookeeper都可以用来实现分布式锁,两者可以进行对比:

基于Redis实现分布式锁

  • 实现比较复杂

  • 存在死锁的可能

  • 性能比较好,基于内存 ,而且保证的是高可用,redis优先保证的是AP(分布式CAP理论)

基于Zookeeper实现分布式锁

  • 实现相对简单

  • 可靠性高,因为zookeeper保证的是CP(分布式CAP理论)

  • 性能相对较好 并发1~2万左右,并发太高,还是redis性能好

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