Zookeeper系列文章目录
1、zookeeper3.7.1安装与验证
2、zookeeper基本操作及应用示例(shell、java api、应用场景示例)
3、zookeeper的选举----经验证符合事实,网上很多都是错误的
4、zookeeper的java三种客户端介绍-Curator(crud、事务操作、监听、分布式计数器、分布式锁)
5、zookeeper的java -Curator(服务注册与发现)
zookeeper常用的3种java客户端
- zookeeper原生Java API
- ZkClient
- Apache curator
本文将按照顺序逐一简单介绍其使用。
一、zookeeper原生Java API
Zookeeper客户端提供了基本的操作,比如创建会话、创建节点、读取节点、更新数据、删除节点和检查节点是否存在等。但对于开发人员来说,Zookeeper提供的基本操纵还是有一些不足之处。
Zookeeper API不足之处
(1)Session超时之后没有实现重连机制,需要手动操作;
(2)Watcher注册是一次性的,每次触发之后都需要重新进行注册;
(3)不支持递归创建节点;
(4)异常处理繁琐,Zookeeper提供了很多异常,对于开发人员来说可能根本不知道该如何处理这些异常信息;
(5)只提供了简单的byte[]数组的接口,没有提供针对对象级别的序列化;
(6)创建节点时如果节点存在抛出异常,需要自行检查节点是否存在;
(7)删除节点无法实现级联删除;
基于以上原因,直接使用Zookeeper原生API的人并不多。
具体使用参见文章zookeeper的基本操作及应用示例中的介绍。
二、ZkClient
ZkClient是一个开源客户端,在Zookeeper原生API接口的基础上进行了包装,更便于开发人员使用。解决如下问题:
1)session会话超时重连
2)解决Watcher反复注册
3)简化API开发
虽然 ZkClient 对原生 API 进行了封装,但也有它自身的不足之处:
- 几乎没有参考文档;
- 异常处理简化(抛出RuntimeException);
- 重试机制比较难用;
- 没有提供各种使用场景的实现;
示例欠奉,pom.xml文件增加如下内容:
<dependency>
<groupId>com.101tecgroupId>
<artifactId>zkclientartifactId>
<version>0.10version>
dependency>
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三、Apache curator
Curator是Netflix公司开源的一套Zookeeper客户端框架,和ZkClient一样,解决了非常底层的细节开发工作,包括连接重连、反复注册Watcher和NodeExistsException异常等。目前已经成为 Apache 的顶级项目。
官网:http://curator.apache.org/index.html
Apache Curator是Apache ZooKeeper的Java / JVM客户端库,Apache ZooKeeper是一种分布式协调服务。它包括一个高级API框架和实用程序,使Apache ZooKeeper更容易和更可靠。它还包括常见用例和扩展(如服务发现和Java 8异步DSL)的配方。
其特点:
- Apache 的开源项目
- 解决Watch注册一次就会失效的问题
- 提供一套Fluent风格的 API 更加简单易用
- 提供更多解决方案并且实现简单,例如:分布式锁
- 提供常用的ZooKeeper工具类
- 编程风格更舒服
除此之外,Curator中还提供了Zookeeper各种应用场景(Recipe,如共享锁服务、Master选举机制和分布式计算器等)的抽象封装。
Curator项目组件
组件的Maven依赖
源码地址:https://github.com/apache/curator
如果只想使用Curator操作Zookeeper增删改查,则使用curator-client包及curator-framework包。zookeeper的版本是3.7.1
1、pom.xml
<dependency>
<groupId>org.apache.curatorgroupId>
<artifactId>curator-frameworkartifactId>
<version>5.3.0version>
dependency>
<dependency>
<groupId>org.apache.curatorgroupId>
<artifactId>curator-clientartifactId>
<version>5.3.0version>
dependency>
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2、定义常量类
import org.apache.curator.retry.ExponentialBackoffRetry;
/**
* @author alanchan
*
*/
public class Constant {
// 会话超时时间 10000
public final static int SESSION_TIMEOUT = 10 * 1000;
// 连接超时时间 50000
public final static int CONNECTION_TIMEOUT = 50 * 1000;
// ZooKeeper服务地址
public static String zkServerAddress = "192.168.10.41:2118,192.168.10.42:2118,192.168.10.43:2118";
// 1 重试策略:初试时间为1s 重试3次
public static ExponentialBackoffRetry retryPolicy = new ExponentialBackoffRetry(1000, 3);
}
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3、连接实例化
import org.apache.curator.RetryPolicy;
import org.apache.curator.framework.CuratorFramework;
import org.apache.curator.framework.CuratorFrameworkFactory;
import org.apache.curator.retry.ExponentialBackoffRetry;
import org.apache.curator.utils.CloseableUtils;
import org.apache.zookeeper.ZooKeeper.States;
public class App {
public static void main(String[] args) {
// 例子1
// test1();
// 例子2
// CuratorFramework zkClient = createSimple(zkServerAddress);
// zkClient.start();
// 例子3
ExponentialBackoffRetry retryPolicy = new ExponentialBackoffRetry(1000, 3);
CuratorFramework zkClient = createWithOptions(Constant.zkServerAddress, retryPolicy, 5000, 3000);
zkClient.start();
System.out.println(States.CONNECTED);
System.out.println(zkClient.getState());
}
public static void test1() {
// * @param baseSleepTimeMs initial amount of time to wait between retries 初始重试等待时间
// * @param maxRetries max number of times to retry 最大重试次数
// * @param maxSleepMs max time in ms to sleep on each retry 最大重试等待时间
ExponentialBackoffRetry retryPolicy = new ExponentialBackoffRetry(1000, 3, 5000);
CuratorFramework zkClient = CuratorFrameworkFactory.builder().connectString(Constant.zkServerAddress)
.sessionTimeoutMs(3000).connectionTimeoutMs(5000).retryPolicy(retryPolicy).build();
// 很重要 一定要调用start来创建session链接
zkClient.start();
CloseableUtils.closeQuietly(zkClient);
}
public static CuratorFramework createSimple(String connectionString) {
// these are reasonable arguments for the ExponentialBackoffRetry. The first
// retry will wait 1 second - the second will wait up to 2 seconds - the
// third will wait up to 4 seconds.
ExponentialBackoffRetry retryPolicy = new ExponentialBackoffRetry(1000, 3);
// The simplest way to get a CuratorFramework instance. This will use default
// values.
// The only required arguments are the connection string and the retry policy
return CuratorFrameworkFactory.newClient(connectionString, retryPolicy);
}
// int connectionTimeoutMs 50000
// int sessionTimeoutMs 10000
//连接时间要大于会话时间,如果设置不当,会出现 KeeperErrorCode = ConnectionLoss异常
public static CuratorFramework createWithOptions(String connectionString, RetryPolicy retryPolicy,
int connectionTimeoutMs, int sessionTimeoutMs) {
// using the CuratorFrameworkFactory.builder() gives fine grained control
// over creation options. See the CuratorFrameworkFactory.Builder javadoc
// details
return CuratorFrameworkFactory.builder().connectString(connectionString).retryPolicy(retryPolicy)
.connectionTimeoutMs(connectionTimeoutMs).sessionTimeoutMs(sessionTimeoutMs)
// etc. etc.
.build();
}
}
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4、事务操作示例
import java.util.Collection;
import org.apache.curator.framework.CuratorFramework;
import org.apache.curator.framework.api.transaction.CuratorOp;
import org.apache.curator.framework.api.transaction.CuratorTransactionResult;
import org.zookeeper_curator.App;
import org.zookeeper_curator.Constant;
/**
* @author alanchan Curator 事务管理 操作
*/
public class TransactionExamples {
public static void main(String[] args) throws Exception {
transaction(getCuratorFramework());
}
private static CuratorFramework getCuratorFramework() {
CuratorFramework client = App.createWithOptions(Constant.zkServerAddress, Constant.retryPolicy,
Constant.CONNECTION_TIMEOUT, Constant.SESSION_TIMEOUT);
client.start();
return client;
}
public static Collection<CuratorTransactionResult> transaction(CuratorFramework client) throws Exception {
// this example shows how to use ZooKeeper's transactions
CuratorOp createOp = client.transactionOp().create().forPath("/a/path", "some data".getBytes());
CuratorOp setDataOp = client.transactionOp().setData().forPath("/another/path", "other data".getBytes());
CuratorOp deleteOp = client.transactionOp().delete().forPath("/yet/another/path");
// 将上述基本操作封装程一个事务
//如果上述三个操作都没有事先创建路径的话,不会成功任何一个命令
//为了验证,先创建一个/a目录,按照不增加事务控制的话,create /a/path,应该成功,因为增加了事务控制,应该都不会成功
//如果先创建了/a目录,第一条命令create /a/path会成功,但没有提前创建/another/path,所以修改数据不会成功
Collection<CuratorTransactionResult> results = client.transaction().forOperations(createOp, setDataOp,
deleteOp);
for (CuratorTransactionResult result : results) {
System.out.println(result.getForPath() + " - " + result.getType());
}
return results;
}
}
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5、CRUD示例
import java.util.List;
import org.apache.curator.framework.CuratorFramework;
import org.apache.curator.framework.api.BackgroundCallback;
import org.apache.curator.framework.api.CuratorEvent;
import org.apache.curator.framework.api.CuratorListener;
import org.apache.curator.retry.ExponentialBackoffRetry;
import org.apache.curator.utils.CloseableUtils;
import org.apache.zookeeper.CreateMode;
import org.apache.zookeeper.Watcher;
import org.zookeeper_curator.App;
import org.zookeeper_curator.Constant;
/**
* @author alanchan
*
*/
public class CrudExamples {
// 创建连接实例
private static CuratorFramework zkClient = null;
public static void main(String[] args) throws Exception {
// int connectionTimeoutMs 50000
// int sessionTimeoutMs 10000
// 2 通过工厂创建连接
zkClient = App.createWithOptions(Constant.zkServerAddress, Constant.retryPolicy, Constant.CONNECTION_TIMEOUT,
Constant.SESSION_TIMEOUT);
zkClient.start();
// zkClient.create().forPath("/testcurator", "testing".getBytes());
// create(zkClient, "/testcurator", "testing".getBytes());
// createEphemeral(zkClient, "/testcurator", "testing".getBytes());
// createEphemeralSequential(zkClient, "/testcurator", "testing".getBytes());
// createIdempotent(zkClient, "/testcurator", "testing".getBytes());
// setData(zkClient, "/testcurator", "testing2".getBytes());
// setDataAsync(zkClient, "/testcurator", "testing32".getBytes());
BackgroundCallback callback = new BackgroundCallback() {
@Override
public void processResult(CuratorFramework client, CuratorEvent event) throws Exception {
System.out.println("监听事件触发,event内容为:" + event);
}
};
setDataAsyncWithCallback(zkClient, callback, "/testcurator", "testing".getBytes());
System.out.println(zkClient.getState());
CloseableUtils.closeQuietly(zkClient);
}
// 创建默认节点
public static void create(CuratorFramework client, String path, byte[] payload) throws Exception {
// this will create the given ZNode with the given data
client.create().forPath(path, payload);
}
// 创建临时节点
public static void createEphemeral(CuratorFramework client, String path, byte[] payload) throws Exception {
// this will create the given EPHEMERAL ZNode with the given data
client.create().withMode(CreateMode.EPHEMERAL).forPath(path, payload);
}
// 创建序列临时节点
public static String createEphemeralSequential(CuratorFramework client, String path, byte[] payload)
throws Exception {
// this will create the given EPHEMERAL-SEQUENTIAL ZNode with the given data
// using Curator protection.
return client.create().withProtection().withMode(CreateMode.EPHEMERAL_SEQUENTIAL).forPath(path, payload);
}
// 创建幂等的节点
public static void createIdempotent(CuratorFramework client, String path, byte[] payload) throws Exception {
/*
* This will create the given ZNode with the given data idempotently, meaning
* that if the initial create failed transiently, it will be retried and behave
* as if the first create never happened, even if the first create actually
* succeeded on the server but the client didn't know it.
*/
client.create().idempotent().forPath(path, payload);
}
// 针对节点,修改其数据
public static void setData(CuratorFramework client, String path, byte[] payload) throws Exception {
// set data for the given node
client.setData().forPath(path, payload);
}
// 此监听主要针对background通知和错误通知。使用此监听器之后,调用inBackground方法会异步获得监听,而对于节点的创建或修改则不会触发监听事件
public static void setDataAsync(CuratorFramework client, String path, byte[] payload) throws Exception {
// this is one method of getting event/async notifications
CuratorListener listener = new CuratorListener() {
@Override
public void eventReceived(CuratorFramework client, CuratorEvent event) throws Exception {
// examine event for details
System.out.println("监听事件触发,event内容为:" + event);
}
};
client.getCuratorListenable().addListener(listener);
// 异步获取节点数据
client.getData().inBackground().forPath(path);
// 变更节点内容
// set data for the given node asynchronously. The completion notification
// is done via the CuratorListener.
client.setData().inBackground().forPath(path, payload);
Thread.sleep(Integer.MAX_VALUE);
}
// 通过回调函数获取数据变化
public static void setDataAsyncWithCallback(CuratorFramework client, BackgroundCallback callback, String path,
byte[] payload) throws Exception {
// this is another method of getting notification of an async completion
client.setData().inBackground(callback).forPath(path, payload);
}
//
public static void setDataIdempotent(CuratorFramework client, String path, byte[] payload, int currentVersion)
throws Exception {
/*
* This will set the given ZNode with the given data idempotently, meaning that
* if the initial setData failed transiently, it will be retried and behave as
* if the first setData never happened, even if the first setData actually
* succeeded on the server but the client didn't know it. In other words, if
* currentVersion == X and payload = P, this will return success if the znode
* ends up in the state (version == X+1 && data == P). If withVersion is not
* specified, it will end up with success so long as the data == P, no matter
* the znode version.
*/
client.setData().idempotent().withVersion(currentVersion).forPath(path, payload);
client.setData().idempotent().forPath(path, payload);
}
// 删除节点
public static void delete(CuratorFramework client, String path) throws Exception {
// delete the given node
client.delete().forPath(path);
}
//
public static void guaranteedDelete(CuratorFramework client, String path) throws Exception {
// delete the given node and guarantee that it completes
/*
* Guaranteed Delete
*
* Solves this edge case: deleting a node can fail due to connection issues.
* Further, if the node was ephemeral, the node will not get auto-deleted as the
* session is still valid. This can wreak havoc with lock implementations.
*
*
* When guaranteed is set, Curator will record failed node deletions and attempt
* to delete them in the background until successful. NOTE: you will still get
* an exception when the deletion fails. But, you can be assured that as long as
* the CuratorFramework instance is open attempts will be made to delete the
* node.
*/
client.delete().guaranteed().forPath(path);
}
//
public static void deleteIdempotent(CuratorFramework client, String path, int currentVersion) throws Exception {
/*
* This will delete the given ZNode with the given data idempotently, meaning
* that if the initial delete failed transiently, it will be retried and behave
* as if the first delete never happened, even if the first delete actually
* succeeded on the server but the client didn't know it. In other words, if
* currentVersion == X, this will return success if the znode ends up deleted,
* and will retry after connection loss if the version the znode's version is
* still X. If withVersion is not specified, it will end up successful so long
* as the node is deleted eventually. Kind of like guaranteed but not in the
* background. For deletes this is equivalent to the older quietly() behavior,
* but it is also provided under idempotent() for compatibility with
* Create/SetData.
*/
client.delete().idempotent().withVersion(currentVersion).forPath(path);
client.delete().idempotent().forPath(path);
client.delete().quietly().withVersion(currentVersion).forPath(path);
client.delete().quietly().forPath(path);
}
//
public static List<String> watchedGetChildren(CuratorFramework client, String path) throws Exception {
/**
* Get children and set a watcher on the node. The watcher notification will
* come through the CuratorListener (see setDataAsync() above).
*/
return client.getChildren().watched().forPath(path);
}
//
public static List<String> watchedGetChildren(CuratorFramework client, String path, Watcher watcher)
throws Exception {
/**
* Get children and set the given watcher on the node.
*/
return client.getChildren().usingWatcher(watcher).forPath(path);
}
public static boolean isExists(CuratorFramework zkClient, String path) throws Exception {
/*
* boolean flag = false; Stat stat = zkClient.checkExists().forPath(path); if
* (stat != null) { flag = true; }
*/
return zkClient.checkExists().forPath(path) != null ? true : false;
}
}
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6、监听示例
包含原生API和CuratorCache、CuratorListener
atomic,分布式计数器(DistributedAtomicLong),能在分布式环境下实现原子自增
barriers,分布式屏障(DistributedBarrier),使用屏障来阻塞分布式环境中进程的运行,直到满足特定的条件
cache,监听机制,分为NodeCache(监听节点数据变化),PathChildrenCache(监听节点的子节点数据变化),TreeCache(既能监听自身节点数据变化也能监听子节点数据变化)
leader,leader选举
locks,分布式锁
nodes,提供持久化节点(PersistentNode)服务,即使客户端与zk服务的连接或者会话断开
queue,分布式队列(包括优先级队列DistributedPriorityQueue,延迟队列DistributedDelayQueue等)
shared,分布式计数器SharedCount
要使用该部分功能,则需要在pom.xml中增加如下部分
<dependency>
<groupId>org.apache.curatorgroupId>
<artifactId>curator-recipesartifactId>
<version>5.3.0version>
dependency>
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代码示例如下:
import java.util.function.Consumer;
import org.apache.curator.framework.CuratorFramework;
import org.apache.curator.framework.api.CuratorEvent;
import org.apache.curator.framework.api.CuratorListener;
import org.apache.curator.framework.recipes.cache.ChildData;
import org.apache.curator.framework.recipes.cache.CuratorCache;
import org.apache.curator.framework.recipes.cache.CuratorCacheListener;
import org.apache.curator.framework.recipes.cache.CuratorCacheListenerBuilder.ChangeListener;
import org.apache.curator.framework.recipes.cache.PathChildrenCache;
import org.apache.curator.utils.CloseableUtils;
import org.apache.zookeeper.WatchedEvent;
import org.apache.zookeeper.Watcher;
import org.zookeeper_curator.App;
import org.zookeeper_curator.Constant;
/**
* @author chenw
* TreeCacheListener、PathChildrenCacheListener和NodeCacheListener均已过期,替代的是CuratorCache
*/
public class ListenerDemo {
// 创建连接实例
private static CuratorFramework zkClient = null;
public static void main(String[] args) throws Exception {
zkClient = App.createWithOptions(Constant.zkServerAddress, Constant.retryPolicy, Constant.CONNECTION_TIMEOUT,
Constant.SESSION_TIMEOUT);
zkClient.start();
String path = "/testNode";
//
if (!isExists(zkClient, path)) {
zkClient.create().forPath(path, "testing".getBytes());
}
// watchEvent(zkClient, path);
// curatorListener(zkClient, path);
// curatorNodeCache(zkClient, path);
curatorNodeCacheByLambda(zkClient, path);
CloseableUtils.closeQuietly(zkClient);
}
// 使用原生zookeeper api,监控路径变化,只能监听一次变化
// 运行结果如下:
// 监听节点内容:testing
// 监听器watchedEvent:WatchedEvent state:SyncConnected type:NodeDataChanged path:/testNode
//实际数据如下:
// [zk: server1:2118(CONNECTED) 39] get /testNode
// second data
private static void watchEvent(CuratorFramework zkClient, String path) throws Exception {
byte[] data = zkClient.getData().usingWatcher(new Watcher() {
@Override
public void process(WatchedEvent watchedEvent) {
System.out.println("监听器watchedEvent:" + watchedEvent);
}
}).forPath(path);
System.out.println("监听节点内容:" + new String(data));
// 第一次变更节点数据
zkClient.setData().forPath(path, "new data".getBytes());
// 第二次变更节点数据
zkClient.setData().forPath(path, "second data".getBytes());
Thread.sleep(Integer.MAX_VALUE);
}
// CuratorListener监听,此监听主要针对background通知和错误通知。使用此监听器之后,调用inBackground方法会异步获得监听,而对于节点的创建或修改则不会触发监听事件
// 其中两次触发监听事件,第一次触发为注册监听事件时触发,第二次为getData异步处理返回结果时触发。而setData的方法并未触发监听事件。
// 测试结果是只有getData数据时有结果返回
// 运行结果如下:
// 监听事件触发,event内容为:testing CuratorEventImpl{type=GET_DATA, resultCode=0, path='/testNode', name='null', children=null, context=null, stat=55834578087,55834578087,1659404526966,1659404526966,0,0,0,0,7,0,55834578087
// , data=[116, 101, 115, 116, 105, 110, 103], watchedEvent=null, aclList=null, opResults=null}
// 实际结果
// [zk: server1:2118(CONNECTED) 56] get /testNode
// testing123
private static void curatorListener(CuratorFramework zkClient, String path) throws Exception {
zkClient.getCuratorListenable().addListener(new CuratorListener() {
// 增加监听方法
public void eventReceived(CuratorFramework client, CuratorEvent event) {
System.out.println("监听事件触发,event内容为:" + new String(event.getData()) + " " + event);
}
});
// 异步获取节点数据
zkClient.getData().inBackground().forPath(path);
// 变更节点内容
zkClient.setData().forPath(path, "testing123".getBytes());
Thread.sleep(Integer.MAX_VALUE);
}
// 该版本适合zookeeper 3.6.0 以上版本,服务器 zookeeper 服务也需要为 3.6.0 版本
// CuratorCache会试图将来自节点的数据保存在本地缓存中。
// 可以缓存指定的单个节点,也可以缓存以指定节点为根的整个子树(默认缓存方案)。可以给CuratorCache实例注册监听器,当相关节点发生更改时会接收到通知,
// 将响应更新、创建、删除等事件。
// 客户端操作结果
// [zk: server2:2118(CONNECTED) 138] delete /testNode
// [zk: server2:2118(CONNECTED) 140] ls /
// [zookeeper]
// [zk: server2:2118(CONNECTED) 141] create /testNode
// Created /testNode
// [zk: server2:2118(CONNECTED) 142] ls /
// [testNode, zookeeper]
// [zk: server2:2118(CONNECTED) 143] set /testNode "testing1234"
// [zk: server2:2118(CONNECTED) 144] get /testNode
// testing1234
// 程序运行结果
// create:ChildData{path='/testNode', stat=55834578106,55834578106,1659419377672,1659419377672,0,0,0,0,7,0,55834578106, data=[116, 101, 115, 116, 105, 110, 103]}
// 初始化...
// delete:ChildData{path='/testNode', stat=55834578106,55834578106,1659419377672,1659419377672,0,0,0,0,7,0,55834578106, data=[116, 101, 115, 116, 105, 110, 103]}
// create:ChildData{path='/testNode', stat=55834578109,55834578109,1659419426777,1659419426777,0,0,0,0,0,0,55834578109, data=null}
// ChildData{path='/testNode', stat=55834578109,55834578109,1659419426777,1659419426777,0,0,0,0,0,0,55834578109 , data=null} change to ChildData{path='/testNode', stat=55834578109,55834578110,1659419426777,1659419448002,1,0,0,0,11,0,55834578109, data=[116, 101, 115, 116, 105, 110, 103, 49, 50, 51, 52]}
private static void curatorNodeCache(CuratorFramework zkClient, String path) throws Exception {
CuratorCache cache = CuratorCache.build(zkClient, path);
CuratorCacheListener listener = CuratorCacheListener.builder().forCreates(new Consumer<ChildData>() {// 创建监控
@Override
public void accept(ChildData t) {
System.out.println(" create:" + t);
}
}).forChanges(new ChangeListener() {// 改变监控
@Override
public void event(ChildData oldNode, ChildData node) {
System.out.println(oldNode + " change to " + node);
}
}).forDeletes(new Consumer<ChildData>() {// 删除监控
@Override
public void accept(ChildData t) {
System.out.println(" delete:" + t);
}
}).forInitialized(new Runnable() {// 初始化监控
@Override
public void run() {
System.out.println(" 初始化...");
}
}).build();
// register the listener
cache.listenable().addListener(listener);
// the cache must be started
cache.start();
Thread.sleep(Integer.MAX_VALUE);
}
// 该方法与curatorNodeCache方法功能完全一致,不同的是写法
private static void curatorNodeCacheByLambda(CuratorFramework zkClient, String path) throws Exception {
CuratorCache cache = CuratorCache.build(zkClient, path);
CuratorCacheListener listener = CuratorCacheListener.builder()
.forCreates(node -> System.out.println(" create:" + node))
.forChanges((oldNode, node) -> System.out.println(oldNode + " change to " + node))
.forDeletes(node -> System.out.println(" delete:" + node))
.forInitialized(() -> System.out.println(" 初始化...")).build();
// register the listener
cache.listenable().addListener(listener);
// the cache must be started
cache.start();
Thread.sleep(Integer.MAX_VALUE);
}
private static boolean isExists(CuratorFramework zkClient, String path) throws Exception {
/*
* boolean flag = false; Stat stat = zkClient.checkExists().forPath(path); if
* (stat != null) { flag = true; }
*/
return zkClient.checkExists().forPath(path) != null ? true : false;
}
}
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7、计数器示例
1)、单机原子自增性实现
原子性就是指该操作是不可再分的,要么全部执行,要么全部不执行。
Java中保证原子性操作的有:
- Synchronized和Lock,加锁使得同一时刻只有一个线程能访问共享变量,操作自然是原子的
- java.util.concurrent.atomic下的原子操作类,如AtomicInteger,AtomicReference,基于Cas算法实现了类似乐观锁版本更新控制的原子操作
这两种方法,下面会分别介绍如何使用来解决i++原子性问题
volatile关键字不能保证原子性,保证原子性还得通过synchronized,Lock和java.util.concurrent.atomic下的原子操作类。
1、Synchronized示例
static int count = 0;
static CountDownLatch countDownLatch = new CountDownLatch(10);
static Object lock = new Object();
public static void main(String[] args) {
//创建10个线程 每个线程内部自增100000次
for (int i = 0; i < 10; i++) {
new Thread(() -> {
for (int j = 0; j < 100000; j++) {
//锁住lock对象,lock对象所有线程共享
synchronized (lock) {
count++;
}
}
countDownLatch.countDown();
}).start();
}
try {
countDownLatch.await();
} catch (InterruptedException e) {
e.printStackTrace();
}
System.out.println(count);
}
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2、Lock示例
static int count = 0;
static CountDownLatch countDownLatch = new CountDownLatch(10);
static ReentrantLock lock = new ReentrantLock();
public static void main(String[] args) {
//创建10个线程 每个线程内部自增100000次
for (int i = 0; i < 10; i++) {
new Thread(() -> {
for (int j = 0; j < 100000; j++) {
lock.lock();
count++;
lock.unlock();
}
countDownLatch.countDown();
}).start();
}
try {
countDownLatch.await();
} catch (InterruptedException e) {
e.printStackTrace();
}
System.out.println(count);
}
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ReentrantLock相比Synchronized,主要区别有以下几点
3、AtomicInteger示例
将count变量设为AtomicInteger,使用incrementAndGet方法也能实现,变量原子自增
static CountDownLatch countDownLatch = new CountDownLatch(10);
static AtomicInteger count = new AtomicInteger(0);
public static void main(String[] args) {
//创建10个线程 每个线程内部自增100000次
for (int i = 0; i < 10; i++) {
new Thread(() -> {
for (int j = 0; j < 100000; j++) {
count.incrementAndGet();
}
countDownLatch.countDown();
}).start();
}
try {
countDownLatch.await();
} catch (InterruptedException e) {
e.printStackTrace();
}
System.out.println(count.get());
}
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2)、分布式线程安全原子自增实现
Curator基于Zookeeper实现的分布式计数器,Curator recipes包下实现了DistributedAtomicInteger,DistributedAtomicLong等分布式原子自增计数器。
import java.util.concurrent.CountDownLatch;
import org.apache.curator.framework.CuratorFramework;
import org.apache.curator.framework.recipes.atomic.AtomicValue;
import org.apache.curator.framework.recipes.atomic.DistributedAtomicInteger;
import org.apache.curator.retry.ExponentialBackoffRetry;
import org.apache.curator.utils.CloseableUtils;
import org.zookeeper_curator.App;
import org.zookeeper_curator.Constant;
/**
* @author alanchan
*
*/
public class DistributedAtomicIntegerDemo {
static CountDownLatch countDownLatch = new CountDownLatch(10);
static int count = 0;
// 创建连接实例
private static CuratorFramework zkClient = null;
/**
* @param args
* @throws Exception
*/
public static void main(String[] args) throws Exception {
zkClient = App.createWithOptions(Constant.zkServerAddress, Constant.retryPolicy, Constant.CONNECTION_TIMEOUT,
Constant.SESSION_TIMEOUT);
zkClient.start();
String path = "/countdown";
// testIDoublePlus();
distributedAtomicInteger(zkClient, path);
CloseableUtils.closeQuietly(zkClient);
}
private static void distributedAtomicInteger(CuratorFramework zkClient, String path) throws Exception {
DistributedAtomicInteger distributedAtomicInteger = new DistributedAtomicInteger(zkClient, path,
new ExponentialBackoffRetry(1000, 3));
// 1.start
// start作用是启动一个新线程。
// 当用start()开始一个线程后,线程就进入就绪状态,使线程所代表的虚拟处理机处于可运行状态,这意味着它可以由JVM调度并执行。但是这并不意味着线程就会立即运行。只有当cpu分配时间片时,这个线程获得时间片时,才开始执行run()方法。start()不能被重复调用,它调用run()方法.run()方法是你必须重写的
// 2.run
// run()就和普通的成员方法一样,可以被重复调用。
// 如果直接调用run方法,并不会启动新线程!程序中依然只有主线程这一个线程,其程序执行路径还是只有一条,还是要顺序执行,还是要等待run方法体执行完毕后才可继续执行下面的代码,这样就没有达到多线程的目的。
// 调用start方法方可启动线程,而run方法只是thread的一个普通方法调用,还是在主线程里执行。
//下面的例子运行结果是10×100,具体看start和run的解释
// for (int i = 0; i < 10; i++) {
//
// Runnable thread = new Runnable() {
// @Override
// public void run() {
// for (int j = 0; j < 100; j++) {
// try {
// AtomicValue result = distributedAtomicInteger.increment();
// } catch (Exception e) {
// e.printStackTrace();
// }
// }
// countDownLatch.countDown();
// }
// };
// thread.run();
// }
for (int i = 0; i < 10; i++) {
new Thread(() -> {
for (int j = 0; j < 100; j++) {
try {
// 调用add方法自增
// Add delta to the current value and return the new value information. Remember
// to always check {@link AtomicValue#succeeded()}.
AtomicValue<Integer> result = distributedAtomicInteger.add(1);
// if (result.succeeded()) {
// System.out.println("current value: " + distributedAtomicInteger.get().postValue());
// }
} catch (Exception e) {
e.printStackTrace();
}
}
countDownLatch.countDown();
}).start();
}
try {
countDownLatch.await();
} catch (InterruptedException e) {
e.printStackTrace();
}
// 查看结果
System.out.println("多线程自增结果:" + distributedAtomicInteger.get().postValue());
}
/**
* 测试i++ 是否线程安全
* CountDownLatch调用await()方法的线程将一直阻塞等待,直到这个CountDownLatch对象的计数值减到0(每次调用countDown方法计数器减一)为止。
* 例子里每个子线程自增100000次后调用countDown()方法将计数器减一,初始化数值10,10个线程全部跑完自增后,主线程await方法不再阻塞,输出count值
*/
private static void testIDoublePlus() {
// 创建10个线程 每个线程内部自增100000次
for (int i = 0; i < 10; i++) {
new Thread(() -> {
for (int j = 0; j < 100000; j++) {
count++;
}
countDownLatch.countDown();
}).start();
}
try {
countDownLatch.await();
} catch (InterruptedException e) {
e.printStackTrace();
}
System.out.println(count);
}
}
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8、分布式锁示例
1)、实现原理
基于zookeeper瞬时有序节点实现的分布式锁。大致思想即为:每个客户端对某个功能加锁时,在zookeeper上的与该功能对应的指定节点的目录下,生成一个唯一的瞬时有序节点。判断是否获取锁的方式很简单,只需要判断有序节点中序号最小的一个。当释放锁的时候,只需将这个瞬时节点删除即可。同时,其可以避免服务宕机导致的锁无法释放,而产生的死锁问题。
2)、优点
锁安全性高,zk可持久化
3)、缺点
性能开销比较高。因为其需要动态产生、销毁瞬时节点来实现锁功能。
4)、实现
可以直接采用zookeeper第三方库curator即可方便地实现分布式锁。
1、使用原生API存在的问题
- 会话连接是异步的,需要自己去处理。比如使用 CountDownLatch Watch
- 需要重复注册,不然就不能生效
- 开发的复杂性比较高
- 不支持多节点删除和创建。需要自己去递归
2、Curator主要实现了下面四种锁
- InterProcessMutex:分布式可重入排它锁
- InterProcessSemaphoreMutex:分布式排它锁
- InterProcessReadWriteLock:分布式读写锁
- InterProcessMultiLock:将多个锁作为单个实体管理的容器
import java.util.concurrent.ExecutorService;
import java.util.concurrent.Executors;
import org.apache.curator.framework.CuratorFramework;
import org.apache.curator.framework.recipes.locks.InterProcessLock;
import org.apache.curator.framework.recipes.locks.InterProcessMutex;
import org.apache.curator.framework.recipes.locks.InterProcessReadWriteLock;
import org.apache.curator.framework.recipes.locks.InterProcessSemaphoreMutex;
import org.zookeeper_curator.App;
import org.zookeeper_curator.Constant;
/**
* @author alanchan 测试分布式锁
*/
public class DistributedLockDemo {
private static Integer testData = 0;
private static final ExecutorService EXECUTOR_SERVICE = Executors.newCachedThreadPool();
public static void main(String[] args) throws Exception {
String path = "/locks";
#InterProcessMutex:分布式可重入排它锁
// testInterProcessMutex(path);
#InterProcessSemaphoreMutex:分布式排它锁
// testInterProcessSemaphoreMutex(path); //该方法不能获得期望的结果
#InterProcessReadWriteLock:分布式读写锁
// pool-1-thread-4获取读锁
// pool-1-thread-4释放读锁
// pool-1-thread-2获取读锁
// pool-1-thread-2释放读锁
// pool-1-thread-5获取写锁
// pool-1-thread-5释放写锁
// pool-1-thread-3获取读锁
// pool-1-thread-1获取读锁
// pool-1-thread-3释放读锁
// pool-1-thread-1释放读锁
// 验证读写锁
for (int i = 0; i < 5; i++) {
EXECUTOR_SERVICE.execute(new InterProcessReadWriteLockRunnable());
}
// pool-1-thread-5获取写锁
// pool-1-thread-5获取读锁,锁降级成功
// pool-1-thread-5释放读锁
// pool-1-thread-5释放写锁
// pool-1-thread-4获取写锁
// pool-1-thread-4获取读锁,锁降级成功
// pool-1-thread-4释放读锁
// pool-1-thread-4释放写锁
// pool-1-thread-2获取写锁
// pool-1-thread-2获取读锁,锁降级成功
// pool-1-thread-2释放读锁
// pool-1-thread-2释放写锁
// pool-1-thread-1获取写锁
// pool-1-thread-1获取读锁,锁降级成功
// pool-1-thread-1释放读锁
// pool-1-thread-1释放写锁
// pool-1-thread-3获取写锁
// pool-1-thread-3获取读锁,锁降级成功
// pool-1-thread-3释放读锁
// pool-1-thread-3释放写锁
// 验证锁降级
// for (int i = 0; i < 5; i++) {
// EXECUTOR_SERVICE.execute(new InterProcessReadWriteLockRunnable1());
// }
}
// 写入数据
private static void write(String path) throws Exception {
// 创建读写锁对象, Curator 以公平锁的方式进行实现
InterProcessReadWriteLock lock = new InterProcessReadWriteLock(getCuratorFramework(), path);
// 获取写锁(使用 InterProcessMutex 实现, 所以是可以重入的)
InterProcessLock writeLock = lock.writeLock();
writeLock.acquire();
try {
Thread.sleep(10);
testData++;
System.out.println("写入数据,测试:" + testData);
} finally {
writeLock.release();
}
}
// 读取数据
private void read(CuratorFramework zkClient, String path) throws Exception {
// 创建读写锁对象, Curator 以公平锁的方式进行实现
InterProcessReadWriteLock lock = new InterProcessReadWriteLock(zkClient, path);
// 获取读锁(使用 InterProcessMutex 实现, 所以是可以重入的)
InterProcessLock readLock = lock.readLock();
readLock.acquire();
try {
Thread.sleep(10);
System.out.println("读取数据,测试:" + testData);
} finally {
readLock.release();
}
}
// Result:
// 线程2 获取到锁
// 线程2 再次获取到锁
// 线程2 释放锁
// 线程2 再次释放锁
// 线程1 获取到锁
// 线程1 再次获取到锁
// 线程1 释放锁
// 线程1 再次释放锁
// 共享可重入锁
public static void testInterProcessMutex(String path) {
// 创建分布式锁1
InterProcessMutex lock1 = new InterProcessMutex(getCuratorFramework(), path);
// 创建分布式锁2
InterProcessMutex lock2 = new InterProcessMutex(getCuratorFramework(), path);
new Thread(new Runnable() {
@Override
public void run() {
try {
lock1.acquire();
System.out.println("线程1 获取到锁");
lock1.acquire();
System.out.println("线程1 再次获取到锁");
Thread.sleep(5 * 1000);
lock1.release();
System.out.println("线程1 释放锁");
Thread.sleep(5 * 1000);
lock1.release();
System.out.println("线程1 再次释放锁");
} catch (Exception e) {
e.printStackTrace();
}
}
}).start();
new Thread(new Runnable() {
@Override
public void run() {
try {
lock2.acquire();
System.out.println("线程2 获取到锁");
lock2.acquire();
System.out.println("线程2 再次获取到锁");
Thread.sleep(5 * 1000);
lock2.release();
System.out.println("线程2 释放锁");
Thread.sleep(5 * 1000);
lock2.release();
System.out.println("线程2 再次释放锁");
} catch (Exception e) {
e.printStackTrace();
}
}
}).start();
}
// result:
// 线程2 获取到锁
// 然后处于阻塞状态,其他线程不能获取到锁,也不能释放锁
// 共享不可重入锁
public static void testInterProcessSemaphoreMutex(String path) {
// 创建分布式锁1
InterProcessLock lock1 = new InterProcessSemaphoreMutex(getCuratorFramework(), path);
// 创建分布式锁2
InterProcessLock lock2 = new InterProcessSemaphoreMutex(getCuratorFramework(), path);
new Thread(new Runnable() {
@Override
public void run() {
try {
lock1.acquire();
System.out.println("线程1 获取到锁");
lock1.acquire();
System.out.println("线程1 再次获取到锁");
Thread.sleep(5 * 1000);
lock1.release();
System.out.println("线程1 释放锁");
Thread.sleep(5 * 1000);
lock1.release();
System.out.println("线程1 再次释放锁");
} catch (Exception e) {
e.printStackTrace();
}
}
}).start();
new Thread(new Runnable() {
@Override
public void run() {
try {
lock2.acquire();
System.out.println("线程2 获取到锁");
lock2.acquire();
System.out.println("线程2 再次获取到锁");
Thread.sleep(5 * 1000);
lock2.release();
System.out.println("线程2 释放锁");
Thread.sleep(5 * 1000);
lock2.release();
System.out.println("线程2 再次释放锁");
} catch (Exception e) {
e.printStackTrace();
}
}
}).start();
}
// 共享不可重入锁
public InterProcessLock getInterProcessSemaphoreMutex(CuratorFramework zkClient, String path) {
InterProcessLock ipsmLock = new InterProcessSemaphoreMutex(zkClient, path);
return ipsmLock;
}
// 共享可重入锁
public InterProcessLock getInterProcessMutex(CuratorFramework zkClient, String path) {
InterProcessLock ipLock = new InterProcessMutex(zkClient, path);
return ipLock;
}
// 共享可重入读锁
public InterProcessLock getInterProcessReadLock(CuratorFramework zkClient, String path) {
InterProcessReadWriteLock ipReadWriteLock = new InterProcessReadWriteLock(zkClient, path);
InterProcessLock readLock = ipReadWriteLock.readLock();
return readLock;
}
// 共享可重入写锁
public InterProcessLock getInterProcessWriteLock(CuratorFramework zkClient, String path) {
InterProcessReadWriteLock ipReadWriteLock = new InterProcessReadWriteLock(zkClient, path);
InterProcessLock writeLock = ipReadWriteLock.writeLock();
return writeLock;
}
private static CuratorFramework getCuratorFramework() {
CuratorFramework client = App.createWithOptions(Constant.zkServerAddress, Constant.retryPolicy,
Constant.CONNECTION_TIMEOUT, Constant.SESSION_TIMEOUT);
// 启动客户端
client.start();
System.out.println("zookeeper 启动成功");
return client;
}
}
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读写锁
import java.nio.charset.StandardCharsets;
import java.util.Random;
import org.apache.curator.framework.CuratorFramework;
import org.apache.curator.framework.recipes.locks.InterProcessReadWriteLock;
import org.zookeeper_curator.App;
import org.zookeeper_curator.Constant;
/**
* @author alanchan
* 测试读写锁
*/
public class InterProcessReadWriteLockRunnable implements Runnable {
@Override
public void run() {
CuratorFramework zkClient = getCuratorFramework();
String path = "/locks";
// 创建InterProcessReadWriteLock实例,用于提供分布式锁的功能
InterProcessReadWriteLock readWriteLock = new InterProcessReadWriteLock(zkClient, path,
"分布式读写锁".getBytes(StandardCharsets.UTF_8));
// 根据随机数来决定获取写锁还是读锁
Random random = new Random();
try {
if (random.nextInt(10000) > 5000) {
// 获取写锁
readWriteLock.writeLock().acquire();
System.out.println(Thread.currentThread().getName() + "获取写锁");
Thread.sleep(2);
System.out.println(Thread.currentThread().getName() + "释放写锁");
// 释放写锁
readWriteLock.writeLock().release();
} else {
// 获取读锁
readWriteLock.readLock().acquire();
System.out.println(Thread.currentThread().getName() + "获取读锁");
Thread.sleep(2);
System.out.println(Thread.currentThread().getName() + "释放读锁");
// 释放读锁
readWriteLock.readLock().release();
}
} catch (Exception e) {
e.printStackTrace();
}
}
private static CuratorFramework getCuratorFramework() {
CuratorFramework client = App.createWithOptions(Constant.zkServerAddress, Constant.retryPolicy,
Constant.CONNECTION_TIMEOUT, Constant.SESSION_TIMEOUT);
// 启动客户端
client.start();
System.out.println("zookeeper 启动成功");
return client;
}
}
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锁降级
import java.nio.charset.StandardCharsets;
import org.apache.curator.framework.CuratorFramework;
import org.apache.curator.framework.recipes.locks.InterProcessReadWriteLock;
import org.zookeeper_curator.App;
import org.zookeeper_curator.Constant;
/**
* @author alanchan
* 锁降级
*/
public class InterProcessReadWriteLockRunnable1 implements Runnable {
private static CuratorFramework getCuratorFramework() {
CuratorFramework client = App.createWithOptions(Constant.zkServerAddress, Constant.retryPolicy,
Constant.CONNECTION_TIMEOUT, Constant.SESSION_TIMEOUT);
// 启动客户端
client.start();
System.out.println("zookeeper 启动成功");
return client;
}
@Override
public void run() {
CuratorFramework zkClient = getCuratorFramework();
String path = "/locks";
// 创建InterProcessReadWriteLock实例,用于提供分布式锁的功能
InterProcessReadWriteLock readWriteLock = new InterProcessReadWriteLock(zkClient, path,
"分布式读写锁".getBytes(StandardCharsets.UTF_8));
try {
// 获取写锁
readWriteLock.writeLock().acquire();
System.out.println(Thread.currentThread().getName() + "获取写锁");
Thread.sleep(2000);
// 锁降级
readWriteLock.readLock().acquire();
System.out.println(Thread.currentThread().getName() + "获取读锁,锁降级成功");
Thread.sleep(2000);
// 释放读锁
System.out.println(Thread.currentThread().getName() + "释放读锁");
readWriteLock.readLock().release();
// 释放写锁
System.out.println(Thread.currentThread().getName() + "释放写锁");
readWriteLock.writeLock().release();
} catch (Exception e) {
e.printStackTrace();
}
}
}
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以上简单的介绍了一下zookeeper的java三种客户端介绍-Curator(crud、事务操作、监听、分布式计数器、分布式锁)。具体深入的使用可能需要进一步的了解。
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