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+you may not use this file except in compliance with the License. +You may obtain a copy of the License at + +http://www.apache.org/licenses/LICENSE-2.0 + +Unless required by applicable law or agreed to in writing, software +distributed under the License is distributed on an "AS IS" BASIS, +WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +See the License for the specific language governing permissions and +limitations under the License. +//--> +<h1>Programming with ZooKeeper - A basic tutorial</h1> +<ul> +<li><a href="#ch_Introduction">Introduction</a></li> +<li><a href="#sc_barriers">Barriers</a></li> +<li><a href="#sc_producerConsumerQueues">Producer-Consumer Queues</a></li> +<li><a href="#Complete+example">Complete example</a> +<ul> +<li><a href="#Queue+test">Queue test</a></li> +<li><a href="#Barrier+test">Barrier test</a></li> +<li><a href="#sc_sourceListing">Source Listing</a></li> +</ul> +</li> +</ul> +<p><a name="ch_Introduction"></a></p> +<h2>Introduction</h2> +<p>In this tutorial, we show simple implementations of barriers and producer-consumer queues using ZooKeeper. We call the respective classes Barrier and Queue. These examples assume that you have at least one ZooKeeper server running.</p> +<p>Both primitives use the following common excerpt of code:</p> +<pre><code>static ZooKeeper zk = null; +static Integer mutex; + +String root; + +SyncPrimitive(String address) { + if(zk == null){ + try { + System.out.println("Starting ZK:"); + zk = new ZooKeeper(address, 3000, this); + mutex = new Integer(-1); + System.out.println("Finished starting ZK: " + zk); + } catch (IOException e) { + System.out.println(e.toString()); + zk = null; + } + } +} + +synchronized public void process(WatchedEvent event) { + synchronized (mutex) { + mutex.notify(); + } +} +</code></pre> +<p>Both classes extend SyncPrimitive. In this way, we execute steps that are common to all primitives in the constructor of SyncPrimitive. To keep the examples simple, we create a ZooKeeper object the first time we instantiate either a barrier object or a queue object, and we declare a static variable that is a reference to this object. The subsequent instances of Barrier and Queue check whether a ZooKeeper object exists. Alternatively, we could have the application creating a ZooKeeper object and passing it to the constructor of Barrier and Queue.</p> +<p>We use the process() method to process notifications triggered due to watches. In the following discussion, we present code that sets watches. A watch is internal structure that enables ZooKeeper to notify a client of a change to a node. For example, if a client is waiting for other clients to leave a barrier, then it can set a watch and wait for modifications to a particular node, which can indicate that it is the end of the wait. This point becomes clear once we go over the examples.</p> +<p><a name="sc_barriers"></a></p> +<h2>Barriers</h2> +<p>A barrier is a primitive that enables a group of processes to synchronize the beginning and the end of a computation. The general idea of this implementation is to have a barrier node that serves the purpose of being a parent for individual process nodes. Suppose that we call the barrier node "/b1". Each process "p" then creates a node "/b1/p". Once enough processes have created their corresponding nodes, joined processes can start the computation.</p> +<p>In this example, each process instantiates a Barrier object, and its constructor takes as parameters:</p> +<ul> +<li>the address of a ZooKeeper server (e.g., "zoo1.foo.com:2181")</li> +<li>the path of the barrier node on ZooKeeper (e.g., "/b1")</li> +<li>the size of the group of processes</li> +</ul> +<p>The constructor of Barrier passes the address of the Zookeeper server to the constructor of the parent class. The parent class creates a ZooKeeper instance if one does not exist. The constructor of Barrier then creates a barrier node on ZooKeeper, which is the parent node of all process nodes, and we call root (<strong>Note:</strong> This is not the ZooKeeper root "/").</p> +<pre><code>/** + * Barrier constructor + * + * @param address + * @param root + * @param size + */ +Barrier(String address, String root, int size) { + super(address); + this.root = root; + this.size = size; + // Create barrier node + if (zk != null) { + try { + Stat s = zk.exists(root, false); + if (s == null) { + zk.create(root, new byte[0], Ids.OPEN_ACL_UNSAFE, + CreateMode.PERSISTENT); + } + } catch (KeeperException e) { + System.out + .println("Keeper exception when instantiating queue: " + + e.toString()); + } catch (InterruptedException e) { + System.out.println("Interrupted exception"); + } + } + + // My node name + try { + name = new String(InetAddress.getLocalHost().getCanonicalHostName().toString()); + } catch (UnknownHostException e) { + System.out.println(e.toString()); + } +} +</code></pre> +<p>To enter the barrier, a process calls enter(). The process creates a node under the root to represent it, using its host name to form the node name. It then wait until enough processes have entered the barrier. A process does it by checking the number of children the root node has with "getChildren()", and waiting for notifications in the case it does not have enough. To receive a notification when there is a change to the root node, a process has to set a watch, and does it through the call to "getChildren()". In the code, we have that "getChildren()" has two parameters. The first one states the node to read from, and the second is a boolean flag that enables the process to set a watch. In the code the flag is true.</p> +<pre><code>/** + * Join barrier + * + * @return + * @throws KeeperException + * @throws InterruptedException + */ + +boolean enter() throws KeeperException, InterruptedException{ + zk.create(root + "/" + name, new byte[0], Ids.OPEN_ACL_UNSAFE, + CreateMode.EPHEMERAL); + while (true) { + synchronized (mutex) { + List<String> list = zk.getChildren(root, true); + + if (list.size() < size) { + mutex.wait(); + } else { + return true; + } + } + } +} +</code></pre> +<p>Note that enter() throws both KeeperException and InterruptedException, so it is the responsibility of the application to catch and handle such exceptions.</p> +<p>Once the computation is finished, a process calls leave() to leave the barrier. First it deletes its corresponding node, and then it gets the children of the root node. If there is at least one child, then it waits for a notification (obs: note that the second parameter of the call to getChildren() is true, meaning that ZooKeeper has to set a watch on the root node). Upon reception of a notification, it checks once more whether the root node has any children.</p> +<pre><code>/** + * Wait until all reach barrier + * + * @return + * @throws KeeperException + * @throws InterruptedException + */ + +boolean leave() throws KeeperException, InterruptedException { + zk.delete(root + "/" + name, 0); + while (true) { + synchronized (mutex) { + List<String> list = zk.getChildren(root, true); + if (list.size() > 0) { + mutex.wait(); + } else { + return true; + } + } + } + } +</code></pre> +<p><a name="sc_producerConsumerQueues"></a></p> +<h2>Producer-Consumer Queues</h2> +<p>A producer-consumer queue is a distributed data structure that groups of processes use to generate and consume items. Producer processes create new elements and add them to the queue. Consumer processes remove elements from the list, and process them. In this implementation, the elements are simple integers. The queue is represented by a root node, and to add an element to the queue, a producer process creates a new node, a child of the root node.</p> +<p>The following excerpt of code corresponds to the constructor of the object. As with Barrier objects, it first calls the constructor of the parent class, SyncPrimitive, that creates a ZooKeeper object if one doesn't exist. It then verifies if the root node of the queue exists, and creates if it doesn't.</p> +<pre><code>/** + * Constructor of producer-consumer queue + * + * @param address + * @param name + */ +Queue(String address, String name) { + super(address); + this.root = name; + // Create ZK node name + if (zk != null) { + try { + Stat s = zk.exists(root, false); + if (s == null) { + zk.create(root, new byte[0], Ids.OPEN_ACL_UNSAFE, + CreateMode.PERSISTENT); + } + } catch (KeeperException e) { + System.out + .println("Keeper exception when instantiating queue: " + + e.toString()); + } catch (InterruptedException e) { + System.out.println("Interrupted exception"); + } + } +} +</code></pre> +<p>A producer process calls "produce()" to add an element to the queue, and passes an integer as an argument. To add an element to the queue, the method creates a new node using "create()", and uses the SEQUENCE flag to instruct ZooKeeper to append the value of the sequencer counter associated to the root node. In this way, we impose a total order on the elements of the queue, thus guaranteeing that the oldest element of the queue is the next one consumed.</p> +<pre><code>/** + * Add element to the queue. + * + * @param i + * @return + */ + +boolean produce(int i) throws KeeperException, InterruptedException{ + ByteBuffer b = ByteBuffer.allocate(4); + byte[] value; + + // Add child with value i + b.putInt(i); + value = b.array(); + zk.create(root + "/element", value, Ids.OPEN_ACL_UNSAFE, + CreateMode.PERSISTENT_SEQUENTIAL); + + return true; +} +</code></pre> +<p>To consume an element, a consumer process obtains the children of the root node, reads the node with smallest counter value, and returns the element. Note that if there is a conflict, then one of the two contending processes won't be able to delete the node and the delete operation will throw an exception.</p> +<p>A call to getChildren() returns the list of children in lexicographic order. As lexicographic order does not necessarily follow the numerical order of the counter values, we need to decide which element is the smallest. To decide which one has the smallest counter value, we traverse the list, and remove the prefix "element" from each one.</p> +<pre><code>/** + * Remove first element from the queue. + * + * @return + * @throws KeeperException + * @throws InterruptedException + */ +int consume() throws KeeperException, InterruptedException{ + int retvalue = -1; + Stat stat = null; + + // Get the first element available + while (true) { + synchronized (mutex) { + List<String> list = zk.getChildren(root, true); + if (list.size() == 0) { + System.out.println("Going to wait"); + mutex.wait(); + } else { + Integer min = new Integer(list.get(0).substring(7)); + for(String s : list){ + Integer tempValue = new Integer(s.substring(7)); + //System.out.println("Temporary value: " + tempValue); + if(tempValue < min) min = tempValue; + } + System.out.println("Temporary value: " + root + "/element" + min); + byte[] b = zk.getData(root + "/element" + min, + false, stat); + zk.delete(root + "/element" + min, 0); + ByteBuffer buffer = ByteBuffer.wrap(b); + retvalue = buffer.getInt(); + + return retvalue; + } + } + } + } +} +</code></pre> +<p><a name="Complete+example"></a></p> +<h2>Complete example</h2> +<p>In the following section you can find a complete command line application to demonstrate the above mentioned recipes. Use the following command to run it.</p> +<pre><code>ZOOBINDIR="[path_to_distro]/bin" +. "$ZOOBINDIR"/zkEnv.sh +java SyncPrimitive [Test Type] [ZK server] [No of elements] [Client type] +</code></pre> +<p><a name="Queue+test"></a></p> +<h3>Queue test</h3> +<p>Start a producer to create 100 elements</p> +<pre><code>java SyncPrimitive qTest localhost 100 p +</code></pre> +<p>Start a consumer to consume 100 elements</p> +<pre><code>java SyncPrimitive qTest localhost 100 c +</code></pre> +<p><a name="Barrier+test"></a></p> +<h3>Barrier test</h3> +<p>Start a barrier with 2 participants (start as many times as many participants you'd like to enter)</p> +<pre><code>java SyncPrimitive bTest localhost 2 +</code></pre> +<p><a name="sc_sourceListing"></a></p> +<h3>Source Listing</h3> +<h4>SyncPrimitive.Java</h4> +<pre><code>import java.io.IOException; +import java.net.InetAddress; +import java.net.UnknownHostException; +import java.nio.ByteBuffer; +import java.util.List; +import java.util.Random; + +import org.apache.zookeeper.CreateMode; +import org.apache.zookeeper.KeeperException; +import org.apache.zookeeper.WatchedEvent; +import org.apache.zookeeper.Watcher; +import org.apache.zookeeper.ZooKeeper; +import org.apache.zookeeper.ZooDefs.Ids; +import org.apache.zookeeper.data.Stat; + +public class SyncPrimitive implements Watcher { + + static ZooKeeper zk = null; + static Integer mutex; + String root; + + SyncPrimitive(String address) { + if(zk == null){ + try { + System.out.println("Starting ZK:"); + zk = new ZooKeeper(address, 3000, this); + mutex = new Integer(-1); + System.out.println("Finished starting ZK: " + zk); + } catch (IOException e) { + System.out.println(e.toString()); + zk = null; + } + } + //else mutex = new Integer(-1); + } + + synchronized public void process(WatchedEvent event) { + synchronized (mutex) { + //System.out.println("Process: " + event.getType()); + mutex.notify(); + } + } + + /** + * Barrier + */ + static public class Barrier extends SyncPrimitive { + int size; + String name; + + /** + * Barrier constructor + * + * @param address + * @param root + * @param size + */ + Barrier(String address, String root, int size) { + super(address); + this.root = root; + this.size = size; + + // Create barrier node + if (zk != null) { + try { + Stat s = zk.exists(root, false); + if (s == null) { + zk.create(root, new byte[0], Ids.OPEN_ACL_UNSAFE, + CreateMode.PERSISTENT); + } + } catch (KeeperException e) { + System.out + .println("Keeper exception when instantiating queue: " + + e.toString()); + } catch (InterruptedException e) { + System.out.println("Interrupted exception"); + } + } + + // My node name + try { + name = new String(InetAddress.getLocalHost().getCanonicalHostName().toString()); + } catch (UnknownHostException e) { + System.out.println(e.toString()); + } + + } + + /** + * Join barrier + * + * @return + * @throws KeeperException + * @throws InterruptedException + */ + + boolean enter() throws KeeperException, InterruptedException{ + zk.create(root + "/" + name, new byte[0], Ids.OPEN_ACL_UNSAFE, + CreateMode.EPHEMERAL); + while (true) { + synchronized (mutex) { + List<String> list = zk.getChildren(root, true); + + if (list.size() < size) { + mutex.wait(); + } else { + return true; + } + } + } + } + + /** + * Wait until all reach barrier + * + * @return + * @throws KeeperException + * @throws InterruptedException + */ + boolean leave() throws KeeperException, InterruptedException{ + zk.delete(root + "/" + name, 0); + while (true) { + synchronized (mutex) { + List<String> list = zk.getChildren(root, true); + if (list.size() > 0) { + mutex.wait(); + } else { + return true; + } + } + } + } + } + + /** + * Producer-Consumer queue + */ + static public class Queue extends SyncPrimitive { + + /** + * Constructor of producer-consumer queue + * + * @param address + * @param name + */ + Queue(String address, String name) { + super(address); + this.root = name; + // Create ZK node name + if (zk != null) { + try { + Stat s = zk.exists(root, false); + if (s == null) { + zk.create(root, new byte[0], Ids.OPEN_ACL_UNSAFE, + CreateMode.PERSISTENT); + } + } catch (KeeperException e) { + System.out + .println("Keeper exception when instantiating queue: " + + e.toString()); + } catch (InterruptedException e) { + System.out.println("Interrupted exception"); + } + } + } + + /** + * Add element to the queue. + * + * @param i + * @return + */ + + boolean produce(int i) throws KeeperException, InterruptedException{ + ByteBuffer b = ByteBuffer.allocate(4); + byte[] value; + + // Add child with value i + b.putInt(i); + value = b.array(); + zk.create(root + "/element", value, Ids.OPEN_ACL_UNSAFE, + CreateMode.PERSISTENT_SEQUENTIAL); + + return true; + } + + /** + * Remove first element from the queue. + * + * @return + * @throws KeeperException + * @throws InterruptedException + */ + int consume() throws KeeperException, InterruptedException{ + int retvalue = -1; + Stat stat = null; + + // Get the first element available + while (true) { + synchronized (mutex) { + List<String> list = zk.getChildren(root, true); + if (list.size() == 0) { + System.out.println("Going to wait"); + mutex.wait(); + } else { + Integer min = new Integer(list.get(0).substring(7)); + String minNode = list.get(0); + for(String s : list){ + Integer tempValue = new Integer(s.substring(7)); + //System.out.println("Temporary value: " + tempValue); + if(tempValue < min) { + min = tempValue; + minNode = s; + } + } + System.out.println("Temporary value: " + root + "/" + minNode); + byte[] b = zk.getData(root + "/" + minNode, + false, stat); + zk.delete(root + "/" + minNode, 0); + ByteBuffer buffer = ByteBuffer.wrap(b); + retvalue = buffer.getInt(); + + return retvalue; + } + } + } + } + } + + public static void main(String args[]) { + if (args[0].equals("qTest")) + queueTest(args); + else + barrierTest(args); + } + + public static void queueTest(String args[]) { + Queue q = new Queue(args[1], "/app1"); + + System.out.println("Input: " + args[1]); + int i; + Integer max = new Integer(args[2]); + + if (args[3].equals("p")) { + System.out.println("Producer"); + for (i = 0; i < max; i++) + try{ + q.produce(10 + i); + } catch (KeeperException e){ + + } catch (InterruptedException e){ + + } + } else { + System.out.println("Consumer"); + + for (i = 0; i < max; i++) { + try{ + int r = q.consume(); + System.out.println("Item: " + r); + } catch (KeeperException e){ + i--; + } catch (InterruptedException e){ + } + } + } + } + + public static void barrierTest(String args[]) { + Barrier b = new Barrier(args[1], "/b1", new Integer(args[2])); + try{ + boolean flag = b.enter(); + System.out.println("Entered barrier: " + args[2]); + if(!flag) System.out.println("Error when entering the barrier"); + } catch (KeeperException e){ + } catch (InterruptedException e){ + } + + // Generate random integer + Random rand = new Random(); + int r = rand.nextInt(100); + // Loop for rand iterations + for (int i = 0; i < r; i++) { + try { + Thread.sleep(100); + } catch (InterruptedException e) { + } + } + try{ + b.leave(); + } catch (KeeperException e){ + + } catch (InterruptedException e){ + + } + System.out.println("Left barrier"); + } +} +</code></pre> +</div> +<div class="clearboth"> </div> +</div> +<div id="footer"> + <div class="lastmodified"> + <script type="text/javascript"> + <!-- + document.write("Last Published: " + document.lastModified); 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+you may not use this file except in compliance with the License. +You may obtain a copy of the License at + +http://www.apache.org/licenses/LICENSE-2.0 + +Unless required by applicable law or agreed to in writing, software +distributed under the License is distributed on an "AS IS" BASIS, +WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +See the License for the specific language governing permissions and +limitations under the License. +//--> +<h1>ZooKeeper Use Cases</h1> +<ul> +<li>Applications and organizations using ZooKeeper include (alphabetically) [1].</li> +<li>If your use case wants to be listed here. Please do not hesitate, submit a pull request or write an email to <strong>[email protected]</strong>, and then, your use case will be included.</li> +<li>If this documentation has violated your intellectual property rights or you and your company's privacy, write an email to <strong>[email protected]</strong>, we will handle them in a timely manner.</li> +</ul> +<h2>Free Software Projects</h2> +<h3><a href="http://adroitlogic.org/";>AdroitLogic UltraESB</a></h3> +<ul> +<li>Uses ZooKeeper to implement node coordination, in clustering support. This allows the management of the complete cluster, or any specific node - from any other node connected via JMX. A Cluster wide command framework developed on top of the ZooKeeper coordination allows commands that fail on some nodes to be retried etc. We also support the automated graceful round-robin-restart of a complete cluster of nodes using the same framework [1].</li> +</ul> +<h3><a href="http://akka.io/";>Akka</a></h3> +<ul> +<li>Akka is the platform for the next generation event-driven, scalable and fault-tolerant architectures on the JVM. Or: Akka is a toolkit and runtime for building highly concurrent, distributed, and fault tolerant event-driven applications on the JVM [1].</li> +</ul> +<h3><a href="http://www.eclipse.org/ecf";>Eclipse Communication Framework</a></h3> +<ul> +<li>The Eclipse ECF project provides an implementation of its Abstract Discovery services using Zookeeper. ECF itself is used in many projects providing base functionallity for communication, all based on OSGi [1].</li> +</ul> +<h3><a href="http://www.eclipse.org/gyrex";>Eclipse Gyrex</a></h3> +<ul> +<li>The Eclipse Gyrex project provides a platform for building your own Java OSGi based clouds.</li> +<li>ZooKeeper is used as the core cloud component for node membership and management, coordination of jobs executing among workers, a lock service and a simple queue service and a lot more [1].</li> +</ul> +<h3><a href="http://www.goldenorbos.org/";>GoldenOrb</a></h3> +<ul> +<li>massive-scale Graph analysis [1].</li> +</ul> +<h3><a href="https://juju.ubuntu.com/";>Juju</a></h3> +<ul> +<li>Service deployment and orchestration framework, formerly called Ensemble [1].</li> +</ul> +<h3><a href="http://katta.sourceforge.net/";>Katta</a></h3> +<ul> +<li>Katta serves distributed Lucene indexes in a grid environment.</li> +<li>Zookeeper is used for node, master and index management in the grid [1].</li> +</ul> +<h3><a href="https://github.com/anthonyu/KeptCollections";>KeptCollections</a></h3> +<ul> +<li>KeptCollections is a library of drop-in replacements for the data structures in the Java Collections framework.</li> +<li>KeptCollections uses Apache ZooKeeper as a backing store, thus making its data structures distributed and scalable [1].</li> +</ul> +<h3><a href="https://neo4j.com/";>Neo4j</a></h3> +<ul> +<li>Neo4j is a Graph Database. It's a disk based, ACID compliant transactional storage engine for big graphs and fast graph traversals, using external indicies like Lucene/Solr for global searches.</li> +<li>We use ZooKeeper in the Neo4j High Availability components for write-master election, read slave coordination and other cool stuff. ZooKeeper is a great and focused project - we like! [1].</li> +</ul> +<h3><a href="http://sna-projects.com/norbert";>Norbert</a></h3> +<ul> +<li>Partitioned routing and cluster management [1].</li> +</ul> +<h3><a href="https://spring.io/projects/spring-cloud-zookeeper";>spring-cloud-zookeeper</a></h3> +<ul> +<li>Spring Cloud Zookeeper provides Apache Zookeeper integrations for Spring Boot apps through autoconfiguration and binding to the Spring Environment and other Spring programming model idioms. With a few simple annotations you can quickly enable and configure the common patterns inside your application and build large distributed systems with Zookeeper. The patterns provided include Service Discovery and Distributed Configuration [38].</li> +</ul> +<h3><a href="https://projects.spring.io/spring-statemachine/";>spring-statemachine</a></h3> +<ul> +<li>Spring Statemachine is a framework for application developers to use state machine concepts with Spring applications.</li> +<li>Spring Statemachine can provide this feature:Distributed state machine based on a Zookeeper [31,32].</li> +</ul> +<h3><a href="https://projects.spring.io/spring-xd/";>spring-xd</a></h3> +<ul> +<li>Spring XD is a unified, distributed, and extensible system for data ingestion, real time analytics, batch processing, and data export. The projectâs goal is to simplify the development of big data applications.</li> +<li>ZooKeeper - Provides all runtime information for the XD cluster. Tracks running containers, in which containers modules and jobs are deployed, stream definitions, deployment manifests, and the like [30,31].</li> +</ul> +<h3><a href="http://www.talend.com/products-application-integration/application-integration-esb-se.php";>Talend ESB</a></h3> +<ul> +<li>Talend ESB is a versatile and flexible, enterprise service bus.</li> +<li>It uses ZooKeeper as endpoint repository of both REST and SOAP Web services. By using ZooKeeper Talend ESB is able to provide failover and load balancing capabilities in a very light-weight manner [1].</li> +</ul> +<h3><a href="https://github.com/ryanlecompte/redis_failover";>redis_failover</a></h3> +<ul> +<li>Redis Failover is a ZooKeeper-based automatic master/slave failover solution for Ruby [1].</li> +</ul> +<h2>Apache Projects</h2> +<h3><a href="https://accumulo.apache.org/";>Apache Accumulo</a></h3> +<ul> +<li>Accumulo is a distributed key/value store that provides expressive, cell-level access labels.</li> +<li>Apache ZooKeeper plays a central role within the Accumulo architecture. Its quorum consistency model supports an overall Accumulo architecture with no single points of failure. Beyond that, Accumulo leverages ZooKeeper to store and communication configuration information for users and tables, as well as operational states of processes and tablets [2].</li> +</ul> +<h3><a href="http://atlas.apache.org";>Apache Atlas</a></h3> +<ul> +<li>Atlas is a scalable and extensible set of core foundational governance services â enabling enterprises to effectively and efficiently meet their compliance requirements within Hadoop and allows integration with the whole enterprise data ecosystem.</li> +<li>Atlas uses Zookeeper for coordination to provide redundancy and high availability of HBase,Kafka [31,35].</li> +</ul> +<h3><a href="https://bookkeeper.apache.org/";>Apache BookKeeper</a></h3> +<ul> +<li>A scalable, fault-tolerant, and low-latency storage service optimized for real-time workloads.</li> +<li>BookKeeper requires a metadata storage service to store information related to ledgers and available bookies. BookKeeper currently uses ZooKeeper for this and other tasks [3].</li> +</ul> +<h3><a href="http://cxf.apache.org/distributed-osgi.html";>Apache CXF DOSGi</a></h3> +<ul> +<li>Apache CXF is an open source services framework. CXF helps you build and develop services using frontend programming APIs, like JAX-WS and JAX-RS. These services can speak a variety of protocols such as SOAP, XML/HTTP, RESTful HTTP, or CORBA and work over a variety of transports such as HTTP, JMS or JBI.</li> +<li>The Distributed OSGi implementation at Apache CXF uses ZooKeeper for its Discovery functionality [4].</li> +</ul> +<h3><a href="http://drill.apache.org/";>Apache Drill</a></h3> +<ul> +<li>Schema-free SQL Query Engine for Hadoop, NoSQL and Cloud Storage</li> +<li>ZooKeeper maintains ephemeral cluster membership information. The Drillbits use ZooKeeper to find other Drillbits in the cluster, and the client uses ZooKeeper to find Drillbits to submit a query [28].</li> +</ul> +<h3><a href="https://druid.apache.org/";>Apache Druid</a></h3> +<ul> +<li>Apache Druid is a high performance real-time analytics database.</li> +<li>Apache Druid uses Apache ZooKeeper (ZK) for management of current cluster state. The operations that happen over ZK are [27]: +<ul> +<li>Coordinator leader election</li> +<li>Segment "publishing" protocol from Historical and Realtime</li> +<li>Segment load/drop protocol between Coordinator and Historical</li> +<li>Overlord leader election</li> +<li>Overlord and MiddleManager task management</li> +</ul> +</li> +</ul> +<h3><a href="http://dubbo.apache.org";>Apache Dubbo</a></h3> +<ul> +<li>Apache Dubbo is a high-performance, java based open source RPC framework.</li> +<li>Zookeeper is used for service registration discovery and configuration management in Dubbo [6].</li> +</ul> +<h3><a href="https://flink.apache.org/";>Apache Flink</a></h3> +<ul> +<li>Apache Flink is a framework and distributed processing engine for stateful computations over unbounded and bounded data streams. Flink has been designed to run in all common cluster environments, perform computations at in-memory speed and at any scale.</li> +<li>To enable JobManager High Availability you have to set the high-availability mode to zookeeper, configure a ZooKeeper quorum and set up a masters file with all JobManagers hosts and their web UI ports. Flink leverages ZooKeeper for distributed coordination between all running JobManager instances. ZooKeeper is a separate service from Flink, which provides highly reliable distributed coordination via leader election and light-weight consistent state storage [23].</li> +</ul> +<h3><a href="https://flume.apache.org/";>Apache Flume</a></h3> +<ul> +<li>Flume is a distributed, reliable, and available service for efficiently collecting, aggregating, and moving large amounts of log data. It has a simple and flexible architecture based on streaming data flows. It is robust and fault tolerant with tunable reliability mechanisms and many failover and recovery mechanisms. It uses a simple extensible data model that allows for online analytic application.</li> +<li>Flume supports Agent configurations via Zookeeper. This is an experimental feature [5].</li> +</ul> +<h3><a href="https://fluo.apache.org/";>Apache Fluo</a></h3> +<ul> +<li>Apache Fluo is a distributed processing system that lets users make incremental updates to large data sets.</li> +<li>Apache Fluo is built on Apache Accumulo which uses Apache Zookeeper for consensus [31,37].</li> +</ul> +<h3><a href="https://griffin.apache.org/";>Apache Griffin</a></h3> +<ul> +<li>Big Data Quality Solution For Batch and Streaming.</li> +<li>Griffin uses Zookeeper for coordination to provide redundancy and high availability of Kafka [31,36].</li> +</ul> +<h3><a href="http://hadoop.apache.org/";>Apache Hadoop</a></h3> +<ul> +<li>The Apache Hadoop software library is a framework that allows for the distributed processing of large data sets across clusters of computers using simple programming models. It is designed to scale up from single servers to thousands of machines, each offering local computation and storage. Rather than rely on hardware to deliver high-availability, the library itself is designed to detect and handle failures at the application layer, so delivering a highly-available service on top of a cluster of computers, each of which may be prone to failures.</li> +<li>The implementation of automatic HDFS failover relies on ZooKeeper for the following things: +<ul> +<li><strong>Failure detection</strong> - each of the NameNode machines in the cluster maintains a persistent session in ZooKeeper. If the machine crashes, the ZooKeeper session will expire, notifying the other NameNode that a failover should be triggered.</li> +<li><strong>Active NameNode election</strong> - ZooKeeper provides a simple mechanism to exclusively elect a node as active. If the current active NameNode crashes, another node may take a special exclusive lock in ZooKeeper indicating that it should become the next active.</li> +</ul> +</li> +<li>The ZKFailoverController (ZKFC) is a new component which is a ZooKeeper client which also monitors and manages the state of the NameNode. Each of the machines which runs a NameNode also runs a ZKFC, and that ZKFC is responsible for: +<ul> +<li><strong>Health monitoring</strong> - the ZKFC pings its local NameNode on a periodic basis with a health-check command. So long as the NameNode responds in a timely fashion with a healthy status, the ZKFC considers the node healthy. If the node has crashed, frozen, or otherwise entered an unhealthy state, the health monitor will mark it as unhealthy.</li> +<li><strong>ZooKeeper session management</strong> - when the local NameNode is healthy, the ZKFC holds a session open in ZooKeeper. If the local NameNode is active, it also holds a special âlockâ znode. This lock uses ZooKeeperâs support for âephemeralâ nodes; if the session expires, the lock node will be automatically deleted.</li> +<li><strong>ZooKeeper-based election</strong> - if the local NameNode is healthy, and the ZKFC sees that no other node currently holds the lock znode, it will itself try to acquire the lock. If it succeeds, then it has âwon the electionâ, and is responsible for running a failover to make its local NameNode active. The failover process is similar to the manual failover described above: first, the previous active is fenced if necessary, and then the local NameNode transitions to active state [7].</li> +</ul> +</li> +</ul> +<h3><a href="https://hbase.apache.org/";>Apache HBase</a></h3> +<ul> +<li>HBase is the Hadoop database. It's an open-source, distributed, column-oriented store model.</li> +<li>HBase uses ZooKeeper for master election, server lease management, bootstrapping, and coordination between servers. A distributed Apache HBase installation depends on a running ZooKeeper cluster. All participating nodes and clients need to be able to access the running ZooKeeper ensemble [8].</li> +<li>As you can see, ZooKeeper is a fundamental part of HBase. All operations that require coordination, such as Regions assignment, Master-Failover, replication, and snapshots, are built on ZooKeeper [20].</li> +</ul> +<h3><a href="http://helix.apache.org/";>Apache Helix</a></h3> +<ul> +<li>A cluster management framework for partitioned and replicated distributed resources.</li> +<li>We need a distributed store to maintain the state of the cluster and a notification system to notify if there is any change in the cluster state. Helix uses Apache ZooKeeper to achieve this functionality [21]. Zookeeper provides: +<ul> +<li>A way to represent PERSISTENT state which remains until its deleted</li> +<li>A way to represent TRANSIENT/EPHEMERAL state which vanishes when the process that created the state dies</li> +<li>A notification mechanism when there is a change in PERSISTENT and EPHEMERAL state</li> +</ul> +</li> +</ul> +<h3><a href="https://hive.apache.org";>Apache Hive</a></h3> +<ul> +<li>The Apache Hive data warehouse software facilitates reading, writing, and managing large datasets residing in distributed storage using SQL. Structure can be projected onto data already in storage. A command line tool and JDBC driver are provided to connect users to Hive.</li> +<li>Hive has been using ZooKeeper as distributed lock manager to support concurrency in HiveServer2 [25,26].</li> +</ul> +<h3><a href="https://ignite.apache.org/";>Apache Ignite</a></h3> +<ul> +<li>Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads delivering in-memory speeds at petabyte scale</li> +<li>Apache Ignite discovery mechanism goes with a ZooKeeper implementations which allows scaling Ignite clusters to 100s and 1000s of nodes preserving linear scalability and performance [31,34].â</li> +</ul> +<h3><a href="http://james.apache.org/mailbox/";>Apache James Mailbox</a></h3> +<ul> +<li>The Apache James Mailbox is a library providing a flexible Mailbox storage accessible by mail protocols (IMAP4, POP3, SMTP,...) and other protocols.</li> +<li>Uses Zookeeper and Curator Framework for generating distributed unique ID's [31].</li> +</ul> +<h3><a href="https://kafka.apache.org/";>Apache Kafka</a></h3> +<ul> +<li>Kafka is a distributed publish/subscribe messaging system</li> +<li>Apache Kafka relies on ZooKeeper for the following things: +<ul> +<li><strong>Controller election</strong> The controller is one of the most important broking entity in a Kafka ecosystem, and it also has the responsibility to maintain the leader-follower relationship across all the partitions. If a node by some reason is shutting down, itâs the controllerâs responsibility to tell all the replicas to act as partition leaders in order to fulfill the duties of the partition leaders on the node that is about to fail. So, whenever a node shuts down, a new controller can be elected and it can also be made sure that at any given time, there is only one controller and all the follower nodes have agreed on that.</li> +<li><strong>Configuration Of Topics</strong> The configuration regarding all the topics including the list of existing topics, the number of partitions for each topic, the location of all the replicas, list of configuration overrides for all topics and which node is the preferred leader, etc.</li> +<li><strong>Access control lists</strong> Access control lists or ACLs for all the topics are also maintained within Zookeeper.</li> +<li><strong>Membership of the cluster</strong> Zookeeper also maintains a list of all the brokers that are functioning at any given moment and are a part of the cluster [9].</li> +</ul> +</li> +</ul> +<h3><a href="http://kylin.apache.org/";>Apache Kylin</a></h3> +<ul> +<li>Apache Kylin is an open source Distributed Analytics Engine designed to provide SQL interface and multi-dimensional analysis (OLAP) on Hadoop/Spark supporting extremely large datasets, original contributed from eBay Inc.</li> +<li>Apache Kylin leverages Zookeeper for job coordination [31,33].</li> +</ul> +<h3><a href="http://mesos.apache.org/";>Apache Mesos</a></h3> +<ul> +<li>Apache Mesos abstracts CPU, memory, storage, and other compute resources away from machines (physical or virtual), enabling fault-tolerant and elastic distributed systems to easily be built and run effectively.</li> +<li>Mesos has a high-availability mode that uses multiple Mesos masters: one active master (called the leader or leading master) and several backups in case it fails. The masters elect the leader, with Apache ZooKeeper both coordinating the election and handling leader detection by masters, agents, and scheduler drivers [10].</li> +</ul> +<h3><a href="https://oozie.apache.org";>Apache Oozie</a></h3> +<ul> +<li>Oozie is a workflow scheduler system to manage Apache Hadoop jobs.</li> +<li>the Oozie servers use it for coordinating access to the database and communicating with each other. In order to have full HA, there should be at least 3 ZooKeeper servers [29].</li> +</ul> +<h3><a href="https://pulsar.apache.org";>Apache Pulsar</a></h3> +<ul> +<li>Apache Pulsar is an open-source distributed pub-sub messaging system originally created at Yahoo and now part of the Apache Software Foundation</li> +<li>Pulsar uses Apache Zookeeper for metadata storage, cluster configuration, and coordination. In a Pulsar instance: +<ul> +<li>A configuration store quorum stores configuration for tenants, namespaces, and other entities that need to be globally consistent.</li> +<li>Each cluster has its own local ZooKeeper ensemble that stores cluster-specific configuration and coordination such as ownership metadata, broker load reports, BookKeeper ledger metadata, and more [24].</li> +</ul> +</li> +</ul> +<h3><a href="https://lucene.apache.org/solr/";>Apache Solr</a></h3> +<ul> +<li>Solr is the popular, blazing-fast, open source enterprise search platform built on Apache Lucene.</li> +<li>In the "Cloud" edition (v4.x and up) of enterprise search engine Apache Solr, ZooKeeper is used for configuration, leader election and more [12,13].</li> +</ul> +<h3><a href="https://spark.apache.org/";>Apache Spark</a></h3> +<ul> +<li>Apache Spark is a unified analytics engine for large-scale data processing.</li> +<li>Utilizing ZooKeeper to provide leader election and some state storage, you can launch multiple Masters in your cluster connected to the same ZooKeeper instance. One will be elected âleaderâ and the others will remain in standby mode. If the current leader dies, another Master will be elected, recover the old Masterâs state, and then resume scheduling [14].</li> +</ul> +<h3><a href="http://storm.apache.org";>Apache Storm</a></h3> +<ul> +<li>Apache Storm is a free and open source distributed realtime computation system. Apache Storm makes it easy to reliably process unbounded streams of data, doing for realtime processing what Hadoop did for batch processing. Apache Storm is simple, can be used with any programming language, and is a lot of fun to use!</li> +<li>Storm uses Zookeeper for coordinating the cluster [22].</li> +</ul> +<h2>Companies</h2> +<h3><a href="http://www.ageto.de/";>AGETO</a></h3> +<ul> +<li>The AGETO RnD team uses ZooKeeper in a variety of internal as well as external consulting projects [1].</li> +</ul> +<h3><a href="http://www.benipaltechnologies.com/";>Benipal Technologies</a></h3> +<ul> +<li>ZooKeeper is used for internal application development with Solr and Hadoop with Hbase [1].</li> +</ul> +<h3><a href="http://box.net/";>Box</a></h3> +<ul> +<li>Box uses ZooKeeper for service discovery, service coordination, Solr and Hadoop support, etc [1].</li> +</ul> +<h3><a href="http://www.deepdyve.com/";>Deepdyve</a></h3> +<ul> +<li>We do search for research and provide access to high quality content using advanced search technologies Zookeeper is used to manage server state, control index deployment and a myriad other tasks [1].</li> +</ul> +<h3><a href="https://www.facebook.com/";>Facebook</a></h3> +<ul> +<li>Facebook uses the Zeus ([17,18]) for configuration management which is a forked version of ZooKeeper, with many scalability and performance en- hancements in order to work at the Facebook scale. It runs a consensus protocol among servers distributed across mul- tiple regions for resilience. If the leader fails, a follower is converted into a new leader.</li> +</ul> +<h3><a href="http://www.idium.no/no/idium_portal/";>Idium Portal</a></h3> +<ul> +<li>Idium Portal is a hosted web-publishing system delivered by Norwegian company, Idium AS.</li> +<li>ZooKeeper is used for cluster messaging, service bootstrapping, and service coordination [1].</li> +</ul> +<h3><a href="http://www.makara.com/";>Makara</a></h3> +<ul> +<li>Using ZooKeeper on 2-node cluster on VMware workstation, Amazon EC2, Zen</li> +<li>Using zkpython</li> +<li>Looking into expanding into 100 node cluster [1].</li> +</ul> +<h3><a href="http://www.midokura.com/";>Midokura</a></h3> +<ul> +<li>We do virtualized networking for the cloud computing era. We use ZooKeeper for various aspects of our distributed control plane [1].</li> +</ul> +<h3><a href="https://www.pinterest.com/";>Pinterest</a></h3> +<ul> +<li>Pinterest uses the ZooKeeper for Service discovery and dynamic configuration.Like many large scale web sites, Pinterestâs infrastructure consists of servers that communicate with backend services composed of a number of individual servers for managing load and fault tolerance. Ideally, weâd like the configuration to reflect only the active hosts, so clients donât need to deal with bad hosts as often. ZooKeeper provides a well known pattern to solve this problem [19].</li> +</ul> +<h3><a href="http://www.rackspace.com/email_hosting";>Rackspace</a></h3> +<ul> +<li>The Email & Apps team uses ZooKeeper to coordinate sharding and responsibility changes in a distributed e-mail client that pulls and indexes data for search. ZooKeeper also provides distributed locking for connections to prevent a cluster from overwhelming servers [1].</li> +</ul> +<h3><a href="http://sematext.com/";>Sematext</a></h3> +<ul> +<li>Uses ZooKeeper in SPM (which includes ZooKeeper monitoring component, too!), Search Analytics, and Logsene [1].</li> +</ul> +<h3><a href="http://tubemogul.com/";>Tubemogul</a></h3> +<ul> +<li>Uses ZooKeeper for leader election, configuration management, locking, group membership [1].</li> +</ul> +<h3><a href="https://twitter.com/";>Twitter</a></h3> +<ul> +<li>ZooKeeper is used at Twitter as the source of truth for storing critical metadata. It serves as a coordination kernel to provide distributed coordination services, such as leader election and distributed locking. Some concrete examples of ZooKeeper in action include [15,16]:</li> +<li>ZooKeeper is used to store service registry, which is used by Twitterâs naming service for service discovery.</li> +<li>Manhattan (Twitterâs in-house key-value database), Nighthawk (sharded Redis), and Blobstore (in-house photo and video storage), stores its cluster topology information in ZooKeeper.</li> +<li>EventBus, Twitterâs pub-sub messaging system, stores critical metadata in ZooKeeper and uses ZooKeeper for leader election.</li> +<li>Mesos, Twitterâs compute platform, uses ZooKeeper for leader election.</li> +</ul> +<h3><a href="http://www.vast.com/";>Vast.com</a></h3> +<ul> +<li>Used internally as a part of sharding services, distributed synchronization of data/index updates, configuration management and failover support [1].</li> +</ul> +<h3><a href="http://wealthfront.com/";>Wealthfront</a></h3> +<ul> +<li>Wealthfront uses ZooKeeper for service discovery, leader election and distributed locking among its many backend services. ZK is an essential part of Wealthfront's continuous <a href="http://eng.wealthfront.com/2010/05/02/deployment-infrastructure-for-continuous-deployment/";>deployment infrastructure</a> [1].</li> +</ul> +<h3><a href="http://www.yahoo.com/";>Yahoo!</a></h3> +<ul> +<li>ZooKeeper is used for a myriad of services inside Yahoo! for doing leader election, configuration management, sharding, locking, group membership etc [1].</li> +</ul> +<h3><a href="http://www.zynga.com/";>Zynga</a></h3> +<ul> +<li>ZooKeeper at Zynga is used for a variety of services including configuration management, leader election, sharding and more [1].</li> +</ul> +<h4>References</h4> +<ul> +<li>[1] https://cwiki.apache.org/confluence/display/ZOOKEEPER/PoweredBy</li> +<li>[2] https://www.youtube.com/watch?v=Ew53T6h9oRw</li> +<li>[3] https://bookkeeper.apache.org/docs/4.7.3/getting-started/concepts/#ledgers</li> +<li>[4] http://cxf.apache.org/dosgi-discovery-demo-page.html</li> +<li>[5] https://flume.apache.org/FlumeUserGuide.html</li> +<li>[6] http://dubbo.apache.org/en-us/blog/dubbo-zk.html</li> +<li>[7] https://hadoop.apache.org/docs/r2.7.1/hadoop-project-dist/hadoop-hdfs/HDFSHighAvailabilityWithQJM.html</li> +<li>[8] https://hbase.apache.org/book.html#zookeeper</li> +<li>[9] https://www.cloudkarafka.com/blog/2018-07-04-cloudkarafka_what_is_zookeeper.html</li> +<li>[10] http://mesos.apache.org/documentation/latest/high-availability/</li> +<li>[11] http://incubator.apache.org/projects/s4.html</li> +<li>[12] https://lucene.apache.org/solr/guide/6_6/using-zookeeper-to-manage-configuration-files.html#UsingZooKeepertoManageConfigurationFiles-StartupBootstrap</li> +<li>[13] https://lucene.apache.org/solr/guide/6_6/setting-up-an-external-zookeeper-ensemble.html</li> +<li>[14] https://spark.apache.org/docs/latest/spark-standalone.html#standby-masters-with-zookeeper</li> +<li>[15] https://blog.twitter.com/engineering/en_us/topics/infrastructure/2018/zookeeper-at-twitter.html</li> +<li>[16] https://blog.twitter.com/engineering/en_us/topics/infrastructure/2018/dynamic-configuration-at-twitter.html</li> +<li>[17] TANG, C., KOOBURAT, T., VENKATACHALAM, P.,CHANDER, A., WEN, Z., NARAYANAN, A., DOWELL,P., AND KARL, R. Holistic Configuration Management at Facebook. In Proceedings of the 25th Symposium on Operating System Principles (SOSPâ15) (Monterey, CA,USA, Oct. 2015).</li> +<li>[18] https://www.youtube.com/watch?v=SeZV373gUZc</li> +<li>[19] https://medium.com/@Pinterest_Engineering/zookeeper-resilience-at-pinterest-adfd8acf2a6b</li> +<li>[20] https://blog.cloudera.com/what-are-hbase-znodes/</li> +<li>[21] https://helix.apache.org/Architecture.html</li> +<li>[22] http://storm.apache.org/releases/current/Setting-up-a-Storm-cluster.html</li> +<li>[23] https://ci.apache.org/projects/flink/flink-docs-release-1.9/ops/jobmanager_high_availability.html</li> +<li>[24] https://pulsar.apache.org/docs/en/concepts-architecture-overview/#metadata-store</li> +<li>[25] https://cwiki.apache.org/confluence/display/Hive/Locking</li> +<li>[26] <em>ZooKeeperHiveLockManager</em> implementation in the <a href="https://github.com/apache/hive/";>hive</a> code base</li> +<li>[27] https://druid.apache.org/docs/latest/dependencies/zookeeper.html</li> +<li>[28] https://mapr.com/blog/apache-drill-architecture-ultimate-guide/</li> +<li>[29] https://oozie.apache.org/docs/4.1.0/AG_Install.html</li> +<li>[30] https://docs.spring.io/spring-xd/docs/current/reference/html/</li> +<li>[31] https://cwiki.apache.org/confluence/display/CURATOR/Powered+By</li> +<li>[32] https://projects.spring.io/spring-statemachine/</li> +<li>[33] https://www.tigeranalytics.com/blog/apache-kylin-architecture/</li> +<li>[34] https://apacheignite.readme.io/docs/cluster-discovery</li> +<li>[35] http://atlas.apache.org/HighAvailability.html</li> +<li>[36] http://griffin.apache.org/docs/usecases.html</li> +<li>[37] https://fluo.apache.org/</li> +<li>[38] https://spring.io/projects/spring-cloud-zookeeper</li> +</ul> +</div> +<div class="clearboth"> </div> +</div> +<div id="footer"> + <div class="lastmodified"> + <script type="text/javascript"> + <!-- + document.write("Last Published: " + document.lastModified); + // --> + </script> + </div> + <div class="copyright"> + Copyright © <a href="http://www.apache.org/licenses/";>The Apache Software Foundation.</a> + </div> + <div id="logos"></div> +</div> +</body> +</html> \ No newline at end of file
