A Distributed Coordination Service for Distributed Applications

  • ZooKeeper is a distributed, open-source coordination service for distributed applications.
  • It uses a data model styled after the familiar directory tree structure of file systems.

Design Goals

ZooKeeper is simple. 

  • ZooKeeper allows distributed processes to coordinate with each other through a shared hierarchical namespace which is organized similarly to a standard file system.
  • The namespace consists of data registers – called znodes, in ZooKeeper parlance – and these are similar to files and directories.
  • Unlike a typical file system, which is designed for storage, ZooKeeper data is kept in-memory, which means ZooKeeper can achieve high throughput and low latency numbers.
  • The ZooKeeper framework was originally built at “Yahoo!” for accessing their applications in an easy and robust manner. Later, Apache ZooKeeper became a standard for organized service used by Hadoop, HBase, and other distributed frameworks. For example, Apache HBase uses ZooKeeper to track the status of distributed data.

ZooKeeper is replicated. Like the distributed processes it coordinates, ZooKeeper itself is intended to be replicated over a set of hosts called an ensemble.

ZooKeeper Service
ZooKeeper service

The servers that make up the ZooKeeper Service must all know about each other. They maintain an in-memory image of state, along with a transaction logs and snapshots in a persistent store. As long as a majority of the servers are available, the ZooKeeper service will be available.

Clients connect to a single ZooKeeper server. The client maintains a TCP connection through which it sends requests, gets responses, gets watch events, and sends heart beats. If the TCP connection to the server breaks, the client will connect to a different server.

ZooKeeper is ordered. ZooKeeper stamps each update with a number that reflects the order of all ZooKeeper transactions. Subsequent operations can use the order to implement higher-level abstractions, such as synchronization primitives.

ZooKeeper is fast. It is especially fast in “read-dominant” workloads. ZooKeeper applications run on thousands of machines, and it performs best where reads are more common than writes, at ratios of around 10:1.

Before moving further, it is important that we know a thing or two about distributed applications. So, let us start the discussion with a quick overview of distributed applications.

Distributed Application

A distributed application can run on multiple systems in a network at a given time (simultaneously) by coordinating among themselves to complete a particular task in a fast and efficient manner. Normally, complex and time-consuming tasks, which will take hours to complete by a non-distributed application (running in a single system) can be done in minutes by a distributed application by using computing capabilities of all the system involved.

The time to complete the task can be further reduced by configuring the distributed application to run on more systems. A group of systems in which a distributed application is running is called a Cluster and each machine running in a cluster is called a Node.

A distributed application has two parts, Server and Client application. Server applications are actually distributed and have a common interface so that clients can connect to any server in the cluster and get the same result. Client applications are the tools to interact with a distributed application.

Distributed Application

Benefits of Distributed Applications

  • Reliability − Failure of a single or a few systems does not make the whole system to fail.
  • Scalability − Performance can be increased as and when needed by adding more machines with minor change in the configuration of the application with no downtime.
  • Transparency − Hides the complexity of the system and shows itself as a single entity / application.

Challenges of Distributed Applications

  • Race condition − Two or more machines trying to perform a particular task, which actually needs to be done only by a single machine at any given time. For example, shared resources should only be modified by a single machine at any given time.
  • Deadlock − Two or more operations waiting for each other to complete indefinitely.
  • Inconsistency − Partial failure of data.

What is Apache ZooKeeper Meant For?

Apache ZooKeeper is a service used by a cluster (group of nodes) to coordinate between themselves and maintain shared data with robust synchronization techniques. ZooKeeper is itself a distributed application providing services for writing a distributed application.

The common services provided by ZooKeeper are as follows −

  • Naming service − Identifying the nodes in a cluster by name. It is similar to DNS, but for nodes.
  • Configuration management − Latest and up-to-date configuration information of the system for a joining node.
  • Cluster management − Joining / leaving of a node in a cluster and node status at real time.
  • Leader election − Electing a node as leader for coordination purpose.
  • Locking and synchronization service − Locking the data while modifying it. This mechanism helps you in automatic fail recovery while connecting other distributed applications like Apache HBase.
  • Highly reliable data registry − Availability of data even when one or a few nodes are down.

Distributed applications offer a lot of benefits, but they throw a few complex and hard-to-crack challenges as well. ZooKeeper framework provides a complete mechanism to overcome all the challenges. Race condition and deadlock are handled using fail-safe synchronization approach. Another main drawback is inconsistency of data, which ZooKeeper resolves with atomicity.

Benefits of ZooKeeper

Here are the benefits of using ZooKeeper −

  • Simple distributed coordination process
  • Synchronization − Mutual exclusion and co-operation between server processes. This process helps in Apache HBase for configuration management.
  • Ordered Messages
  • Serialization − Encode the data according to specific rules. Ensure your application runs consistently. This approach can be used in MapReduce to coordinate queue to execute running threads.
  • Reliability
  • Atomicity − Data transfer either succeed or fail completely, but no transaction is partial.

Each one of the components that is a part of the ZooKeeper architecture has been explained in the following table.

ClientClients, one of the nodes in our distributed application cluster, access information from the server. For a particular time interval, every client sends a message to the server to let the sever know that the client is alive.Similarly, the server sends an acknowledgement when a client connects. If there is no response from the connected server, the client automatically redirects the message to another server.
ServerServer, one of the nodes in our ZooKeeper ensemble, provides all the services to clients. Gives acknowledgement to client to inform that the server is alive.
EnsembleGroup of ZooKeeper servers. The minimum number of nodes that is required to form an ensemble is 3.
LeaderServer node which performs automatic recovery if any of the connected node failed. Leaders are elected on service startup.
FollowerServer node which follows leader instruction.

Hierarchical Namespace

The following diagram depicts the tree structure of ZooKeeper file system used for memory representation. ZooKeeper node is referred as znode. Every znode is identified by a name and separated by a sequence of path (/).

  • In the diagram, first you have a root znode separated by “/”. Under root, you have two logical namespaces config and workers.
  • The config namespace is used for centralized configuration management and the workers namespace is used for naming.
  • Under config namespace, each znode can store upto 1MB of data. This is similar to UNIX file system except that the parent znode can store data as well. The main purpose of this structure is to store synchronized data and describe the metadata of the znode. This structure is called as ZooKeeper Data Model.
Hierarchical Namespace

Every znode in the ZooKeeper data model maintains a stat structure. A stat simply provides the metadata of a znode. It consists of Version number, Action control list (ACL), Timestamp, and Data length.

  • Version number − Every znode has a version number, which means every time the data associated with the znode changes, its corresponding version number would also increased. The use of version number is important when multiple zookeeper clients are trying to perform operations over the same znode.
  • Action Control List (ACL) − ACL is basically an authentication mechanism for accessing the znode. It governs all the znode read and write operations.
  • Timestamp − Timestamp represents time elapsed from znode creation and modification. It is usually represented in milliseconds. ZooKeeper identifies every change to the znodes from “Transaction ID” (zxid). Zxid is unique and maintains time for each transaction so that you can easily identify the time elapsed from one request to another request.
  • Data length − Total amount of the data stored in a znode is the data length. You can store a maximum of 1MB of data.

Types of Znodes

Znodes are categorized as persistence, sequential, and ephemeral.

  • Persistence znode − Persistence znode is alive even after the client, which created that particular znode, is disconnected. By default, all znodes are persistent unless otherwise specified.
  • Ephemeral znode − Ephemeral znodes are active until the client is alive. When a client gets disconnected from the ZooKeeper ensemble, then the ephemeral znodes get deleted automatically. For this reason, only ephemeral znodes are not allowed to have a children further. If an ephemeral znode is deleted, then the next suitable node will fill its position. Ephemeral znodes play an important role in Leader election.
  • Sequential znode − Sequential znodes can be either persistent or ephemeral. When a new znode is created as a sequential znode, then ZooKeeper sets the path of the znode by attaching a 10 digit sequence number to the original name. For example, if a znode with path /myapp is created as a sequential znode, ZooKeeper will change the path to /myapp0000000001 and set the next sequence number as 0000000002. If two sequential znodes are created concurrently, then ZooKeeper never uses the same number for each znode. Sequential znodes play an important role in Locking and Synchronization.


Sessions are very important for the operation of ZooKeeper. Requests in a session are executed in FIFO order. Once a client connects to a server, the session will be established and a session id is assigned to the client.

The client sends heartbeats at a particular time interval to keep the session valid. If the ZooKeeper ensemble does not receive heartbeats from a client for more than the period (session timeout) specified at the starting of the service, it decides that the client died.

Session timeouts are usually represented in milliseconds. When a session ends for any reason, the ephemeral znodes created during that session also get deleted.


Watches are a simple mechanism for the client to get notifications about the changes in the ZooKeeper ensemble. Clients can set watches while reading a particular znode. Watches send a notification to the registered client for any of the znode (on which client registers) changes.

Znode changes are modification of data associated with the znode or changes in the znode’s children. Watches are triggered only once. If a client wants a notification again, it must be done through another read operation. When a connection session is expired, the client will be disconnected from the server and the associated watches are also removed.

Once a ZooKeeper ensemble starts, it will wait for the clients to connect. Clients will connect to one of the nodes in the ZooKeeper ensemble. It may be a leader or a follower node. Once a client is connected, the node assigns a session ID to the particular client and sends an acknowledgement to the client. If the client does not get an acknowledgment, it simply tries to connect another node in the ZooKeeper ensemble. Once connected to a node, the client will send heartbeats to the node in a regular interval to make sure that the connection is not lost.

  • If a client wants to read a particular znode, it sends a read request to the node with the znode path and the node returns the requested znode by getting it from its own database. For this reason, reads are fast in ZooKeeper ensemble.
  • If a client wants to store data in the ZooKeeper ensemble, it sends the znode path and the data to the server. The connected server will forward the request to the leader and then the leader will reissue the writing request to all the followers. If only a majority of the nodes respond successfully, then the write request will succeed and a successful return code will be sent to the client. Otherwise, the write request will fail. The strict majority of nodes is called as Quorum.

Nodes in a ZooKeeper Ensemble

Let us analyze the effect of having different number of nodes in the ZooKeeper ensemble.

  • If we have a single node, then the ZooKeeper ensemble fails when that node fails. It contributes to “Single Point of Failure” and it is not recommended in a production environment.
  • If we have two nodes and one node fails, we don’t have majority as well, since one out of two is not a majority.
  • If we have three nodes and one node fails, we have majority and so, it is the minimum requirement. It is mandatory for a ZooKeeper ensemble to have at least three nodes in a live production environment.
  • If we have four nodes and two nodes fail, it fails again and it is similar to having three nodes. The extra node does not serve any purpose and so, it is better to add nodes in odd numbers, e.g., 3, 5, 7.

We know that a write process is expensive than a read process in ZooKeeper ensemble, since all the nodes need to write the same data in its database. So, it is better to have less number of nodes (3, 5 or 7) than having a large number of nodes for a balanced environment.

The following diagram depicts the ZooKeeper WorkFlow and the subsequent table explains its different components.

ZooKeeper Ensemble
WriteWrite process is handled by the leader node. The leader forwards the write request to all the znodes and waits for answers from the znodes. If half of the znodes reply, then the write process is complete.
ReadReads are performed internally by a specific connected znode, so there is no need to interact with the cluster.
Replicated DatabaseIt is used to store data in zookeeper. Each znode has its own database and every znode has the same data at every time with the help of consistency.
LeaderLeader is the Znode that is responsible for processing write requests.
FollowerFollowers receive write requests from the clients and forward them to the leader znode.
Request ProcessorPresent only in leader node. It governs write requests from the follower node.
Atomic broadcastsResponsible for broadcasting the changes from the leader node to the follower nodes.

Let us analyze how a leader node can be elected in a ZooKeeper ensemble. Consider there are N number of nodes in a cluster. The process of leader election is as follows −

  • All the nodes create a sequential, ephemeral znode with the same path, /app/leader_election/guid_.
  • ZooKeeper ensemble will append the 10-digit sequence number to the path and the znode created will be /app/leader_election/guid_0000000001, /app/leader_election/guid_0000000002, etc.
  • For a given instance, the node which creates the smallest number in the znode becomes the leader and all the other nodes are followers.
  • Each follower node watches the znode having the next smallest number. For example, the node which creates znode /app/leader_election/guid_0000000008 will watch the znode /app/leader_election/guid_0000000007 and the node which creates the znode /app/leader_election/guid_0000000007 will watch the znode /app/leader_election/guid_0000000006.
  • If the leader goes down, then its corresponding znode /app/leader_electionN gets deleted.
  • The next in line follower node will get the notification through watcher about the leader removal.
  • The next in line follower node will check if there are other znodes with the smallest number. If none, then it will assume the role of the leader. Otherwise, it finds the node which created the znode with the smallest number as leader.
  • Similarly, all other follower nodes elect the node which created the znode with the smallest number as leader.

Leader election is a complex process when it is done from scratch. But ZooKeeper service makes it very simple. Let us

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