Co-ordinating and managing a service in a distributed environment is a complicated process. ZooKeeper solves this issue with its simple architecture and API. ZooKeeper allows developers to focus on core application logic without worrying about the distributed nature of the application. Later, Apache ZooKeeper became a standard for organized service used by Hadoop, HBase, and other distributed frameworks.
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. 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. For example, shared resources should only be modified by a single machine at any given time. 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. It is similar to DNS, but for nodes. This mechanism helps you in automatic fail recovery while connecting other distributed applications like Apache HBase. 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. This process helps in Apache HBase for configuration management. Ensure your application runs consistently.
This approach can be used in MapReduce to coordinate queue to execute running threads. Before going deep into the working of ZooKeeper, let us take a look at the fundamental concepts of ZooKeeper. Each one of the components that is a part of the ZooKeeper architecture has been explained in the following table. Clients, 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. The following diagram depicts the tree structure of ZooKeeper file system used for memory representation. ZooKeeper node is referred as znode. 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. Every znode in the ZooKeeper data model maintains a stat structure. A stat simply provides the metadata of a znode. The use of version number is important when multiple zookeeper clients are trying to perform operations over the same znode.
It governs all the znode read and write operations. It is usually represented in milliseconds. Zxid is unique and maintains time for each transaction so that you can easily identify the time elapsed from one request to another request. You can store a maximum of 1MB of data. By default, all znodes are persistent unless otherwise specified.
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. 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. 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. 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. Starting with The data directory specifies a configuration subfolder the GeoEvent Gateway will create when the service is restarted. The data directory specifies a configuration subfolder the GeoEvent Gateway will create when the daemon is restarted.
The Kafka on-disk topic queues and ZooKeeper configuration files should be organized in the same data directory. Kafka and ZooKeeper are tightly coupled, and their runtime files should be collocated. Data from event records flows through Kafka topics as it is ingested, processed, and disseminated. The status of configured elements and information cached by GeoEvent Server is frequently updated in the ZooKeeper configuration store.
It's a good idea to back up the ZooKeeper Data Directory periodically. Although ZooKeeper is highly reliable because a persistent copy is replicated on each server, recovering from backups may be necessary if a catastrophic failure or user error occurs.
When you use the default configuration, the ZooKeeper server does not remove the snapshots and log files, so they will accumulate over time. You will need to clean up this directory occasionally, taking into account on your backup schedules and processes. To automate the cleanup, a zkCleanup.
Modify this script as necessary for your situation. In general, you want to run this as a cron task based on your backup schedule. The data directory is specified by the dataDir parameter in the ZooKeeper configuration file , and the data log directory is specified by the dataLogDir parameter.
View solution in original post. You will need to stop zookeeper cluster for this. Do this as your last option, it's not a safe thing to do. Support Questions.
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