Creating a znode is as easy as specifying the path and the contents. You can then read the contents of these znodes with the get command. The data contained in the znode is printed on the first line, and metadata is listed afterwards most of the metadata in these examples has been replaced with the textfor brevity.
You can, of course, modify znodes after you create them. Notice that the dataVersion values have been modified as well as the modified timestamp — other metadata has been omitted for brevity. You can also delete znodes. There is an rmr command that will do this for you. In addition to the standard znode type, there are two special types of znode: sequential and ephemeral.
You can create these by passing the -s and -e flags to the create command, respectively. You can also apply both types to a znode. Sequential nodes will be created with a numerical suffix appended to the specified name, and ZooKeeper guarantees that two nodes created concurrently will not be given the same number. Note that the numbering is based on previous children that have had the same parent — so the first sequential node we created was actually 2.
This feature allows you to create distributed mutexes. If a client wants to hold the mutex, it creates a sequential node. If it is then the lowest number znode with that name, it holds the lock. If not, it waits. To release the mutex, it deletes the node, allowing the next znode in order to hold the lock. You can implement a very simple master election system by making sequential znodes ephemeral.
Ephemeral nodes are automatically deleted when the client that created them disconnects which means that ZooKeeper can also help you with failure detection — another hard problem in distributed systems. Clients can disconnect intentionally when they shut down, or they can be considered disconnected by the cluster because the client exceeded the configured timeout without sending a heartbeat.
If the machine crashes, or the JVM pauses too long for garbage collection, the ephemeral node is deleted and the next eligible node can assume its place.
Modify the same znode either from the current ZooKeeper client or a separate one , and you will see the following message written to the terminal:. Note that watches fire only once. If you want to be notified of changes in the future, you must reset the watch each time it fires.
Watches allow you to use ZooKeeper to implement asynchronous, event-based systems and to notify nodes when their local copies of the data in ZooKeeper is stale.
If you look at the metadata listed in previous commands, you will see items that are common in many file systems and features that have been discussed above: creation time, modification time and corresponding transaction IDs , the size of the contents in bytes, and the creator of the node if ephemeral.
You will also see some metadata for features that help safeguard the integrity and security of the data: data versioning and ACLs. For example:. The current version of the data is provided every time you read or write to it, and it can also be specified as part of a write command a test-and-set operation.
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. These can be used to [tbd]. ZooKeeper is very fast and very simple. Since its goal, though, is to be a basis for the construction of more complicated services, such as synchronization, it provides a set of guarantees. These are:. One of the design goals of ZooKeeper is providing a very simple programming interface.
As a result, it supports only these operations:. For a more in-depth discussion on these, and how they can be used to implement higher level operations, please refer to [tbd]. ZooKeeper Components shows the high-level components of the ZooKeeper service. With the exception of the request processor, each of the servers that make up the ZooKeeper service replicates its own copy of each of the components.
The replicated database is an in-memory database containing the entire data tree. Updates are logged to disk for recoverability, and writes are serialized to disk before they are applied to the in-memory database. Every ZooKeeper server services clients.
Clients connect to exactly one server to submit requests. Read requests are serviced from the local replica of each server database. Requests that change the state of the service, write requests, are processed by an agreement protocol. As part of the agreement protocol all write requests from clients are forwarded to a single server, called the leader. The rest of the ZooKeeper servers, called followers , receive message proposals from the leader and agree upon message delivery. The messaging layer takes care of replacing leaders on failures and syncing followers with leaders.
ZooKeeper uses a custom atomic messaging protocol. Since the messaging layer is atomic, ZooKeeper can guarantee that the local replicas never diverge. When the leader receives a write request, it calculates what the state of the system is when the write is to be applied and transforms this into a transaction that captures this new state. The programming interface to ZooKeeper is deliberately simple. With it, however, you can implement higher order operations, such as synchronizations primitives, group membership, ownership, etc.
Some distributed applications have used it to: [tbd: add uses from white paper and video presentation. ZooKeeper is designed to be highly performance. But is it? The results of the ZooKeeper's development team at Yahoo! Research indicate that it is. It is especially high performance in applications where reads outnumber writes, since writes involve synchronizing the state of all servers.
Reads outnumbering writes is typically the case for a coordination service. One drive was used as a dedicated ZooKeeper log device.
The snapshots were written to the OS drive. Write requests were 1K writes and the reads were 1K reads. Approximately 30 other servers were used to simulate the clients. The ZooKeeper ensemble was configured such that leaders do not allow connections from clients. In version 3. Benchmarks also indicate that it is reliable, too. Reliability in the Presence of Errors shows how a deployment responds to various failures. The events marked in the figure are the following:.
To show the behavior of the system over time as failures are injected we ran a ZooKeeper service made up of 7 machines.
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