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Table of contents
1.
Introduction
2.
Need of Zookeeper
2.1.
Capabilities of Zookeeper
3.
Benefits of ZooKeeper
4.
Limitations of Zookeeper
5.
Frequently Asked Questions
5.1.
Name a few Hadoop-using companies.
5.2.
What data is stored in ZooKeeper?
5.3.
What do you understand by the term "Big data"?
5.4.
What is Hadoop and its components?
6.
Conclusion
Last Updated: Mar 27, 2024
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Zookeeper

Author SHIVANGI MALL
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Introduction

The ZooKeeper framework was created by "Yahoo!" to make it easy and reliable to access their apps. Later, HadoopHBase, and other distributed frameworks adopted Apache ZooKeeper as a standard for organized services. ZooKeeper, for example, is used by Apache HBase to track the status of distributed data.

ZooKeeper is a service that allows you to manage a large number of servers in a distributed manner. In a distributed context, coordinating and managing a service is a difficult task. With its simple architecture and API, ZooKeeper overcomes this problem. ZooKeeper allows developers to concentrate on the fundamental logic of their applications without having to worry about the application's distributed nature.

This tutorial covers the fundamentals of ZooKeeper, the need for Zookeeper, benefits and limitations of Zookeeper.

Need of Zookeeper

Hadoop's capacity to divide and conquer is its most potent tool for dealing with huge data problems. After the problem has been separated, the solution is based on the Hadoop cluster's capacity to use distributed and parallel processing techniques. Interactive technologies are unable to give the insights or timeliness required to make business decisions for some large data challenges.

To overcome those huge data problems, you'll need to design distributed applications. Zookeeper is Hadoop's method of coordinating all of these distributed applications' pieces.

Although Zookeeper is a simple technology, its functions are really powerful. It is arguable that creating resilient, fault-tolerant distributed Hadoop applications without it would be difficult, if not impossible.

Capabilities of Zookeeper

● Configuration management

Zookeeper can broadcast configuration attributes to any or all of the cluster's nodes. When processing relies on specific resources being available on all nodes, Zookeeper ensures that the configurations are consistent.

● Process synchronization

Zookeeper is in charge of coordinating the start and stop of several nodes in a cluster. This ensures that everything happens in the correct order. Only after an entire process group has been completed can subsequent processing begin.

● Self-election

Zookeeper is aware of the cluster's composition and can assign a "leader" role to one of the nodes. On behalf of the cluster, this leader/master handles all client requests. Should the leader node fail, the surviving nodes will elect a new leader.

● Cluster management

Joining and exiting a cluster, as well as node status in real-time.

● Reliable messaging

Even though Zookeeper workloads are loosely coupled, the distributed application still requires communication between and among the nodes in the cluster. Zookeeper has a publish/subscribe feature that allows you to create a queue. Even if a node fails, this queue ensures that messages are delivered.

Zookeeper is ideally implemented across racks since it manages groups of nodes in service of a single distributed application. This differs significantly from the cluster's requirements (within racks). The rationale for this is straightforward: Zookeeper must perform, be durable, and be fault-tolerant at a level above the cluster. It's important to remember that a Hadoop cluster is already fault resilient and will self-heal. The only thing a zookeeper has to worry about is its own fault tolerance. 

The Hadoop ecosystem, as well as the commercial distributions that are supported, are constantly evolving. Existing technologies are upgraded, while some technologies are discarded in favor of a (hopefully better) replacement. One of the most significant advantages of open source is this. Another example is commercial enterprises' embrace of open source technologies. These businesses improve products and make them better for everyone by providing low-cost support and services. This is how the Hadoop ecosystem has grown and why it's a suitable fit for tackling your big data problems.

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Benefits of ZooKeeper

ZooKeeper has an interface and services that are very easy to use. Below are some of the most important advantages provided by ZooKeeper:

● Reliability

ZooKeeper is replicated across a group of hosts (referred to as an ensemble), and the servers are aware of one another. The ZooKeeper service will be available as long as a critical mass of servers is available. There isn't a single point of failure in this system.

● Fast

With workloads where reads to the data are more common than writes, Zookeeper is extremely fast. About a 10:1 read/write ratio is optimum.

● Simple

Like files and directories, ZooKeeper uses a standard hierarchical namespace.

● Ordered Message

Zookeeper keeps track of each communication with a number, which denotes its order with the stamping of each update.

● Atomicity

No data transfer is partial; it either succeeds or fails entirely.

● Synchronization

Server processes must mutually exclude and cooperate. This procedure aids configuration management in Apache HBase.

 

Must Read Apache Server

Limitations of Zookeeper

Because every coin has two sides, there are a few negatives to Zookeeper after all of its benefits. So, here is a list of some of Zookeeper's drawbacks:

● Adding new zookeeper servers can lead to data loss

Data Loss occurs on existing servers when the number of new ZooKeeper servers surpasses the number of ZooKeeper servers already in use. At the same time, the ZooKeeper service is started, allowing the new servers to form a quorum.

● No migration

The ZooKeeper server cannot be downgraded from version 3.4 to 3.3 and then back to 3.4 without human intervention.

● Limited support

Cross-cluster scenarios have such little support. No CP system, however, willfully handles cross-cluster communication. Though we can say that the consul appears to be better at it.

● Virtual networks

When a service is launched on a virtual network, it may not be possible to move to host networking without a complete re-installation. Additionally, the identical issue arises when attempting to move from host to virtual networking.

● Complex

ZooKeeper is not for the faint of heart. Because it is quite hefty, we will need to keep a fairly large stack on hand.

Frequently Asked Questions

Name a few Hadoop-using companies.

Some of the companies that use Hadoop are:-
Facebook
Netflix
Amazon
Adobe
eBay
Hulu
Spotify

What data is stored in ZooKeeper?

ZooKeeper was created to keep coordination data such as status, configuration, and location, the data saved at each node is often minimal, ranging from a few bytes to a few kilobytes. To be clear about what we're talking about, ZooKeeper data nodes, we use the term znode.

 

What do you understand by the term "Big data"?

The term "big data" refers to a collection of massive and complicated data sets that are difficult to analyze using typical data processing software or relational database management technologies. Capturing, curating, storing, searching, sharing, transferring, analyzing, and visualizing Big data is complex. Big Data has arisen as a business prospect.

 

What is Hadoop and its components?

When the term "Big Data" became a concern, Apache Hadoop arose as a solution. Apache Hadoop is a platform that offers a variety of services and tools for storing and processing large amounts of data. It aids in the analysis of Big Data and the making of business decisions that can't be done as efficiently and effectively with traditional methods.

Conclusion

In this article, we have extensively discussed the Zookeeper, the need for the Zookeeper, benefits, and limitations of Zookeeper in detail. We hope this blog has helped you enhance your knowledge regarding Zookeeper. And if you would like to learn more, check out our articles on Big Data,Cloud, Hadoop,  and Databases. Do upvote our blog to help other ninjas grow.

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