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1.0 Zookeeper Tutorial

Category Zookeeper Tutorial

ZooKeeper is a software project of the Apache Software Foundation, providing open-source distributed configuration services, synchronization services, and naming registration for large-scale distributed computing.

The architecture of ZooKeeper achieves high availability through redundant services.

The design goal of Zookeeper is to encapsulate complex and error-prone distributed consistency services into an efficient and reliable set of primitives, and provide them to users through a series of simple and easy-to-use interfaces.

A typical solution for distributed data consistency, distributed applications can use it to implement functions such as data publishing/subscription, load balancing, naming services, distributed coordination/notification, cluster management, master election, distributed locks, and distributed queues.

Who is this tutorial suitable for?

This tutorial is designed for professional programmers, through which you can understand the application of zookeeper step by step.

Zookeeper Data Structure

The namespace provided by zookeeper is very similar to a standard file system, storing in key-value format. The key name consists of a series of path elements separated by slashes /, and each node in the zookeeper namespace is identified by a path.

Related CAP Theory

-Consistency: In a distributed environment, consistency refers to the characteristic that data can be kept consistent across multiple replicas, equivalent to all nodes accessing the same latest data copy. Under the requirement of consistency, after a system performs an update operation in a consistent state, it should ensure that the system's data remains in a consistent state.

-Availability: Each request can get a correct response, but it does not guarantee that the data obtained is the latest.

-Partition Tolerance: A distributed system must ensure that it can provide services that meet consistency and availability even in the event of any network partition failure, unless the entire network environment has failed.

A distributed system can only meet two of the three requirements of consistency (Consistency), availability (Availability), and partition tolerance (Partition tolerance) at the same time.

Among these three basic needs, at most two can be satisfied simultaneously, and P is necessary, so the choice can only be between CP and AP. Zookeeper ensures CP, compared to the registration center eruka in the spring cloud system, which implements AP.

BASE Theory

BASE is an acronym for Basically Available (basically available), Soft-state (soft state), and Eventually Consistent (eventually consistent).

-Basically Available: In the event of a distributed system failure, it allows for partial availability loss (service degradation, page degradation).

-Soft State: Allows the distributed system to have an intermediate state. And this intermediate state does not affect the system's availability. The intermediate state here refers to the eventual consistency where data updates between different data replication nodes can be delayed.

-Eventually Consistent: Data replications achieve consistency after a period of time.

The BASE theory is a trade-off result between consistency and availability in CAP. The core idea of the theory is that we cannot achieve strong consistency, but each application can achieve eventual consistency according to its own business characteristics in an appropriate way.

Related Resources

Zookeeper Official Website: https://zookeeper.apache.org/

-2.0 Zookeeper Installation and Configuration

-3.0 Zookeeper Linux Server Cluster Setup Steps

-4.0 Zookeeper Java Client Setup

-5.0 ZooKeeper Data Model znode Structure Detailed

-6.0 Zookeeper session Basic Principles

-7.0 Zookeeper Client Basic Command Usage

-8.0 Zookeeper Four-Letter Commands

-9.0 Zookeeper Node Features

-10.0 Zookeeper Access Control ACL

-11.0 Zookeeper Watcher Event Mechanism Analysis

-12.0 Zookeeper Data Synchronization Process

-13.0 Zookeeper Leader Election Principles

-14.0 Zookeeper Distributed Lock Implementation Principles

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