Hadoop is an open source software platform designed to store and process large amounts of data on computer clusters. The inspiration for the creation of the platform was Google’s MapReduce, a software framework that splits applications into many small parts, each of which can be launched or re—launched on any node in the cluster.

The platform allows you to scale from one server to thousands of machines, each of which provides local computing and data storage. Hadoop uses data replication to store multiple copies of data blocks on different nodes, which allows data to be automatically restored in case of failures or loss of node availability.

The main components of Hadoop

  • Hadoop Distributed File System (HDFS) is a component of Hadoop designed to store large amounts of data and provide access to them. HDFS divides data into blocks and distributes them to nodes in the cluster, providing fault tolerance and parallel data processing.
  • MapReduce is a model of programming and data processing in Hadoop. It allows you to split the data processing task into small parts (map) and then collect the results (reduce) on each node of the cluster.
  • Hadoop YARN is a component of Hadoop that manages the resources of systems that store data and perform analysis. YARN allows you to manage computing resources in a cluster and place tasks on available nodes.
  • Hadoop Common is a Hadoop module that includes various utilities and libraries necessary to support the operation of other Hadoop components. Hadoop Common provides common functionality for the entire platform.
  • Hadoop Streaming is an approach in Hadoop that allows you to use any programming language to write MapReduce tasks. It provides flexibility in the choice of programming language and simplifies the integration of existing code and the expansion of Hadoop capabilities.

Comparing Hadoop with traditional databases
Hadoop can store any type of data, structured and unstructured, and scale to petabytes of data. Traditional databases, on the other hand, require structured data and have storage limitations.

Examples of using Hadoop
Hadoop is used in various industries. For example, social media platforms such as Facebook and Twitter can use Hadoop to store and process huge amounts of data. E-commerce giants such as Amazon and Alibaba use the platform to create product recommendation systems, fraud detection, and customer research.

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