Apache Hadoop Architecture

Apache Hadoop, often just called Hadoop, is a powerful open-source framework built to process and store massive datasets by distributing them across clusters of affordable, commodity hardware. Its strength lies in scalability and flexibility, enabling it to work with both structured and unstructured data.

The Hadoop Distributed File System HDFS is a distributed file system designed to run on commodity hardware. It has many similarities with existing distributed file systems. However, the differences from other distributed file systems are significant.

HDFS has a masterslave architecture. An HDFS cluster consists of a single NameNode, a master server that manages the file system namespace and regulates access to files by clients. In addition, there are a number of DataNodes, usually one per node in the cluster, which manage storage attached to the nodes that they run on.

Apache Hadoop includes two core components the Apache Hadoop Distributed File System HDFS that provides storage, and Apache Hadoop Yet Another Resource Negotiator YARN that provides processing. With storage and processing capabilities, a cluster becomes capable of running MapReduce programs to perform the desired data processing.

The architecture of Apache Hadoop is based on a simple yet powerful model that allows for distributed computing. It consists of several key components that work collaboratively 1. Hadoop Distributed File System HDFS HDFS is the primary storage system of Hadoop, designed to store massive files across multiple machines. It splits large files

Apache Hadoop. The Apache Hadoop project develops open-source software for reliable, scalable, distributed computing. The Apache Hadoop software library is a framework that allows for the distributed processing of large data sets across clusters of computers using simple programming models. It is designed to scale up from single servers to

This article explores the architecture of the Hadoop framework and discusses each component of the Hadoop architecture in detail. But before that, let's understand what exactly the Hadoop framework is. What is Hadoop? Hadoop, also known as Apache Hadoop, is an open-source big data processing framework.

Apache Hadoop is a popular big data framework that allows organizations to store, process, and analyze vast amounts of data. architecture of Hadoop is designed to handle large amounts of data by using distributed storage and processing. In this article, we will explain architecture of Apache Hadoop and its various components with diagrams.

A large Hadoop cluster is consists of so many Racks . with the help of this Racks information Namenode chooses the closest Datanode to achieve the maximum performance while performing the readwrite information which reduces the Network Traffic. HDFS Architecture . 3. YARNYet Another Resource Negotiator YARN is a Framework on which MapReduce

Apache Hadoop Architecture Explained with Diagrams By. Vladimir Kaplarevic. Published May 25, 2020. Topics big data, hadoop. Apache Hadoop is an exceptionally successful framework that manages to solve the many challenges posed by big data. This efficient solution distributes storage and processing power across thousands of nodes within a