The master comprises of Namenode and Job Tracker components.Some Hadoop-related projects at Apache are HBase, Hive, Sqoop Mahout, ZooKeeper, and Flume. Even though Hadoop is considered for MapReduce and its distributed file system- HDFS, it is also used for similar projects that falls under large-scale data processing and distributed computing.This component is responsible for delivering all the computations and operates by breaking down a large complex computation into various tasks and assigning those to individual slave or worker nodes and looks after consolidation and coordination of results. MapReduce presents an analysis system that can deliver complex computations on large datasets.
It guarantees high availability and fault tolerance. Unlike the other regular file systems, when data is pushed to HDFS, it will automatically split into multiple blocks (configurable parameter) and store/replicates the data across various datanodes.
Hadoop Distributed File System (HDFS) grants an extremely secure and distributed storage, and guarantees reliability, even on commodity hardware, by replicating the data across numerous nodes. Hadoop has 2 major components: HDFS and MapReduce. Hadoop operates in a master-worker or master-slave fashion. Let’s look at some of the few spotlights of the Hadoop Architecture: Mentioned below is an advanced architecture of the multi-node Hadoop Cluster. Such a program processes data stored in Hadoop HDFS. This computational logic is a consolidated variant of a program written in a high-level language like Java. The processing model is devised on the concept of ‘Data Locality’, where computational logic is sent to cluster nodes(server) containing data. In Hadoop, data resides in a distributed file system, which is known as a Hadoop Distributed File system, which is quite similar to data residing in a local file system of a personal computer system. These are chiefly beneficial for obtaining greater computational power at a low cost. Commodity computers are affordable and are available widely. Hadoop implements a secure shared storage and analysis system.Īpplications developed using Hadoop are operated on large data sets spread across groups of commodity computers. Hadoop is an open-source framework, from the Apache foundation, proficient in processing huge chunks of heterogeneous data sets in a distributed manner across groups of commodity computers and hardware employing a simplified programming model. This article talks explicitly about the features of Hadoop. 
If you have ever pondered what Hadoop is and why is it so popular, then you have come to the right place. Hadoop has become a well-known term and is quite renowned in today’s digital world.
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