Analysis of the Hadoop Architecture, Modules, and Components, As Well as Knowledge of Its Potential and Restrictions

Abstract

Big data sets can range in size from gigabytes to petabytes, and Hadoop is an open source framework used to store them. Unlike Hadoop architecture, which makes it possible to cluster data sets so that multiple datasets can be evaluated concurrently without interfering with one another, traditional methods of data storage will store the data in one large computer as a result of which only one data set can be analysed at a given point in time. In comparison to other data storage techniques, Hadoop processes data more quickly and provides quick responses. Additionally, the Hadoop architecture offers building blocks on which other services and applications may be developed. Spark, Hive, Presto, Hbase, and other popular Hadoop applications are listed here. In Hadoop.