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A Complete PDF Guide to Hadoop Big Data Analytics

Hadoop is an open-source framework for storing data and running applications on clusters of commodity hardware. It is a distributed processing technology that provides expansive data storage facility and handles thousands of terabytes of data and rapid data transfer among nodes.


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Eshika Singh

a year ago | 1 min read

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Hadoop is an open-source framework for storing data and running applications on clusters of commodity hardware. It is a distributed processing technology that provides expansive data storage facility and handles thousands of terabytes of data and rapid data transfer among nodes. Hadoop is extensively used in big data analytics, including scientific analytics, business and sales development, and enormous volumes of data processing. Hadoop provides excellent flexibility to enterprises and enables the companies to access and process data easily.

It's at the center of an ecosystem of big data technologies that are primarily used to support advanced analytics initiatives, including predictive analytics, data mining and machine learning. Hadoop systems can handle various forms of structured and unstructured data, giving users more flexibility for collecting, processing, analyzing and managing data than relational databases and data warehouses provide.

How Hadoop Works

Hadoop makes it easier to use all the storage and processing capacity in cluster servers, and to execute distributed processes against huge amounts of data. Hadoop provides the building blocks on which other services and applications can be built.

Applications that collect data in various formats can place data into the Hadoop cluster by using an API operation to connect to the NameNode. The NameNode tracks the file directory structure and placement of “chunks” for each file, replicated across DataNodes. To run a job to query the data, provide a MapReduce job made up of many map and reduce tasks that run against the data in HDFS spread across the DataNodes. Map tasks run on each node against the input files supplied, and reducers run to aggregate and organize the final output.

Why Hadoop used for Big Data Analytics?

Big data analytics is the process of examining large data sets to uncover hidden patterns, unknown correlations, market trends, customer preferences and other useful business information.

Hadoop is a framework to store and process big data. Hadoop specifically designed to provide distributed storage and parallel data processing that big data requires.

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