Features and components of Hadoop

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Features and components of Hadoop

Hi Guys,

I am learning Hadoop and just started with the Big Data basic details. I Found Hadoop is most popular Big Data platform and I want to learn Hadoop in very detail.

So, I want to know the Features and components of Hadoop to learn each component with example codes.

Can anyone explain me these concepts step by step so that I can start learning Hadoop and its components one by one in correct order.

Thanks

View Answers

March 18, 2018 at 1:20 AM

Hi,

You are right Hadoop is one of the top used Big Data platforms and even Microsoft is using Hadoop in their HDInsight platform. Horntonworks Hadoop distribution is used by Microsoft and it come with the Ambari interface for cluster installation and management.

Hadoop Big Data Platform

Hadoop platform comes with many Hadoop eco-system software which allows the developers to create data ingestion, cleansing, processing and analysis programs which can be executed on the nodes in the cluster. Hadoop jobs runs in parallel on different nodes in the cluster which makes processing very fast. Hadoop horizontally scalable which means you can add more servers to increase power of your cluster. New servers and components can be added without restart of the whole cluster.

Features of Hadoop

Hadoop is distributed file system and processing framework which can be installed on the 1000s of commodity servers to handle large volume of data at very high speed. It allows the developers to write programs using various Hadoop API to interact, process and analyze vast set of data.

HDFS - Distributed file system

Hadoop provides its file system known as Hadoop File System (HSFS for short) which can handle both structured and instuctured data in distribute environment. HDFS is highly scalable and new hardware can be added to increase storage and processing capacity to the system.

Distributed Processing

Hadoop provides MapReduce jobs which is executed over the nodes in the cluster in parallel fashion. More importantly execution program is sent to the cluster node where data resides which helps in reducing the network traffic and increases performance of the system. Hadoop is designed to runs the jobs in fault tolerant way, which means if any node fails while job is running then the failed part of job is executed using another node in the cluster.

Hadoop eco-system software

There are many parallel projects which is under development and Apache software foundation to support Hadoop environment. These software components are collectively known as Hadoop Eco-system components. These software packages includes Spark, Hive, Sqoop, HBase and many other which can be used to develop applications in Big Data environment.

Check tutorials at:

Thanks

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