Hadoop Ecosystem Tutorial

Meaning of Hadoop Ecosystem:

Hadoop ecosystem is not a service and programming, Hadoop ecosystem is the one type of platform which used to process a large amount of Hadoop Data.Hadoop ecosystem using HDFS and MapReduce for Storing and processing a large amount of data and also used Hive for querying the data.Hadoop Ecosystem consists of following three different types of data

Structured Data – Data having clear structure which can be stored in tabular form

Semi-Structured Data – Data having some structure which cannot be stored in tabular form

UnStructured Data – Data does not have any structure which cannot be stored data in tabular form

Storage Layer of Hadoop Ecosystem:

  • In Hadoop Ecosystem uses an HDFS for stores a large amount of data that stored file system is running on Hadoop cluster machines.
  • HDFS stores the three types of data like Structured, Semi-Structured and unstructured.
  • Hadoop cluster adding nodes to the cluster. If adding more nodes the cluster is having a large number of datasets.

Computation Layer of Hadoop Ecosystem:

  • In Hadoop Ecosystem uses a MapReduce for Processing a large amount of data set in the form of key /value pair.
  • MapReduce is the one type of Programming that program applied to Structured, Semi-Structured and unstructured data in Hadoop.
  • Uses of Key/Value pair is mapping the element and it acts as an identifier.

Main Components of Hadoop Ecosystem:

Hadoop Ecosystem Tutorial

1.Data Transfer Components: 


  • Sqoop is one type of tools and used to transfer a large amount of data between Hadoop from RDBMS to HDFS.
  • It is export and import data from data stores to HDFS
  • It uses a MapReduce for export the data for processing the large amount of data


  • Flume is one type of tool and it gets data from online server which placed on HDFS
  • Flume get data from log file and convert that data to Hadoop format
  • Main purposes of flume are collecting the data and moving huge amount of data.
  • Flume also knew as log collector

PDF Download – Advanced Hadoop Training Topics

2.Application Programming Components: 


  • Main Purposes of Hive is querying and analyze the data from HDFS.
  • Hive deals unstructured data with query language and it is similar to SQL.
  • It runs on MapReduce and processing backend data in HDFS.
  • It processing SQL language so Hive also called HiveQL
  • It is a data warehousing infrastructure and build on top of the Hadoop
  • It has three functions: Data summarization, Querying and Analysis


  • Pig is the one type of tool and it is used to analyze the large amount of data that runs on HDFS
  • Scripting Language of Pig is Pig Latin.
  • Pig Performs Data Manipulations and it is similar to SQL.
  • Pig converts all the tasks at Map and Reduce tasks and that tasks are run in Hadoop.
  • It deals structured data only using pig latin.

3.Data Storage Components: 


  • HBase is a NoSQL database and it runs on top of the HDFS.
  • Main Purpose of HBase is read and write a large number of datasets.
  • HBase stores the data in rows and columns.
  • Hbase programming written in only Java.
  • HBase does not support Structured Query Language.
  • It stores the column-oriented database in Hadoop

4.Analysis Components: 


  • Mahout is an open source machine learning and it is written in Java Program.
  • Mahout used by data scientist to do machine learning
  • Mahout helps to write machine learning algorithm and used to big data analytics
  • Some machine learning techniques are Clustering, Recommendation, and clustering

5.Workflow Management: 


  • It mainly used to implement the java web application program.
  • It also manages the Hadoop jobs.
  • Oozie combines the multiple jobs and that runs in sequential order to achieve big task
  • In Oozie one or more jobs are programmed at a time
  • It has three types of a job such as Workflow jobs, Coordinators jobs, and Bundle jobs.

6.Administration and Coordinates Components: 


  • Ambari Maintained by the administrator of the system and it is an open source framework.
  • It has many administration tools for installing, maintaining and monitoring the Hadoop cluster


  • It is also called as an administrative interface.
  • It has GUI tool for handling pig and hive query and also used to browsing files and Oozieworkflows.

Zoo Keeper: 

  • ZooKeeper is an open source mechanism and perform a synchronization between Hadoop tools and components
  • Main services of ZooKeeper is configuration and synchronization used by the distributed application.