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HADOOP

Hadoop is for the most part for taking care of large information. Enormous information is unstructured information like log records, sounds, recordings, pictures, messages, books, archives, etc. In reality there are parcel of sources which are creating enormous information ordinary. The vast majority of the tasks from regarded customers require enormous information taking care of.

Length : 60 Hours

Introduction to HADOOP

What is Big Data?

What is Hadoop?

Challenges With Big Data

Comparison With Other Technologies

Components of Hadoop Echo System

HDFS

Significance of HDFS in Hadoop

Features of HDFS

Storage aspects of HDFS

HDFS Architecture

Accessing HDFS

MapReduce

Why MapReduce is essential in Hadoop

Processing Daemons of Hadoop

Input Split

Life Cycle

Data Types

Driver Code

Mapper Code

Reducer Code

Input Format in MapReduce

Output Format in MapReduce

MapReduce API

Combiner

Partitioner

Oozie

YARN

Hive

Pig

Hbase

Zookeeper

MySql

Sqoop

MongoDB

Scala

Spark

Hue