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Bigdata Hadoop Training:

Course Introduction

Hadoop developer is one amongst the most demanded Hadoop roles in the market right now. Hadoop is still in demand due to its varied advantages like its cost effectiveness , performance , high availability, fault tolerancy capacity , low network traffic , etc. Hadoop accepts almost all forms of data and its serves as the best economical solution for most organizations. Hadoop processes bulk amount of data across multiple units /computers. It’s a technology which can process and store infinite number of data/tasks at the same time is HADOOP.

Course Name

Bigdata Hadoop

Course duration

40-50 Hrs

Faculty

Real time Expert

Category

Live Classes

Hadoop Course Content

Hadoop Online training-Complete Course Details HDFS and MAPREDUCE.

  • 4 V's of BIG DATA(IBM Definition of BIG DATA)
  • What is Hadoop?
  • Why Hadoop?
  • Core Components of Hadoop
  • Intro to HDFS and its Architecture
  • Difference b/w Code Locality and Data Locality
  • HDFS commands
  • Name Node’s Safe Mode
  • Different Modes of Hadoop
  • Intro to MAPREDUCE
  • Versions of HADOOP
  • What is Daemon?
  • Hadoop Daemons?
  • What is Name Node?
  • What is Data Node?
  • What is Secondary name Node?
  • What is Job Tracker?
  • What is Task Tracker?
  • What is Edge computer in Hadoop Cluster and Its role
  • Read/Write operations in HDFS
  • Complete Overview of Hadoop1.x and Its architecture
  • Rack awareness
  • Introduction to Block size
  • Introduction to Replication Factor(R.F)
  • Introduction to HeartBeat Signal/Pulse
  • Introduction to Block report
  • MAPREDUCE Architecture
  • What is Mapper phase?
  • What is shuffle and sort phase?
  • What is Reducer phase?
  • What is split?
  • Difference between Block and split
  • Intro to first Word Count program using MAPREDUCE
  • Different classes for running MAPREDUCE program using Java
  • Mapper class
  • Reducer Class and Its role
  • Driver class
  • Submitting the Word Count MAPREDUCE program
  • Going through the Jobs system output
  • Intro to Partitioner with example
  • Intro to Combiner with example
  • Intro to Counters and its types
  • Different types of counters
  • Different types of input/output formats in HADOOP
  • Use cases for HDFS & MapReduce programs using Java
  • Single Node cluster Installation
  • Multi Node cluster Installation
  • Introduction to Configuration files in Hadoop and Its Imp.
  • Complete Overview of Hadoop2.x and Its architecture
  • Introduction to YARN
  • Resource Manager
  • Node Manager
  • Application Master(AM)
  • Applications Manager(AsM)
  • Journal Nodes
  • Difference Between Hadoop1.x and Hadoop2.x
  • High Availability(HA)
  • Hadoop Federation

  • The difference between MAPREDUCE and PIG
  • When to go with MAPREDUCE?
  • When to go with PIG?
  • PIG data types
  • What is field in PIG?
  • What is tuple in PIG?
  • What is Bag in PIG?
  • Intro to Grunt shell?
  • Different modes in PIG
  • Local Mode
  • MAPREDUCE mode
  • Running PIG programs
  • PIG Script
  • Intro to PIG UDFs
  • Writing PIG UDF using Java
  • Registering PIG UDF
  • Running PIG UDF
  • Different types of UDFs in PIG
  • Word Count program using PIG script
  • Use cases for PIG scripts

  • Intro to HIVE
  • Why HIVE?
  • History of HIVE
  • Difference between PIG and HIVE
  • HIVE data types
  • Complex data types
  • What is Metastore and its importance?
  • Different types of tables in HIVE
  • Managed tables
  • External tables
  • Running HIVE queries
  • Intro to HIVE partitions
  • Intro to HIVE Buckets
  • How to perform the JOINS using HIVE queries
  • Intro to HIVE UDFs
  • Different types of UDFs in HIVE
  • Running HIVE queries for Word Count example
  • Use cases for HIVE

  • Intro to HBASE
  • Intro to NoSQL database
  • Sparse and dense Concept in RDBMS
  • Intro to columnar/column oriented database
  • Core architecture of HBase
  • Why Hbase?
  • HDFS vs HBase
  • Intro to Regions, Region server and Hmaster
  • Limitations of Hbase
  • Integration with Hive and Hbase
  • Hbase commands
  • Use cases for HBASE

  • Intro to Flume
  • Intro to Sink, Source, Flume Master and Flume agents
  • Importance of Flume agents
  • Live Demo on copying LOG DATA into HDFS

  • Intro to Sqoop
  • Importing and exporting the RDBMS into HDFS
  • Intro to incremental imports and its types
  • Use cases to import the Mysql data into HDFS

  • Intro to Zookeeper
  • Zookeeper operations

  • Intro to Oozie
  • What is Job.properties
  • What is workflow.xml
  • Scheduling the jobs in Oozie
  • Scheduling MapReduce, HIVE,PIG jobs/Programs using Oozie.
  • Setting up the VMware for Hadoop
  • Installing all Hadoop Components
  • Intro to Hadoop Distributions
  • Intro to Cloudera and its major components

  • What is Spark Ecosystem
  • What is Scala and its utility in Spark
  • What is SparkContext
  • How to work on RDD in Spark
  • How to run a Spark Cluster
  • Comparison of MapReduce vs Spark

  • Tableau Fundamentals
  • Tableau Analytics
  • Visual Analytics
  • Connecting
  • Hadoop Integration with Tableau

  • Proficient understanding of code versioning tools such as Git

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FAQ’s:

Annual salary of an Hadoop developer is around 6 lakhs and it varies based on the experience of the individuals.

Their has been a lot of investment going on in the big data industry which has lead to increase job opportunities in Hadoop/Big Data industry .From a business point of view as well the use of Hadoop shall rise.

IT Tuition have tie ups and references of few MNC’s with which we assist you to work on a real time project. Any difficulties faced working on the project will be resolved by our trainers.

Few advantages of taking the training from our institute IT Tuition are : Live Online demo sessions with an overview of the course; Soft copies of the training materials; Videos of all the sessions taken online;Real time project scenarios ; To do list after every training session ; Repeat training sessions if any doubts are need to be clarified.

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