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Bigdata Hadoop Online Training

We are ruled by the world of data. They have become an integral part of life. These data has to be stored somewhere so that we can extract them whenever required. An open-source software is generally free and one can download them without involving any cost. Hadoop is an open source software framework which is used to store data and run applications on hardware. It has the capacity to store huge amount of data without any error. The processing power is very high. The traditional databases can take up only the pre-processed data for storage.The best advantage of using Hadoop is that it gives the power to store unstructured data without any complications.

Hadoop works on the concept of nodes. Higher the nodes, better is the processing capacity. When one node fails, the data is automatically transferred to other nodes. This ensures that the data is safe all the times. The cost involved is less as it is a free downloadable software. And guess what, you do not have to constantly monitor it. The administration required is very less.

Hadoop Administration

Hadoop is an open source Content Management Software that has high capacity to store the data. It has the ability to run multiple projects simultaneously with enormous processing power capacity. LearningSlot has the real time trainers who can share the best industry knowledge to make you the finest Hadoop developer.

Learning Slot assures you the better way of learning Hadoop technology by applying its immense training technology on Big data hadoop online training to help its students. Join and get access to the world class IT online trainings anytime anywhere.

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Course Objectives

1. BigData

  • What is BigData
  • Characterstics of BigData
  • Problems with BigData
  • Handling BigData

2. Distributed Systems

  • Introduction to Distributed Systems
  • Problems with Existing Distributed Systems to deal BigData
  • Requirements of NewApprocach
  • HADOOP history

3. HADOOP Core Concepts

  • HDFS
  • MapReduce
  • Master the concepts of Hadoop Distributed File System
  • The Five Deamons working
    • NameNode
    • JobTracker
    • SecondaryNameNode
    • TaskTracker
    • DataNode

4.Introduction to HADOOP EcoSystem projects

  • Setup a Hadoop Cluster
  • Install Pseudo cluster
  • Install Multi node cluster

5.Write MapReduce Code in Java 

  • Understanding HADOOP API
  • Basic programs of HADOOP MapReduce ApplicationForm
    • Driver Code
    • Mapper Code
    • SecondaryNameNode
    • Reducer Code
  • Eclipse intigration with HADOOP for Rapid Application Development


6.Understanding ToolRunner

  • More about ToolRunner 
  • RecordReader
  • Combiner
  • Reducer
  • configure and close methods 

7.Common MapReduce Algorithems

  •     Sorting 
  •   Searching
  •   Indexing
  •   TF-IDF
  • Word_Co-Occurance 

8. Perform Data Analytics using Pig and Hive 

  • Hive 
  • Introduction to hive
  • Creating tables in hive
  • Running queries
  • Pig 
  • Introduction to pig 
  • Different modes of pig 
  • When to use hive and when to use pig 

9. Understand Data Loading Techniques using Sqoop and Flume 

  • Sqoop 
  • Importing data from RDBMS using sqoop

10. Implement HBase, MapReduce Integration

11.Use Apache Oozie to Schedule and Manage Hadoop Jobs 

12.Implement best Practices for Hadoop Development and Debugging 

13.Develop a working Hadoop Architecture 

14.Work on a Real Life Project on Big Data Analytics and gain Hands on Project Experience

15.Hands ons Exercise for each concept

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