• $499.00 $399.00
  • 25 Days
  • 20 SEATS
345 STUDENTS ENROLLED

    Contact Information

    Email : training@learnfromguru.com
    Phone : 408 - 657 – 4159

    LearnFromGuru’s Hadoop Training, will introduce to the participants to explore the master of Hadoop concepts and services.

    Participants will be offered guidance and will share lot of demo’s on each topic with real time examples.

    Participants will also get to implement one project towards the end of the course.

    After the completion of the Hadoop Developer course at LearnFromGuru, you will be able to:
    a) What is Bigdata
    b) Why Bigdata is needed
    c) Bigdata characteristics
    d) How to store and process Bigdata
    e) What is Hadoop
    f) Why Hadoop
    g) Hadoop history
    h) Software and hardware requirements for Hadoop
    i) Hadoop real time use case
    j) Major Components of Hadoop ? Hadoop ecosystem projects
    k) Scope of Hadoop
    l) Hadoop distributions
    M) Hadoop installation modes

    Anyone who has a good understanding of any java can join this program.

    1)Hadoop Distributed File System (HDFS) 

    • Introduction to HDFS
      Why HDFS
      HDFS Commands
      Regular File system Vs Hadoop distributed file system
      HDFS Master/slave architecture
      Daemons in Hadoop
      HDFS concepts like blocks, Name node, Secondary name node, data node
      HDFS File reads
      HDFS File writes
      Fault Tolerance
      Details on Network topologies like nodes, clusters and racks.
      Details about heartbeat?
      Details on rack awareness file
      HDFS Federation
      High Availability of Name node
      Hadoop Archive files
      Distcp usage
      Assignment and Interview Questions on HDFS module

    2)MapReduce

    • Introduction to MapReduce framework
    • MapReduce Architecture
    • MapReduce execution phases
    • Details on input splits, mappers, shuffle sort and reducers
    • Eclipse plug in installation ? My first map reduce program
    • Depth knowledge about Combiners
    • Details on Tool runner
    • Partitioner
    • Real time use cases to write MapReduce programs

    3) Advanced MapReduce 

    • Counters
    • Real time use case on Counters
    • Secondary Sorting
    • Map side joins
    • Reducer side joins
    • Classic MapReduce and Yarn
    • Details on resource Manager, Application Master, Node Manager and Container
    • Performance Tuning features
    • Hadoop Streaming
    • Hadoop Pipes
    • File Input /Output Formats in MapReduce
    • Distributed cache
    • Assignment and Interview Questions on MapReduce and advance MapReduce

    4)Hive 

    • Introduction to Hive
    • Hive Architecture
    • Difference between HQL and SQL
    • Installation of Hive
    • Depth knowledge on Managed Tables and External Tables
    • Hive Data types
    • Hive Create, Alter and drop tables
    • Hive Multi table inserts
    • Partitions in Hive with real time example
    • Bucketing in Hive with real time example
    • Hive storage formats
    • Joins in hive
    • Hive Indexes
    • Hive Views
    • Hive UDF
    • Assignment and Interview Questions on Hive.

    5)Pig

    • Introduction to Pig
    • Details on pig data flow engine
    • MapReduce Vs Hive Vs Pig
    • When to use Pig
    • Datatypes in Pig
    • Modes of execution in Pig
    • Pig programming
    • Pig Execution models
    • Operators in Pig
    • Pig UDF
    • Assignment and Interview Questions on PIG.

    6)HBASE 

    • Introduction to HBASE
    • Basic Configurations of HBASE
    • Fundamentals of HBase
    • HBase Data Model
    • HBASE Architecture
    • SQL vs. NOSQL
    • DFS vs. HBase
    • Client-side buffering or bulk uploads
    • HBase Operations
    • Assignment and Interview Questions on HBase.

    7) Sqoop 

    •  Introduction to Sqoop
    • Sqoop and sqoop2 architectural differences
    • Sqoop Import
    • Sqoop Incremental Import
    • Sqoop Import-all
    • Sqoop Export
    • Sqoop Jobs
    • Real time Example of Import/export from RDBMS (MySQL) to Hadoop

    8)Flume 

    •  Introduction to Flume
    • Architecture of Flume
    • Depth on Flume agents
    • Real time Data ingestion from Twitter to Hadoop using flume
    • Assignment and Interview Questions 

     

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