Big Data using Hadoop Hands-On Workshop

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Thane, Mumbai

Course ID: 29516

Thane, Mumbai

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TS picture
TS

M.E. (Computers)

12 Years of Experience

About TS

TS is a Big Data Enthusiast with 14+ years of training experience in BI and Big Data arena. He is a passionate trainer and has trained 10000+ professionals till date.

His average training feedback is 4.5.
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About the Course

Gone are the days when we were talking about Gigabytes and Terabytes of data.  With the increase in the usage of Social Media, Sensors, e-commerce etc., we have reached an era of petabytes and exabytes of data. 


Join this course and be an early adopter of Big Data and its related technologies.


High Level Course Outline



  • · Why Big Data

  • · Sources of Big Data

  • · Characteristics of Big Data

  • · Big Data â?? Use Cases

  • · Solutions so far and pitfalls

  • · Design Considerations of Hadoop

  • · Hadoop and its architecture (Detailed)

  • · HDFS & MapReduce

  • · Hadoop Components and daemons

  • · Understanding Block Size, Replication, and Heart Beat with scenarios.

  • · Hadoop in Implementation

  • · Hadoop Files for Implementation

  • · Modes to set-up Hadoop Cluster

  • · Hands On: Setting up a Hadoop Cluster and understanding different  daemons

  • · Hands On: Writing Files to HDFS

  • · Hands On: Reading Files from HDFS

  • · Hands On: Hadoop commands

  • · Hands On: Few Hadoop Admin Commands

  • · Understanding MapReduce

  • · Case Study: Thinking in terms of MapReduce Key Value Pairs

  • · Hands On: Running MapReduce Job

  • · Hands On: Creating MapReduce Programs and executing it

  •     Advanced MapReduce - Combiner, Custom Practitioner, Counters, Distributed Cache, Joins, Chain Mapper, Chain Reducer

  • · Pig

  • · Why Pig

  • · Hands On: Configuring Pig

  • · Hands On: Creating and Executing Pig Scripts

  • · Hive and HiveQL

  • · Why Hive

  • · Hands On: Configuring

  •  Understanding Hadoop Ecosystem: Pig, Hive, Sqoop, Mahout, HBase, Zookeeper, Oozie etc

  • Sqoop

  • Hands On: Sqoop

  • Flume

  • Hands On: Flume


 

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