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Hadoop

Bigdata Hadoop and a supporting ecosystem of complementing technologies, building blocks, and implementation frameworks today provide one of the most powerful, mature, and compelling answers to problems in this domain. The true power of the Hadoop stack lies in it being a complete solution covering the entire lifecycle needs of applications including data collection, web scale storage, data curation and organization, massively parallel processing, statistical and analytical tooling, integratives, visualization, and reporting tooling. All of this made possible at costs that make sense in today's highly budget constrained economic environment.

Hadoop Course Contents:
Part 1: Hadoop Distributed File System (HDFS)
  • Design of HDFS, HDFS Concepts
  • Command Line Interface
  • Java Interface
  • NameNode, DataNode and Secondary NameNode
  • Data Flow (Anatomy of a File Read, Anatomy of a File Write, Coherency Model)
  • Parallel Copying with DISTCP
  • Hadoop Archives
Part 2: Setting up Hadoop Cluster
  • Cluster Specification
  • Cluster Setup and Installation
  • SSH Configuration
  • Hadoop Configuration
  • Security
Part 3: Map Reduce
  • Writing a Map Reduce job
  • Anatomy of a Map Reduce Job Run (Job Tracker and Task Tracker)
  • Map Reduce Configuration
  • Hadoop Data Types
  • Functional - Concept of Mappers
  • Functional - Concept of Reducers
  • Functional - Concept of Partitioners
  • Functional - Concept of Combiners
  • Input Formats (Input Splits and Records, Text Input, Binary Input, Multiple Inputs, Database Input and Output)
  • Output Formats (Text Output, Binary Output, Multiple Outputs, Database output)
  • Hands-On Exercise
Part 4 : PIG
  • Installing and Running Pig
  • Pig's Data Model
  • Pig Latin
  • Developing & Testing Pig Latin Scripts
  • Making Pig Fly
  • Writing Evaluation
  • Filter
  • Load & Store Functions
  • User Defined Functions (UDF)
  • Hands-On Exercise
Part 5: HIVE
  • Installing Hive
  • Running Hive (Configuring Hive, Hive Services, MetaStore)
  • Comparison with Traditional Database (Schema on Read Versus Schema on Write, Updates, Transactions and Indexes)
  • Hive QL (Data Types, Operators and Functions)
  • Tables (Managed Tables and External Tables, Partitions and Buckets, Storage Formats, Importing Data, Altering Tables, Dropping Tables)
  • Querying Data (Sorting And Aggregating, Map Reduce Scripts, Joins & Sub queries & Views, Map and Reduce site Join to optimize Query)
  • User Defined Functions
  • Appending Data into existing Hive Table
  • Custom Map/Reduce in Hive
  • Hands-On Exercise
Part 6: HBASE
  • Introduction
  • Installation
  • HBase Architecture
  • Exploring HBase Master & Regionservers
  • HBase Shell Commands
  • Intro to Zookeeper
  • Client API – Basics
  • Client API - Advanced Features
  • Client API - Administrative Features
  • MapReduce Integration
  • Hands-On Exercise
  • Building Applications with Zookeeper (Zookeeper in Production)
Part 7: SQOOP
  • Introduction to Sqoop
  • Installation of Sqoop on your system
  • Import/Export data from RDBMS to HDFS
  • Import/Export data from RDBMS to HBase
  • Import/Export data from RDBMS to Hive
  • Hands-On Exercise
Part 8: NEXT-GEN HADOOP
  • Intro to High level concepts in Hadoop 2.0
  • YARN (Map Reduce 2.0)
  • Flume
  • HDFS HA
  • Oozie

For details like duration, commercials and customization for your college’s requirement please get in touch with us or mail to info@ecloudsol.com.


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