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16th December 2015, 05:48 PM
Super Moderator
Join Date: Apr 2013
Re: Big Data Online Training

WizIQ provides Hadoop and Big Data Training online course, here given below are the details of this course

Course Highlights
30 hrs of live online classes by highly qualified Hadoop professionals

In-session practice exercises for gaining practical understanding

Suitable for database developers, programmers, BI developers and DBA’s

All live online classes are recorded and can be accessed for 6 months

Course Outcomes
Understand Big Data and Hadoop ecosystem

Work with Hadoop Distributed File System (HDFS)

Write MapReduce programs and implementing HBase

Write Hive and Pig scripts

Knowledge of programming in C++ or Java or any other Object Oriented Programming language is preferred

Hardware/Software Requirements:
64 bit or 64 bit ready PC/Laptop (Intel Core 2 Duo or above)

Modules and Content

Virtual Box/VM Ware

Basics, Installations, Backups, Snapshots




Why Hadoop, Scaling, Distributed Framework, Hadoop v/s RDBMS, Brief history of Hadoop, Problems with traditional large-scale systems, Requirements for a new approach, Anatomy of a Hadoop cluster, Other Hadoop Ecosystem components

Setup Hadoop
Pseudo mode, Cluster mode, Installation of Java, Hadoop, Configurations of Hadoop, Hadoop Processes ( NN, SNN, JT, DN, TT), Temporary directory, UI, Common errors when running Hadoop cluster, Solutions

HDFS- Hadoop Distributed File System-

HDFS design and architecture, HDFS concepts, Interacting HDFS using command line,Dataflow, Blocks, Replica

Hadoop Processes

Name node, Secondary name node, Job tracker, Task tracker, Data node

Developing MapReduce application, Phases in MapReduce framework, MapReduce input and output formats, Advanced concepts, Sample applications, Combiner

Writing a MapReduce Program
The MapReduce flow, Examining a sample MapReduce program, Basic MapReduce API concepts, Driver code, Mapper, Reducer, Hadoop’s streaming API, Using Eclipse for rapid development, Hands-on exercise, New MapReduce API

Common MapReduce Algorithms
Sorting and Searching, Indexing, Term Frequency – Inverse Document Frequency, Word Co-occurrence, Hands-on exercise

Writing advance map reduce programs
Building multivalue writable data, Accessing and using counters,Partitioner - Hashpartitioner,Hands on Exercises .

Hadoop Programming Languages
HIVE: Introduction, Installation, Configuration, Interacting HDFS using HIVE, MapReduce programs through HIVE, HIVE commands, Loading, Filtering, Grouping, Data types, Operators, Joins, Groups, Sample programs in HIVE

PIG: Basics, Configuration, Commands,Loading, Filtering, Grouping, Data types, Operators, Joins, Groups, Sample programs in PIG

What is HBase, HBase architecture, HBase API, Managing large data sets with HBase, Using HBase in Hadoop applications.

Integrating Hadoop into the Enterprise Workflow
Integrating Hadoop into an Existing Enterprise, Loading Data from an RDBMS into HDFS by Using Sqoop, Managing Real-Time Data Using Flume.

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