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Big Data HADOOP Comprehensive Training (Weekend)
Start Date: 27-07-2015 Duration: 45 hours Price: 20000 Offer: 18000 Status: Full
Overview
Objectives

As the world moves to a digital age, there is literally an explosion of data and Hadoop makes it possible to stay on top of it.
Hadoop is a free, open-source software written in Java. It makes a quick work of processing mountains of data by breaking it up into smaller process that are parallelly run on multiple computers.  Two critical components of Hadoop are MapReduce and Hadoop Distributed File System (HDFS). While the latter organizes data in an easily manageable way, the former divides up the job of searching the data in a distributed and error-free manner.
HADOOP is sponsored by Apache Software Foundation, which promotes collaborative development of free and open-sources of software.

The attendees will learn below topics through lectures and hands-on exercises

    Understand Big Data & Hadoop Ecosystem
    Hadoop Distributed File System – HDFS
    Use Map Reduce API and write common algorithms
    Best practices for developing and debugging map reduce programs
    Advanced Map Reduce Concepts & Algorithms
    Hadoop Best Practices & Tip and Techniques
    Managing and Monitoring Hadoop Cluster
    Leverage Hive & Pig for analysis

Certification
Reasons to join

BIGDATA | HADOOP - TALENTCERTIFIED HADOOP PROFESSIONAL

Individuals who achieve TalentCertified Developer for Apache Hadoop (TCDH) accreditation have demonstrated their technical knowledge, skill, and ability to write, maintain, and optimize Apache Hadoop development projects.

Exam Code: TCDH-101
Number of Questions: 60 questions
Time Limit: 70 minutes
Passing Score: 70%

Hadoop - Hot skill to acquire on IT job circuit: The newest buzzword in the technology world is Hadoop. Think of it as the technology foundation without which all the hype around big data would not have been possible.  And if you are a programmer who knows what Hadoop is, you are a hot commodity on the job circuit.

Syllabus

BIGDATA  HADOOP Training Contents

(for details course contents, please call: 99860 44799 or mailto: info@sysinnovatalent.com)

HADOOP Intro and Installation
Virtual box/VM Ware
Basics & Installations
Linux
Installations & Commands
Need for Hadoop
Problem with existing traditional system
Requirements for new approach
Hadoop Basics
What is Hadoop?
Distributed Framework
Hadoop v/s RDBMS
Brief history of Hadoop
Setup Hadoop
Pseudo mode
Cluster mode
Ipv6, Ssh
Installation of java, Hadoop
Configurations of Hadoop
Hadoop Processes ( NN, SNN, JT, DN, TT)
Hadoop File System, UI
Common errors when running Hadoop cluster,  solutions

HDFS
The Hadoop Distributed Filesystem
Namenodes
Datanodes
The Command-Line Interface
Reading and writing data using Java
Hadoop Archives
Hadoop Streaming
Streaming using Unix
Streaming using Python
Python in MapReduce

MapReduce
What is MapReduce?
Relevance of MapReduce to Cloud computing
Map operation, Reduce operation
Real-world 'MapReduce' problems
Execution strategies for MapReduce
Common MapReduce Algorithms
Sorting and Searching
Indexing
Delving Deeper Into the Hadoop API
Using Combiners
Using LocalJobRunner Mode for Faster Development
Reducing Inter mediate Data with Combiners
Writing Partitioners for Better Load Balancing
Directly Accessing HDFS
Hands-On Exercise

PIG
Introduction  to Pig
Where do they fit in?
Getting Started with Pig Development  
Loading and displaying data
Basic data filters
Pig Schemas
Hands-On Exercise  
PigLatin in-depth  
Pig Datatypes  
More Advanced Dataset Filtering  
Pig Expressions and Functions  
Grouping and Sorting Data
Hands-On Exercise  
Joining Multiple Datasets  
Validating Datasets
Storing Data
User-Defined Functions
Using functions in Pig  
Hands-On Exercise


HIVE
Introduction to Hive
Hive Architecture
Hive interfaces       
Hive architecture
The Hive CLI
Getting data into Hive
Creating tables
Data types
Load data
SerDe
External tables
HiveQL           
SQL vs. HiveQL       
SELECT/ GROUP BY   
Functions/Subqueries   
Custom map/reduce scripts       
Joins/Inserting
Hands-on Exercise: Writing queries in HiveQL
Partitioning and Bucketing
Creating partitions
Loading data into partitions
Bucketing, Sampling
Hands-on Exercise: Using partitioning and bucketing
Best Practices for Hive
Configuring Hive
Handling data in Hive
Hands-on Exercise: loading data into Hive
Importing and Exporting Data from MySQL

HBASE
What is HBase?
Schema Modeling
The HBase Shell
The HBase Architecture
HBase Java APIs
HBase Data creation using Java Client Programs

SQOOP
Sqoop Overview
Installation
Imports and Exports
Importing and Exporting Data Between HDFS and RDBMS(MySQL)

FLUME
Flume Overview
Installation
Import and Export data
Import Streaming Data
Q & A

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