Big Data Hadoop Training

[Hadoopexpert]

Big Data Hadoop course Content - online training 

 

Training from Lead Hadoop expert architect and corporate trainer

 

Understanding Big Data

 Introduction

 Understanding Big Data

3V (Volume-Variety-Velocity) Characteristics

Structured and Unstructured Data

Application and use cases of Big Data

Limitations of Traditional Large Scale Systems

How a distributed way of computing is superior (cost and scale)

 

Installation/ setup/ configuration

                Download and setting the VMware for running the Linux Cent OS or Ubunto

                Download Install and configuration of Hadoop 1.0.4

                Download Install and configuration of Hive 0.10 stable version

                Download Install and configuration of sqoop 1.4.2

                Download Install and configuration of oozie

 

Will share the configurations for setting up the Hadoop cluster and Monitoring

 

HDFS (Hadoop Distributed FileSystem)

 HDFS Overview and Architecture

Data Replication

Safe Mode

Name Node

Checkpoint Node

Backup Node

Configuration Files

 

HDFS Data Flows

                Read

Write

HDFS Commands

 File System

Administrative

Advanced HDFS Features

                HDFS Federation

HDFS High Availability

 

MapReduce Overview 

 Functional Programming Paradigms

Fundamental MR Algorithms (Non-Graph)

 

Input and Output Formats

Hadoop Data Types

MR Algorithm and Data Flow-Explanation

WordCount Problem for understanding the workflow

 

Input Splits

Shuffling

Sorting

Hadoop Streaming 

Combiners

 

Advanced MapReduce Concepts

Partitioning

Counters (Skipping Bad Records)

Configuration Files

                Compression (Creating a sequence file and compressing the sequence file)

Distributed Cache

 

MR Best Practice and Debugging

Map Reduce Unit Testing

               

 

MapReduce Architecture

 

                Legacy MR

Next Generation MapReduce (aka YARN/MRV2)

Difference between Legacy MR and MR2 by programming

 

 

Higher Level Abstractions for MapReduce – 1

 Pig Introduction

Pig Latin Language Constructs

Pig User Defined Functions

Pig Use Cases

Pig  scripts for data analysis

 

Higher Level Abstractions for MapReduce – 2

 Hive - Introduction

Hive QL

Hive User Defined Functions

Hive Use Cases

 

SQOOP

OOZIE

 

NOSQL Databases 

                NoSQL Concepts

 Review of RDBMS

Need for NOSQL

Brewers CAP Theorem

ACID vs BASE

 

Different Types of NoSQL Databases

 Key Value

Document

Graph

Columnar Databases

 

Hadoop Ecosystem

 HBase – No SQL Database -

 

 

Key features:

 

·         At the end of each session material for the day will be shared and along with few links and other resources for the topics will be shared with the candidates.

 

·         Exercises on the topic will be given for practice next day will discuss the solution for the same and will move to the next topic.

 

·         Where ever possible Interview questions and scenario based problems will be shared to the candidates to get the insight of the real time environment.

 

·         At the completion of the course a real time POC (Proof Of Concept) requirement will be given to the candidates for practicing the end to end Hadoop contents.

 

·         POC on Eco Systems includes Hive, HBase and Pig.

 

·         Assistance for Resume preparation and mock interviews will conducted

 

Optional:

 

                For the candidate who do not have prior Java (Core Java)  knowledge, five sessions on Java concepts required for writing MapReduce programs will be taken.

 

Timings:

We conduct online training in two fashions:

1.       6:30 AM IST to 8:00 AM IST during week days (Monday through Friday)

2.       9:00 AM IST to 5:00 PM IST Only weekends (5 weekends)

 

 

 

For fee further details

 

Contact: Krishna Raju

Email ID: [email protected]

Ph# +91-9160031512