• Bangalore - 560076
  • 8904740434
  • learn@techieventures.in

Hadoop training institute in btm layout

Description

Hadoop is an open-source framework that allows huge storage and process large datasets in a distributed environment across clusters of several thousand computers(commodity hardware) using simple programming models. It is designed to scale up from single server to thousands of machines, each offering local computation and storage.

Hadoop provides massive storage capacity for any kind of data, enormous processing power and the ability to handle virtually limitless concurrent tasks or jobs.

Hadoop's architecture helps us to gain insight from big data at low cost and in huge scale. It is very reliable and easily scalable.

Duration

Duration: 1.5 Month

Career Option
  • Developer/Testing
  • Administration
  • Data Analyst
Opportunities

Some of the big names using Hadoop are Shopzilla, Treato, Google, Amazon, Facebook.

The Big Data Vendor Revenue and Market Forecast between 2013-2017, Wikibon said it expects rapid growth for Hadoop, with revenues set to rise from $18.6 billion in 2013 to $50.1 billion by 2018.

Allied Market Research company put Hadoop’s market value at $2.0 billion in 2013, rising to a staggering $50.2 billion by 2020.

Major Companies Using Hadoop
  • Facebook
  • Google
  • Yahoo!
  • flipkart
  • Amazon
  • ANZ
Course Content
HDFS ARCHITECTURE
Basic Terminologies
HDFS Block Concepts
Replication Concepts
Basic reading & writing Of files in HDFS
Basic processing concepts in MapReduce
Data Flow
Anatomy of file READ And WRITE
Hadoop commands
Hadoop Archives
Communication Among HDFS Elements
In-Depth Concepts of HDFS Elements
DataNode Block Management Advance
Real Use Case
MAP REDUCE
Introduction to Map Reduce
Architecture of Map Reduce
Map Reduce types and format
Programming with Map Reduce
Map Reduce Features
Counters
Sorting
Joins
Side data distribution
Programming on joins using Map Reduce
PIG
Introduction to Pig
Comparison with Databases
Pig Latin
User Defined Functions
Filters
Data Processing operators
Load And Store Function
Developing and Testing Pig Latin Scripts
HIVE
An Introduction
Hive Architecture
Hive Installation Guide
Running Hive
Comparison with Traditional Database
HiveQL
HiveQL: Data Types, Operators and Functions
Tables Management
Querying Data
UDF
HBASE
Basic Concepts
Configuration & Installation
Working With HBase
HBase versus RDBMS
Schema Design
CASSANDRA
Why NoSQL databases
Intro to Cassandra
Installation and setup of Cassandra
Cassandra Query Language
Cassandra Architecture

ZOOKEEPER
Installing & Running Zookeeper
The ZooKeeper Service: Data Model
Services
States
Sessions
Consistency
Application Building
Zookeeper in Production
HADOOP 2.0,YARN,V2
Hadoop 2.0 New Features: Name Node High Availability
HDFS Federation
MRv2
YARN
Running MRv1 in YARN
Upgrade your existing MRv1 code to MRv2
LINUX ADMINISTRATIONS
Introduction to Linux
Planning Disk Partition
Users And Group Management
Administration Of File System & Security
Linux Essentials And Hardware Management
Trouble Shooting Problems in Linux Systems
Linux Security
CLUSTER SETUP -SINGLE NODE CLUSTER
Single Node Cluster
Installing Java
Creating Hadoop User
SSH configuration
Understanding Hadoop Configuration Files
Setting Up The Single Node Cluster
CLUSTER SETUP -MULTINODE CLUSTER
Understanding the Configuration Files
Setting Up Multi Node Cluster
Deploying Data on 3-Node Cluster
FLUME
Introduction
Flume Architecture
Data Ingest in HDFS with Flume
Flume Sources
Flume Sinks
Topology Design Considerations

SQOOP
An Introduction
Sqoop Architecture
Downloading & Installing Sqoop
Starting Sqoop
Importing Data From MySql, And PostgreSQL
Various Cases Of Import
Incremental Import Cases
Importing Data From Multiple Tables
Using Custom Boundary Queries
Exporting Data From Hadoop
Use Cases Of Export
Hadoop Ecosystem Integration
COMMSSIONING & DECOMMISSIONING
TOPOLOGY AWARNESS & RACK SETUP
CONFIGURING BACKUP & RECOVERY FOR HADOOP
BASIC KNOWLEDGE OF AMAZON DISTRIBUTRION
PERFORMANCE TUNING
Split Size
Number of Reducers
Combiners
Distributed Cache
Compression
Combine File Input Format
Filtering
JVM Reuse
MONITORING HADOOP(NAGIOS OR GANGLIA
Introduction
Installation
Features
Working with the tools
Monitoring the system
Monitoring the cluster

JAVA FOR HADOOP-JAVA INTRODUCTION
Installing Java
Eclipse Introduction
Creating a Sample Java Project
Writing First Java Program
Basic Java Terminology
OOPS CONCEPT
Object
Class
Data handling & Encapsulation
Message Passing
Inheritance
Polymorphism
Dynamic Binding
COLLECTIONS
Lists
Sets
Maps
Trees
EXCEPTION HANDLING
Errors
Checked Exception
Unchecked Exception
Custom Exceptions