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Bigdata Hadoop Training

Bigdata Hadoop Training

SDLC -Progress

Bigdata Hadoop Training program at SDLC Training is designed to give participants the skills & knowledge to gain a competitive advantage in starting / enhancing a career in Bigdata Hadoop industry. Participants receive up-to-date training in multiple areas in Bigdata Hadoop and a thorough understanding of real-world projects.

SDLC Training is one of the pioneers in software training. We delivered the training for many individuals, groups, and corporations. We prioritize to give our best quality of training and further assistance. You have complete freedom to customize course topics and time. Online training is a good experience and a generation ahead. Register yourself for unbelievable prices.

The Bigdata Hadoop course has been constituted towards the needs of current industry standards. While we will continue to emphasize our own basic academics, we are also aware that our students require Bigdata Hadoop competencies that enhance employment and livelihood opportunities. Clearly the perspective of will be to continuously demonstrate the quality in the delivery of technology.

 Hadoop Overview:

Apache Hadoop enables organizations to analyze massive volumes of structured and unstructured data and is currently very hot trend across the software tech industry. Hadoop will be adopted as default enterprise data hub by most of the enterprise soon.

This course will provide you an excellent kick start in building your fundamentals in developing big data solutions using Hadoop platform and its ecosystem tools. The course is well balanced between theory and hands-on lab (more than 15 lab exercises) spread on real world uses cases like retail data analysis, sentiment analysis, log analysis, real time trend analysis etc.

 

We are committed to provide high quality Bigdata Hadoop Training in Bangalore that helps the students and professionals in areas of Bigdata Hadoop through its innovative programs and outstanding faculty.

Post Successful completion of Bigdata Hadoop Training Program leads to placement assistance and participation in campus placements by SDLC.

Who Should Attend?

Architects and developers, who wish to write, build and maintain Apache Hadoop jobs.

Prerequisite:

The participants should have basic knowledge of java, SQL and Linux. It is advised to refresh these skills to obtain maximum benefit from this workshop.

What participants will learn?

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

  • Understand Big Data, Hadoop 2.0 architecture and its Ecosystem
  • Deep Dive into HDFS and YARN Architecture
  • Writing map reduce algorithms using java APIs
  • Advanced Map Reduce features & Algorithms
  • How to leverage Hive & Pig for structured and unstructured data analysis
  • Data import and export using Sqoop and Flume and create workflows using Oozie
  • Hadoop Best Practices, Sizing and capacity planning
  • Creating reference architectures for big data solutions

Bigdata Hadoop Course Details

Demo Class : Free Demo Session, Flexible TimingsFree Class : Attend 3 Free Classes to check training Quality
Regular : 2 Hour per dayFast Track : 3 – 4 Hours per day: 10 days
Weekdays : AvailableWeekend : Available
Online Training : AvailableClass Room Training : Available
Course Fee : Talk to our Customer SupportDuration : 30 Hours

Bigdata Hadoop Training Content

 MODULE 1- INTRODUCTION TO BIGDATA

  • Evolution of Big Data
  • The 6 V’s challenges of traditional technology
  • Comparison of Big Data with Traditional technologies
  • What is Big Data?
  • Examples of Big Data
  • Reasons for Big Data Evolution
  • Why Big Data deserves your attention
  • Use cases of Big Data
  • Different ways of analytical techniques using Bigdata

MODULE 2- INTRODUCTION TOHADOOP

  • What is Hadoop
  • History of Hadoop
  • Hadoop Ecosystem
  • Problems with Traditional Large-Scale Systems and Need for Hadoop
  • Understanding Hadoop Architecture
  • Fundamental of HDFS (Blocks, Name Node, Data Node, Secondary Name Node)
  • Rack Awareness
  • Read/Write from HDFS
  • HDFS Federation and High Availability

MODULE 3- STARTING HADOOP

  • Setting up single node Hadoop cluster(Pseudo mode)
  • Understanding Hadoop configuration files
  • Hadoop Components- HDFS, MapReduce
  • Overview Of Hadoop Processes
  • Overview Of Hadoop Distributed File System
  • The building blocks of Hadoop
  • Hands-On Exercise: Using HDFS commands

MODULE 4- MAPREDUCE-1(MR V1)

  • Understanding Map Reduce
  • Job Tracker and Task Tracker
  • Architecture of Map Reduce
  • Map Function
  • Reduce Function
  • Data Flow of Map Reduce
  • How Map Reduce Works
  • Anatomy of Map Reduce Job (MR-1)
  • Submission & Initialization of Map Reduce Job
  • Assigning & Execution of Tasks
  • Monitoring & Progress of Map Reduce Job
  • Hadoop Writable and Comparable
  • Map Reduce Types and Formats
  • Understand Difference Between Block and Input Split
  • Role of Record Reader
  • Different File Input Formats
  • Map Reduce Joins

MODULE 5- MAPREDUCE-2(YARN)

  • Limitations of Current Architecture
  • YARN Architecture
  • Application Master, Node Manager&Resource Manager
  • Job Submission and Job Initialization
  • Task Assignment and Task Execution
  • Progress and Monitoring of the Job
  • Failure Handling in YARN
  • Task Failure

MODULE 6- HIVE

  • Introduction to Apache Hive
  • Architecture of Hive
  • Installing Hive
  • Hive data types
  • Hive-HQL
  • Types of Tables in Hive
  • Partitions
  • Buckets& Sampling
  • Indexes
  • Views
  • Executing hive queries from Linux terminal
  • Executing hive queries from a file
  • Creating UDFs in HIVE
  • Hands-On Exercise

MODULE 7- PIG

  • Introduction to Apache Pig
  • Install Pig
  • Architecture
  • Data types
  • Working with various PIG Commands covering all the functions in PIG
  • Working with un-structured data
  • Working with Semi-structured data
  • Creating UDFs
  • Hands-On Exercise

MODULE 8- SQOOP

  • Introduction to SQOOP& Architecture
  • Installation of SQOOP
  • Import data from RDBMS to HDFS
  • Importing Data from RDBMS to HIVE
  • Exporting data from HIVE to RDBMS
  • Hands on exercise

MODULE 9- HBASE

  • Introduction to HBASE
  • Installation ofHBASE
  • Exploring HBASE Master & Region server
  • Exploring Zookeeper
  • CRUD Operation of HBase with Examples
  • HIVE integration with HBASE
  • Hands on exercise on HBASE

MODULE 10- OVERVIEW SESSIONS ON

  • HUE
  • OOZIE
  • FLUME
  • SPARK
  • KAFKA
  • STORM
  • AMBARI
  • MAHOUT

MODULE 11- FAQs, REAL TIME ENVIRONMENT & REAL TIME SCENARIOS

  • Real Time Q/A
  • FAQ
  • Real Time Environment

MODULE 12-REAL TIME PROJECT

  • Working on Real Time Project

We will be providing raw data & requirements for the project & you will have to work. Finally we will have one Project execution session where we will be explaining the steps for execution.

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  • 100% Placement Assistance
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  • Flexible Timings
  • Resume Preparation
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  • Mock Interviews
  • Small Batch Size for Individual Care