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Hadoop at Tekclasses Institute





₹ 15,000   ( ₹ 18,000  | 15% Off)
#249,3rd floor, chirag towers , Outer Ring Road, ,
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What is Hadoop?

Hadoop is an open-source framework that allows to store and process big data and helps to organize the massive data. It is designed to scale up from single servers to thousands of machines, each offering local computation and storage. We have designed Hadoop Training course as per Cloud Era Certification syllabus. This course is designed to provide knowledge and skills to become a successful Hadoop Developer. The candidate will get in-depth knowledge of core concepts along with implementation to real-time use-cases.

Who can take this course

Hadoop Online Training is suitable for professionals aspiring to make a career in Big Data Analytics, Architects, Datawarehouse Developers

Pre-Requisite

To learn Hadoop the prerequisites are to have basic knowledge on UNIX Commands and knowledge on Core java is essential.

Key-Takeaways

30 Hours of Lab Exercises with Proprietary VM
Packed with Latest & Advanced modules like YARN, Flume, Oozie and Sqoop
Well Experienced and Real Time Trainers
Best in Class Infrastructure

FAQ’S

WHAT IS BIGDATA?
Big data means really a big data, it is a collection of large datasets that cannot be processed using traditional computing techniques. The data in it will be of three types. Structured data(Relational data) , Semi Structured(XML data) data Unstructured data (Word, PDF, Text, Media Logs)

IS THERE ANY SAMPLE VIDEO I CAN SEE BEFORE ENROLLING TO THE COURSE?
Yes, Please verify the Demo video section for each course.

HOW SOON AFTER SIGNING UP WOULD I GET ACCESS TO THE LEARNING CONTENT?
Yes, we will provide access to all the learning materials after the complete payment for the course.

IS THERE ANY OFFER / DISCOUNT I CAN AVAIL?
Yes, offers will be keep changing from time to time. Please check with training coordinator or chat with us.

DO YOU PROVIDE THE SOFTWARE INSTALLATION FOR HADOOP TRAING?

For doing the practical’s we will help you to setup Virtual Machine in your System with local access. The detailed installation video is provided in the Tek Classes You tube channel for setting up this environment. In case you come across any doubt, the 24*7 support team will promptly assist you.

In the end of this course the participant will be able to:

  • Understand basics of Big Data and Hadoop
  • Hadoop Cluster Set-up
  • Hadoop Distributed File System
  • Advance understanding of MapReduce programming with Hands-On practices
  • Working with PIG, HIVE and HBASE
  • Basics of Oozie, Flume and Sqoop

Module 1: Introduction to Big Data

Topics covered on Big Data introduction
  • What is Big Data?
  • What are the challenges for processing big data?
  • What technologies support big data?
  • 3V’s of BigData and Growing
  • Problems with traditional large-scale systems

Module 2: Introduction to Hadoop

Topics covered on Hadoop Introduction
  • An Overview of Hadoop
  • History of Hadoop
  • Hadoop Core
    • The Hadoop Distributed File System
    • MapReduce Programming model
  • Hadoop Ecosystem
  • Real Life Use Cases

Module 3: Hadoop Cluster Setup

Topics covered on Cluster Setup
  • Setup & Configuration details
  • Local mode
  • Pseudo distributed mode
  • Distributed mode
  • Using Cloudera CDH

Module 4: Hadoop Distributed File System (HDFS)

Topics covered on HDFS
  • HDFS Design & Concepts
  • Building Blocks of Hadoop
    • Name Node (NN) and its functionality
    • Data Node(DN) and its functionality
    • SecondaryNameNode(SNN) and its functionality
  • Replica and Block placement
  • HDFS user and admin commands.
  • Basic File System Operations
  • HDFS Java Client API
  • Read and Write flow
  • Safemode
  • distCP-Data loading into HDFS parallel
  • Hadoop Data Archives
  • Data Integrity and Compression

Module 5: MapReduce

Topics covered on MapReduce
  • Components of MapReduce
  • JobTracker and its functionality
  • TaskTrack and its functionality
  • Job execution flow
  • MapReduce Programming Model
  • Mapper
  • Reducer
  • Writable and WritableComparator
  • MapReduce old and new API’s
  • Input Formatters and its associated Record Readers
  • InputSplits
  • Output Formatters and its associated Record Writers
  • Configuration and Writing MR jobs in Eclipse.
  • Running MR Job on Local Mode.
  • Running MR Job on Cluster/Distributed Mode
  • Shuffle Sort
  • Combiner
  • Partitioner
  • Job submission flow
  • Speculative Execution
  • RawComparator
  • Different FileFormats (Sequence File, MapFile, Other File Formats)
  • Hands-on MapReduce Program Examples

Module 6: Advance Map Reduce Programming

Topics covered on Advance Map Reduce Programming
  • Custom Writable
  • Custom Partitioner
  • Custom Combiner
  • Custom Input and output Formatters
  • Custom Sorting (Secondary Sorting)
  • Distributed Cache
  • Counters & Reporter
  • Compression techniques
  • Joins
  • Chaining of MR Jobs
  • Adding third party libraries to MRJobs

Module 7: Programming Practices

Topics covered on Programming Practices
  • Writing MapReduce Programs with Eclipse IDE
  • Setup Maven Project for writing MapReduce Jobs
  • Web UI for monitoring cluster
  • Side Data Distribution Techniques
  • Sending Job specific parameters
  • Using Distributed Cache
  • Performance tuning
  • Partitioning MR Job output into multiple output files

Module 8: Apache PIG

Topics covered on PIG
  • Introduction to Apache Pig
  • Setup & Configurations
  • Pig Latin through Grunt Shell
  • Data types
  • Relational Operators
  • Expressions and Functions
  • Working with Pig Script
  • Writing reusable script by parameter substitution
  • Writing UDF’s
  • Pig Joins
  • Load and Processing Complex Data with Pig
  • Hands-on writing Pig Script
  • DataFu/Piggy Bank

Module 9: Apache Hive

Topics covered on Hive
  • Introduction to Apache Hive
  • Hive vs SQL
  • Setup & Configuration
  • Hive Architecture
  • MetaStore
  • Different DataTypes
  • Hive CLI
  • Hive QL
  • DDL and DML Operations
  • Hive build in operators and functions
  • Create Partitioned tables
  • Create User Defined Functions
  • Bucketing
  • Working with different FileFormats
  • Perform a join of two datasets with Hive
  • Tuning

Module 10: Apache HBase

Topics covered on HBase
  • HBase introduction
  • When Should I Use HBase
  • HBase Vs HDFS
  • Setup & Configurations
  • Key Design
  • Column families
  • HBase shell commands
  • Basic CRUD operations
  • Web Based UI
  • HBase Architecture
  • HBase Components
  • Zookeeper
  • Compaction
  • HBase Hands-on
  • Mapreduce integration
  • Pig Integration
  • Hive Integration
  • HBase Clients

Module 11: Apache Oozie, Flume and Sqoop

  • Cloud era Certified Trainer
  • 6+ Years of Experience in Java
  • 2+ Years of experience in Hadoop class room Training and Hadoop Online Training
  • Working Big data Architect in TOP MNC
  • Excellent Communication Skills
Good Course
  • Content
  • Instructor
  • Institute

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Videotekclasses hadoop bangalore training course
Price: ₹ 15,000
Start-End Dates: 17 Oct 16 - 16 Nov 16
Course Duration: 30 days
Discount: 25%
Instructional Level: Appropriate for All
Certification
Quizzes
Live Projects
Doubt Clearing Sessions
Reading Material
EMI Option
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