Apache Hadoop online and Classroom training

Expert Level Live big data hadoop Online & classroom Job oriented Training from Hyderabad by IT award winner, Hadoop certified professional trainer with 16 + Years of experience offers Job assistance training. Enroll TODAY to learn big data Analytics, Hadoop 2.X, HIVE, PIG, Hbase, Zookeeper and Sqoop

HADOOP Curriculam
  • Big Data and Hadoop Course
  • Big data and hadoop Course schedule
Big Data and Hadoop Course

Best Big Data and Hadoop Developer Certification Training

Enroll this course and become a big data hadoop certified professional Developer and administrator.

Course Description: learn Big data Analytics, Hadoop, MongoDB, No Sql, HIVE, PIG, hadoop Eco System
Course Duration: 199 Hours 
No of TM1 Classes:35    
Learning Mode:LIVE Instructor Led Online & classroom Training
Tools: Big data, Hadoop, Apache hadoop, Horton works Hadoop, Cloud era hadoop  
About Trainer: Big data Hadoop Certified technical trainer and Hadoop Subject Matter expert(SME) with 16 + years of experience
Big data course content: High quality and placement assistance Hadoop course curriculum has been prepared 

Course Level: Advanced Expert Level big data and Hadoop        
Register this course TODAY & get below benefits:

Hadoop administration training Free

Big data job assistance training free

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RK SOFT is a world best class Quality software training institute in Hyderabad offering Big data and Hadoop online training. It also provides IT Big data  infrastructure management courses and solutions.

Advantages with RKSOFT:
=> Covers both Big data Hadoop Development, Hadoop Administration and Functional
=> Complete LIVE project explanation
=> 60 hours big data hadoop hands on training exercises
=> End to end big data Hadoop Workshop 
=> big data job assistance training in all countries
=> High Quality big data Hadoop Course Content
=> Resume Preparation assistance
=> Big data hadoop Placement assistance
=> Big data hadoop course materials

Big data Hottest Training course - Every thing in single Place Including ETL (Pentaho)

Big data Hadoop Course Content

Designing and Building Big Data Applications

It will take 10 full days for Instructor-Led training, For Online Training it will take 80 Hrs. This course has been designed to teach you how to create HDFS system and access complete Big Data and Hadoop. You will walk through the entire process of designing and building solutions, including ingesting data, determining the appropriate file format for storage, processing the stored data, and presenting the results to the end-user in an easy-to-digest form.It also provides a technical overview of Apache Hadoop. It includes high-level information about concepts, architecture, operation,installation,configuration, maintenance, security, performance topics and uses of the Hadoop ecosystem.

Big Data & Hadoop basics and fundamentals

  •   Introduction of Big Data 

  •   What is Big Data?
  •   What kind of information comes under Big Data?
  •   Advantages of Big Data
  •   Characteristics of big data
  •   Operational Big Data
  •   Analytical Big Data
  •   Traditional data management systems and their limitations
  •   What is Hadoop?
  •   Overview of Hadoop
  •   Why Hadoop
  •   Background of Hadoop
  •   Basic Concepts and Fundamentals of Hadoop 
  •   Hadoop eco-system
  •   Hadoop Distributed File System (HDFS)
  •   HDFS Concepts and its Importance
  •   HDFS Deep Dive
  •   HDFS Architecture
  •   Data Replication
  •   HDFS Daemons
  •   Data Flow
  •   What is Map Reduce
  •   Overview of Map Reduce
  •   Importance of Map Reduce
  •   Overview of Map function
  •   importance of Reduce function
  •   What is mapreduce Ordering
  •   What is mapreduce Concurrency
  •   What is mapreduce Shuffle
  •   What is mapreduce Reducing
  •   What is mapreduce Concurrency

big data hadoop Hands-on Exercises

  •   Installing Hadoop in Pseudo Distributed Mode
  •   Understanding Important configuration files
  •   Understanding configuration files Properties and Demon Threads
  •   Accessing HDFS from Command Line
  •   Data ingest
  •   Starting HDFS
  •   Showing the files of HDFS
  •   Display the contents of the directory
  •   recursively display contents in all subdirectories of perticular path.
  •   Display disk usage
  •   Display the summary of disk usage of all files/directories in the perticular path.
  •   Moves the file from Source to Target
  •   Copy the file from Source to Target
  •   Removes the file 
  •   Remove all files from directory identified by path
  •   Other hands on excercises
  •   Inserting Data into HDFS
  •   get the Data from HDFS
  •   Map Reduce – Basic Exercises
  •   Understanding Big Data Hadoop Ecosystem
  •   Introduction to Sqoop, use cases and Installation
  •   Introduction to Hive, use cases and Installation
  •   Introduction to Pig, use cases and Installation
  •   Introduction to Oozie, use cases and Installation
  •   Introduction to Flume, use cases and Installation
  •   Introduction to Yarn

Map Reduce course content

  •   Mapper & Reducer
  •   Relation between input splits and HDFS blocks.
  •   Map reduce job submission flow of input splits.
  •   How Mapper and Combiner Works
  •   Mapper and Combiners Work
  •   Shuffle & Sort Phase,Combiner & Partitioner.
  •   Map Reduce in detail.
  •   Comparison b/w YARN and MRV1
  •   MapReduce job Execution.
  •   MapReduce Combiner.
  •   Mapreduce Partitioner.
  •   shuffle & Sort Phase.
  •   Job Scheduler
  •   Map reduce job submission flow
  •   Job launch process (Job)
  •   Job launch Process (task)
  •   Job launch process (Task tracker)
  •   Job launch process (Task runner)
  •   Joining Of Files/Datasets
  •   Joining Data sets in Map Reduce.
  •   Distributed cache.
  •   Reduce Joins
  •   Counters
  •   Reduce Join
  •   Input Format
  •   Custom Input Format.
  •   Inverted Indexing.
  •   Map Reduce – Inverted Indexing
  •   Hadoop API’s
  •   Explanation of MapReduce organization.
  •   How mapper process with detailed example

Pig Course objectives

  •   Introduction to Pig
  •   What Is Pig?
  •   Pig’s Features
  •   Pig Use Cases
  •   Interacting with Pig
  •   Basic Data Analysis with Pig
  •   Pig Latin Syntax
  •   Loading Data
  •   Simple Data Types
  •   Field Definitions
  •   Data Output
  •   Viewing the Schema
  •   Filtering and Sorting Data
  •   Commonly-Used Functions
  •   Hands-On Exercise: Using Pig for ETL Processing
  •   Processing Complex Data with Pig
  •   Complex/Nested Data Types
  •   Grouping
  •   Iterating Grouped Data
  •   Hands-On Exercise: Analyzing Data with Pig
  •   Multi-Dataset Operations with Pig
  •   Techniques for Combining Data Sets
  •   Joining Data Sets in Pig
  •   Set Operations
  •   Splitting Data Sets
  •   Hands-On Exercise

 Hive Course Outline

  •   Introduction to Hive
  •   What Is Hive?
  •   Hive Schema and Data Storage
  •   Comparing Hive to Traditional Databases
  •   Hive vs. Pig
  •   Hive Use Cases
  •   Interacting with Hive
  •   Relational Data Analysis with Hive
  •   Hive Databases and Tables
  •   Basic HiveQL Syntax
  •   Data Types
  •   Joining Data Sets
  •   Common Built-in Functions
  •   Hands-On Exercise: Running Hive Queries on the Shell, Scripts, and Hue
  •   Hive Data Management
  •   Hive Data Formats
  •   Creating Databases and Hive-Managed Tables
  •   Loading Data into Hive
  •   Altering Databases and Tables
  •   Self-Managed Tables
  •   Simplifying Queries with Views
  •   Storing Query Results
  •   Controlling Access to Data
  •   Hands-On Exercise: Data Management with Hive
  •   Hive Optimization
  •   Understanding Query Performance
  •   Partitioning
  •   Bucketing
  •   Indexing Data
  •   Extending Hive
  •   User-Defined Functions
  •   Hands on Exercises – Playing with huge data and Querying extensively.
  •   User defined Functions
  •   Optimizing Queries
  •   Tips and Tricks for performance tuning

Big Data and Hadoop Real Time project

Big data case study

Hadoop case study
Hadoop HDFS and Hive Real time project and data ingest into HDFS
Hive ODBC setup and connect to your technology 

RKSOFT IT Training Formats:

Learn Big data and Hadoop from the experts for in-depth training on your business analytics software in either classroom or instructor led online formats.

On-demand big data training availability for students who need training immediately to prepare for project start dates

Learn Big data and Hadoop with the same course content, class exercises and hands-on labs as classroom training without the need to travel. We can Customize the course material to suit your Project business requirement.
Big data and Hadoop Certification provides an industry standard benchmark for technical competence, and offers validation for professionals who work with Big data and Hadoop.
RKSOFT offer you a range of certifications and provide a way for professionals to demonstrate their competence in a competitive marketplace. Hortonworks Certification is highly recognized in the industry.You can enhance career advancement and opportunities.
RKSOFT offers a range of courses to suit your application, role, timeline and preferred learning format. Offered via instructor-led or self-paced courses, Big data and Hadoop standard and customized training programs are designed to match your unique project requirements.
Big data and Hadoop Class duration time: Big data and Hadoop typically run for 10 full days including Hands on Lab

 Big data and Hadoop training from Hyderabad

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Big data and hadoop Course schedule