Hadoop Online Training

BigData /Hadoop
Data beats Emotions

hadoop online training india
BigData / Hadoop Online Course Training
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QA Training Hub - Online Hadoop Training Tools Training Institutes in India - Hyderabad, Bangalore, Chennai, Pune.

Hadoop provides distributed processing framework formassive data sets. Hadoop is part of Apache Software Foundation. It is an open source and can be downloaded for free from its website: http://hadoop.apache.org.Hadoop is a java based programming framework.

Hadoop cluster consists of two layers namely the storage layer and the execution layer. Hadoop storage layer is composed of Hadoop distributed file system (HDFS)that responsible for data storage.The execution layer is composed of Hadoop Map Reduce responsible for data analysis. Map Reduce is responsible for parallel execution of jobs on multiple servers.

Hadoop consists of a virtual file system that connects many servers and accesses them as one huge system.Hadoop manages data size in Petabytes. The major components of Hadoop are Hive, HBase and Pig.

Hadoop framework is established in many renowned corporations like Google, Yahoo and IBM.

Advantages of Hadoop:

  • Simple - easy to write efficient code
  • Reliable - detects failures and redundant storage easily.
  • Fault tolerant - automatic suspension of failed jobs
  • Cost effective - provides storage for massive amount of data.
  • Fast - The unique storage method aids faster data processing.
  • Scalable - handles massive data through large number of nodes.

Hadoop is useful for managing massive data sets. Learning Hadoop has become an in-demand skill for any professional to sustain in the software industry. Our experienced trainers guide you through the implementation of Hadoop and explain you the key concepts used in Hadoop like HDFS and Map Reduce

Starting from simple concepts like how to configure simple and advanced clusters, and how to use the distributed file system, we guide you through creation of complex Map Reduce applications. Our aim is to train you to solve problems on your own.

This course is best suited for testing professionals as testing Hadoop application requires some basic knowledge on how Hadoop applications are developed and how it functions. Learning Hadoop makes the testing job easier. We also provide real time projects that give you better working experience with Hadoop.

Hadoop Online Training Course Content

Introduction to Hadoop
  • High Availability
  • Scaling
  • Advantages and Challenges
Introduction to Big Data
  • What is Big data
  • Big Data opportunities
  • Big Data Challenges
  • Characteristics of Big data
Introduction to Hadoop
  • Hadoop Distributed File System
  • Comparing Hadoop & SQL.
  • Industries using Hadoop.
  • Data Locality.
  • Hadoop Architecture.
  • Map Reduce & HDFS.
The Hadoop Distributed File System (HDFS)
  • HDFS Design & Concepts
  • Blocks, Name nodes and Data nodes
  • HDFS High-Availability and HDFS Federation.
  • Hadoop DFS The Command-Line Interface
Map Reduce
  • Functional Programming Basics.
  • Map and Reduce Basics
  • How Map Reduce Works
  • Anatomy of a Map Reduce Job Run
Map/Reduce Programming – Java Programming
  • Hands on “Word Count” in Map/Reduce in standalone and Pseudo distribution Mode.
  • Sorting files using Hadoop Configuration API discussion
  • Emulating “grep” for searching inside a file in Hadoop
  • DBInput Format
  • ACID in RDBMS and BASE in NoSQL.
  • CAP Theorem and Types of Consistency.
  • Types of NoSQL Databases in detail.
  • Columnar Databases in Detail (HBASE and CASSANDRA).
  • TTL, Bloom Filters and Compensation.
  • HBase Installation
  • HBase concepts
  • HBase Data Model and Comparison between RDBMS and NOSQL.
  • Master & Region Servers.
  • HBase Operations (DDL and DML) through Shell and Programming and HBase Architecture.
  • Installation
  • Introduction and Architecture.
  • Hive Services, Hive Shell, Hive Server and Hive Web Interface (HWI)
  • Meta store
  • Hive QL
  • OLTP vs. OLAP
  • Installation
  • Execution Types
  • Grunt Shell
  • Pig Latin
  • Data Processing
  • Schema on read
  • Primitive data types and complex data types.
  • Tuple schema, BAG Schema and MAP Schema.
  • Loading and Storing
  • Filtering
  • Installation
  • Import Data.
  • Free Form Query Import
  • Export data to RDBMS,HIVE and HBASE
  • Hands on Exercises.
  • Installation.
  • Introduction to HCATALOG.
  • About Hcatalog with PIG,HIVE and MR.
  • Hands on Exercises.
  • Installation
  • Introduction to Flume
  • Flume Agents: Sources, Channels and Sinks
  • Log User information using Java program in to HDFS using LOG4J and Avro Source
  • Log User information using Java program in to HDFS using Tail Source
  • Log User information using Java program in to HBASE using LOG4J and Avro Source More Ecosystems
  • HUE.(Hortonworks and Cloudera).
  • Workflow (Action, Start, Action, End, Kill, Join and Fork), Schedulers, Coordinators and Bundles.
  • Workflow to show how to schedule Sqoop Job, Hive, MR and PIG.
  • Zoo Keeper
  • HBASE Integration with HIVE and PIG.
  • Phoenix
  • Proof of concept (POC).
  • Overview
  • Linking with Spark
  • Initializing Spark
  • Using the Shell
  • Resilient Distributed Datasets (RDDs)
  • Parallelized Collections
For Bigdata Hadoop Testing Online COURSE : Click here
For DATA BASE Testing Online COURSE: Click here
For ETL Online COURSE : Click here
For SELENIUM Online COURSE : Click here
For Automation Online COURSE [HP+QTP/UFT] : Click here

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