Hadoop Online Training by top trainers with placement assurance

We are the best institute provide you excellent hadoop online training with free course materials.
We also provide placement assurance.

HADOOP COURSE CONTEST
HADOOP:
€šš What is Big Data?
€šš What is Hadoop?
€šš Relation between Big Data and Hadoop.
€šš What is the need of going ahead with Hadoop?
€šš Scenarios to apt Hadoop Technology in REAL TIME Projects
€šš Challenges with Big Data
»Storage
» Processing
€šš How Hadoop is addressing Big Data Changes
€šš Comparison with Other Technologies
» RDBMS
» Data Warehouse
» TeraData
€šš Different Components of Hadoop Echo System
» Storage Components
» Processing Components

HDFS (Hadoop Distributed File System)
€šš What is a Cluster Environment?
€šš Cluster Vs Hadoop Cluster.
€šš Significance of HDFS in Hadoop
€šš Features of HDFS
€šš Storage aspects of HDFS
» Block
» How to Configure block size
» Default Vs configurable block size
» Why HDFS block size is so large
» Design Principles of block size
€šš HDFS Architecture 5 demons of Hadoop
» NameNode and its functionality
» Data node and its functionality
» Job Tracker and its functionality
» Task Track and its functionality
» Secondary Name Node and its functionality
€šš Replication in Hadoop - Fail Over Mechanism
» Data Storage in Data Nodes
» Fail Over Mechanism in Hadoop - Replication
» Replication Configuration
» Custom Replication
» Design Constraints with Replication Factor
€šš Accessing HDFS
» CLI (Command Line Interface) and HDFS Commands
» Java Based Approach
€šš Hadoop Archives

MapReduce
€šš Why Map Reduce is essential in Hadoop?
€šš Processing Daemons of Hadoop
» Job Tracker
> Roles Of Job Tracker
> Drawbacks w.r.to Job Tracker failure in Hadoop Cluster
> How to configure Job Tracker in Hadoop Cluster
» Task Tracker
> Roles of Task Tracker
> Drawbacks w.r.to Task Tracker Failure in Hadoop Cluster
€šš Input Split
» InputSplit
» Need Of Input Split in Map Reduce
» InputSplit Size
» InputSplit Size Vs Block Size
»InputSplit Vs Mappers
€šš Map Reduce Life Cycle
» Communication Mechanism of Job Tracker and Task Tracker
» Input Format Class
» Record Reader Class
» Success Case Scenarios
» Failure Case Scenario
» Retry Mechanism in Map Reduce
€šš MapRedue Programming Model
» Different phases of Map Reduce Algorithm
» Different Data types in Map Reduce
> Primitive Data types Vs Map Reduce Data types
» How to write basic Map Reduce Program
> Driver Code
> Mapper Code
> Reducer Code
»Driver Code
> Importance of Driver Code in a Map Reduce program
> How to Identify the Driver Code in Map Reduce program
> Different sections of Driver code
» Mapper Code
> Importance of Mapper Phase in Map Reduce
> How to Write a Mapper Class?
> Methods in Mapper Class
» Reducer Code
> Importance of Reduce phase in Map Reduce
> How to Write Reducer Class?
> Methods in Reducer Class
» IDENTITY MAPPER & IDENTITY REDUCER
» Input Formats in Map Reduce
> TextInputFormat
> KeyValueTextInputFormat
> NLinelnputFormat
> DBlnputFormat
> SequenceFilelnputFormat
> How to use the specific input format in Map Reduce
» Output Formats in Map Reduce
> TextOutputFormat
> KeyValueTextOutputFormat
> NLineOutputFormat
> DBOutputFormat
> SequenceFileOutputFormat
> How to use the specific Output format in Map reduce
» Map Reduce API(Application Programming
> New API
> Deprecated API
» Combiner in Map Reduce
> Is combiner mandate in Map Reduce
> How to use the combiner class in Map Reduce
> Performance tradeoffs w.r.to Combiner
» Partitioner in Map Reduce
> Importance of Pratitioner class in Map Reduce
> How to use the Partitioner class in Map Reduce
> hashPartitioner functionality
> How to write a custom Partitioner
» Compression techniques in Map Reduce
> Importance of Compression in Map Reduce
> What is CODEC
> Compression Types
> GzipCodec
> BzipCodec
> LZOCodec
> SnappyCodec
> Configurations w.r.to Compression Techniques
> How to customize the Compression per one job Vs all the job
» Joins - in Map Reduce
> Map Side Join
> Reduce Side Join
> Performance Trade Off
> Distributed cache
» How to debug MapReduce Jobs in Local and Pseudo cluster Mode.
» Introduction to MapReduce Streaming
» Data localization in Map Reduce

Apache PIG
€šš Introduction to Apache Pig
€šš Map Reduce Vs Apache Pig
€šš SQL Vs Apache Pig
€šš Different data types in Pig
€šš Modes Of Execution in Pig
» Local Mode
» Map Reduce OR Distributed Mode
€šš Execution Mechanism
» Grunt Shell
» Script
€šš Embedded
€šš Transformations in Pig
€šš How to write a simple pig script
€šš How to develop the Complex Pig Script
€šš Bags, Tuples and fields in PIG
€šš UDFs in Pig
» Need of using UDFs in PIG
» How to use UDFs
» REGISTER Key word in PIG
€šš When to use Map Reduce & Apace PIG in REAL TIME Projects

HIVE
€šš Hive Introduction
€šš Need of Apache HIVE in Hadoop
€šš Hive Architect
» Driver
» Compiler
» Executor(Semantic Analyzer)
€šš Meta Store in Hive
» Importance Of Hive Meta Store
» Embedded metastore configuration
» External metastore configuration
» Communication mechanism with Metastore
€šš Hive Integration with Hadoop
€šš Hive Query Language(Hive QL)
€šš Configuring Hive with MySQL MetaStore
€šš SQL VS Hive QL
€šš Data Slicing Mechanisms
» Partitions In Hive
» Buckets In Hive
» Partitioning Vs Bucketing
» Real Time Use Cases
€šš Collection Data Types in HIVE
» Array
» Struct
» Map
€šš User Defined Functions(UDFs) in HIVE
» UDFs
» UDAFs
» UDTFs
» Need of UDFs in HIVE
€šš Hive Serializer/Deserializer SerDe
€šš HIVE - HBASE Integration

SQOOP
€šš Introduction to sqoop
€šš MySQL client and Server Installation
€šš How to connect to Relational database using Sqoop
€šš different Sqoop Commands
» Different flavours of Improrts
» Export
» Hive-Imports

HBASE
€šš HBASE Introduction
€šš HDFS Vs HBase
€šš Hbase use cases
€šš Hbase basics
» Column families
» Scans
€šš HBase Architecture
€šš Clients
» REST
» Thrift
» Java Based
» Avro
€šš Map Reduce Integration
€šš Map Reduce over HBase
€šš HBase Admin
» Schema Definition
» Basic CRUD Operations

FLUME
€šš Flume Introduction
€šš Flume Architecture
€šš Flume Master, Flume Collector and Flume Agent
€šš Flume Configurations
€šš Real Time Use Case using Apache Flume

OOZIE:
€šš Oozie Introduction
€šš Oozie Architecture
€šš Oozie Configuration Files
€šš Oozie Job Submission
» Workflow.xml
» Coordinatot:xml
» job.coordinatonproperties

YARN (Yet Another Resource Negotiator) - Next Gen. Map Reduce
€šš What is YARN?
€šš YARN Architecture
» Resource Manager
» Application Master
» Node Manager
€šš When should we go ahead with YARN
€šš Classic Map Reduce Vs YARN Map Reduce
€šš Different Configuration Files for YARN

IMPALA:
€šš What is Impala?
€šš How can we use Impala for Query Processing
€šš When should we go ahead with Impala
€šš HIVE Vs Impala
€šš REAL TIME Use Case with Impala

MongoDB (NoSQL Database):
€šš Need of NoSQL Databases
€šš Relational Vs Non-Relational Databases
€šš Introduction to MongoDB
€šš Features of MongoDB
€šš Installation of MongoDB
€šš Mongo DB Basic operations

OVERVIEW OF KAFKA:
€šš Topics.
€šš Producers
€šš Consumers.
€šš Brokers.

OVERVIEW OF SPARK:
€šš Scala
€šš Spark SQL
€šš Joins using spark SQL.

HADOOP ADMINISTRATION:
€šš Hadoop Single Node Cluster Set Up (Hands on Installation on Laptops)
» Operating System Installation
» JDK Installation
» SSH Configuration
» Dedicated Group & User Creation
» Hadoop Installation
» Different Configuration Files Setting
» Name node format
» Starting the Hadoop Daemons
€šš Multi Node Hadoop Cluster Set Up (Hands on Installation on Laptops) )
» Network related settings
» Hosts Configuration
» Password less SSH Communication
» Hadoop Installation
» Configuration Files Setting
» Name Node Format
» Starting the Hadoop Daemons
€šš PIG Installation (Hands on Installation on Laptops)
» Local Mode » Clustered Mode » Bashrc file configuration
€šš SQOOP Installation (Hands on Installation on Laptops)
» Sqoop installation with MySQL Client
€šš HIVE Installation (Hands on Installation on Laptops)
» Local Mode » Clustered Mode
€šš Hbase Installation (Hands on Installation on Laptops)
» Local Mode » Clustered Mode
€šš OOZIE Installation (Hands on Installation on Laptops)
€šš Mongo DB Installation (Hands on Installation on Laptops)
€šš Commissioning of Nodes In Hadoop Cluster
€šš Decommissioning of Nodes from Hadoop Cluster

Offerings:
€šš Proof Of Concepts (POCs) - En End Execution and demonstration by POC Groups.
€šš Hand Written Hard Copy & Soft Copy Materials for all the Components.
€šš Detailed Assistance in RESUME Preparation with Real Time Projects based on your technical back ground.
€šš Guidance in Resume preparation.
€šš All the Real Time interview Questions will be provided.
€šš Linux and SQL concepts will be covered as part of the course.
€šš Discussing the Interview Questions on a daily basis