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Hadoop Online Training by top trainers with placement assurance

Course Overview

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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

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