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Course summary

Introduction to BigData, Hadoop:-

Big Data Introduction
Hadoop Introduction
What is Hadoop? Why Hadoop?
Hadoop History?
Different types of Components in Hadoop?
HDFS, Map-Reduce, PIG, Hive, SQOOP, HBASE, OOZIE, Flume, Zookeeper and so on…ð
What is the scope of Hadoop?ð

Deep Drive in HDFS (for Storing the Data):-
Introduction of HDFSð
HDFS Designð
HDFS role in Hadoopð
Features of HDFSð
Daemons of Hadoop and its functionality
o Name Node
o Secondary Name Node
o Job Tracker
o Data Node
o Task Tracker
Anatomy of File Wrightð
Anatomy of File Readð
Network Topologyð
o Nodes
o Racks
o Data Center
Parallel Copying using DistCpð
Basic Configuration for HDFSð
Data Organizationð
o Blocks and
o Replication
Rack Awarenessð
Heartbeat Signalð
How to Store the Data into HDFSð
How to Read the Data from HDFSð
Accessing HDFS (Introduction of Basic UNIX commands)ð
CLI commandsð

MapReduce using Java (Processing the Data):-

The introduction of MapReduce.ð
MapReduce Architectureð
Data flow in MapReduceð
o Splits
o Mapper
o Portioning
o Sort and shuffle
o Combiner
o Reducer
Understand Difference Between Block and InputSplit
Role of RecordReader
Basic Configuration of MapReduce
MapReduce life cycle
How MapReduce Works
Writing and Executing the Basic MapReduce Program using Java
Submission & Initialization of MapReduce Job.
File Input/Output Formats in MapReduce Jobs
o Text Input Format
o Key Value Input Format
o Sequence File Input Format
o NLine Input Format
o Map-side Joins
o Reducer-side Joins
Word Count Example
Partition Map-Reduce Program
Side Data Distribution
o Distributed Cache (with Program)
Counters (with Program)
o Types of Counters
o Task Counters
o Job Counters
o User Defined Counters
o Propagation of Counters
Job Scheduling


Introduction to Apache PIG
Introduction to PIG Data Flow Engine
MapReduce vs. PIG in detail
When should PIG use?
Data Types in PIG
Basic PIG programming
Modes of Execution in PIG
o Local Mode and
o Map-Reduce Mode
Execution Mechanisms
o Grunt Shell
o Script
o Embedded
Operators/Transformations in PIG
PIG UDF’s with Program
Word Count Example in PIG
The difference between the Map-Reduce and PIG


Introduction to SQOOP
Use of SQOOP
Connect to mySql database
SQOOP commands
o Import
o Export
o Eval
o Codegen etc…
Joins in SQOOP
Export to MySQL
Export to HBase


Introduction to HIVE
HIVE Meta Store
HIVE Architecture
Tables in HIVE
o Managed Tables
o External Tables
Hive Data Types
o Primitive Types
o Complex Types
Joins in HIVE
HIVE UDF’s and UADF’s with Programs
Word Count Example


Introduction to HBASE
Basic Configurations of HBASE
Fundamentals of HBase
What is NoSQL?
HBase Data Model
Categories of NoSQL Data Bases
HBASE Architecture
How HBASE is differed from RDBMS
HDFS vs. HBase
Client-side buffering or bulk uploads
HBase Designing Tables
HBase Operations
o Get
o Scan
o Put
o Delete


What is MongoDB?
Where to Use?
Configuration On Windows
Inserting the data into MongoDB?
Reading the MongoDB data.

Cluster Setup:–

Downloading and installing the Ubuntu12.x
Installing Java
Installing Hadoop
Creating Cluster
Increasing Decreasing the Cluster size
Monitoring the Cluster Health
Starting and Stopping the Nodes



Introduction Zookeeper
Data Modal


Introduction to OOZIE
Use of OOZIE
Where to use?


Introduction to Flume
Uses of Flume
Flume Architecture
o Flume Master
o Flume Collectors
o Flume Agents

Project Explanation with Architecture

Section 1
Hadoop is an Apache open source framework written in java that allows distributed processing of large datasets across clusters of computers using simple programming models. A Hadoop frame-worked application works in an environment that provides distributed storage and computation across clusters of computers.
Section 2
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Level Master
Institution CoreLogic Technologies

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