Hadoop Training Institute in Hyderabad with Course Certification

Module 1 : Fundamental of Core Java

Module 2 : Fundamental of Basic SQL

Module 3: Introduction to BigData, Hadoop (HDFS and MapReduce) :
BigData Introduction
Hadoop Introduction
HDFS Introduction
MapReduce Introduction

Module 4 : Deep Dive in HDFS
HDFS Design
Fundamental of HDFS (Blocks, NameNode, DataNode, Secondary Name Node)
Read/Write from HDFS
HDFS Federation and High Availability
Parallel Copying using DistCp
HDFS Command Line Interface

Module 4A : HDFS File Operation Lifecycle (Supplementary)
1. File Read Cycel from HDFS
– DistributedFileSystem
– FSDataInputStream
2. Failure or Error Handling When File Reading Fails
3. File Write Cycle from HDFS
– FSDataOutputStream
4. Failure or Error Handling while File write fails

Module 5 : Understanding MapReduce :
JobTracker and TaskTracker
Topology Hadoop cluster
Example of MapReduce
– Map Function
– Reduce Function
Java Implementation of MapReduce
DataFlow of MapReduce
Use of Combiner

Module 6 : MapReduce Internals -1 (In Detail)
How MapReduce Works
Anatomy of MapReduce Job (MR-1)
Submission & Initialization of MapReduce Job (What Happen ?)
Assigning & Execution of Tasks
Monitoring & Progress of MapReduce Job
Completion of Job

Module 7 : Advanced MapReduce Algorithm
File Based Data Structure
– Sequence File
– MapFile
Default Sorting In MapReduce
– Data Filtering (Map-only jobs)
– Partial Sorting
Data Lookup Stratgies
– In MapFiles
Sorting Algorithm
– Total Sort (Globally Sorted Data)
– InputSampler
– Secondary Sort

Module 8 : Advanced MapReduce Algorithm -2
MapReduce Joining
– Reduce Side Join
– MapSide Join
– Semi Join
2. MapReduce Job Chaining
– MapReduce Sequence Chaining
– MapReduce Complex Chaining

Module 9 : Apache Pig
What is Pig ?
Introduction to Pig Data Flow Engine
Pig and MapReduce in Detail
When should Pig Used ?
Pig and Hadoop Cluster
Pig Interpreter and MapReduce
Pig Relations and Data Types
PigLatin Example in Detail
Debugging and Generating Example in Apache Pig

Module 9A : Apache Pig Coding
Working with Grunt shell
Create word count application
Execute word count application
Accessing HDFS from grunt shell

Module 9B : Apache Pig Complex Datatypes
Understand Map, Tuple and Bag
Create Outer Bag and Inner Bag
Defining Pig Schema

Module 9C : Apache Pig Data loading
Understand Load statement
Loading csv file
Loading csv file with schema
Loading Tab separated file
Storing back data to HDFS.

Module 9D : Apache Pig Statements

ForEach statement
Example 1 : Data projecting and foreach statement
Example 2 : Projection using schema
Example 3 : Another way of selecting columns using two dots ..

Module 9E : Apache Pig Complex Datatype practice
Example 1 : Loading Complex Datatypes
Example 2 : Loading compressed files
Example 3 : Store relation as compressed files
Example 4 : Nested FOREACH statements to solved same problem.

Module 10 : Fundamental of Apache Hive Part-1
What is Hive ?
Architecture of Hive
Hive Services
Hive Clients
how Hive Differs from Traditional RDBMS
Introduction to HiveQL
Data Types and File Formats in Hive
File Encoding
Common problems while working with Hive

Module 10A : Apache Hive
HiveQL
Managed and External Tables
Understand Storage Formats
Querying Data
– Sorting and Aggregation
– MapReduce In Query
– Joins, SubQueries and Views
5. Writing User Defined Functions (UDFs)
6. Data types and schemas
7. Querying Data
8. HiveODBC
9. User-Defined Functions

Module 11 : Step by Step Process creating and Configuring eclipse for writing MapReduce
Code
Module 12 : NOSQL Introduction and Implementation
What is NoSQL ?
NoSQL Characterise or Common Traits
Categories of NoSQL DataBases
– Key-Value Database
– Document DataBase
– Column Family DataBase
– Graph DataBase
4. Aggregate Orientation : Perfect fit for NoSQl
5. NOSQL Implementation
6. Key-Value Database Example and Use
7. Document DataBase Example and Use
8. Column Family DataBase Example and Use
9. What is Polyglot persistence ?

Module 12A : HBase Introduction
Fundamentals of HBase
Usage Scenerio of HBase
Use of HBase in Search Engine
HBase DataModel
– Table and Row
– Column Family and Column Qualifier
– Cell and its Versioning
– Regions and Region Server
5. HBase Designing Tables
6. HBase Data Coordinates
7. Versions and HBase Operation
– Get/Scan
– Put
– Delete

Module 13 : Apache Sqoop (SQL To Hadoop)
Sqoop Tutorial
How does Sqoop Work
Sqoop JDBCDriver and Connectors
Sqoop Importing Data
Various Options to Import Data
– Table Import
– Binary Data Import
– SpeedUp the Import
– Filtering Import
– Full DataBase Import Introduction to Sqoop

Module 14 : Apache Flume
Data Acquisition : Apache Flume Introduction
Apache Flume Components
POSIX and HDFS File Write
Flume Events
Interceptors, Channel Selectors, Sink Processor

Module 14A : Advanced Apache Flume
Sample Twiteer Feed Configuration
Flume Channel
– Memory Channel
– File Channel
3. Sinks and Sink Processors
4. Sources
5. Channel Selectors
6. Interceptors

Module 15 : Apache Spark : Introduction to Apache Spark
Introduction to Apache Spark
Features of Apache Spark
Apache Spark Stack
Introduction to RDD’s
RDD’s Transformation
What is Good and Bad In MapReduce
Why to use Apache Spark

Module 16 : Load data in HDFS using the HDFS commands

Module 17 : Importing Data from RDBMS to HDFS
Without Specifying Directory
With target Directory
With warehouse directory

Module 18 : Sqoop Import & Export Module
Importing Subset of data from RDBMS
Changing the delimiter during Import
Encoding Null values
Importing Entire schema or all tables