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Hadoop Training (Hadoop Developer Training and Hadoop Administrator Training)

Hadoop Training

Training Key Features 1. 24/7 Course Access 2. As interactive as Classroom training 3. Very Cost effective 4. No PPT's at all, advanced way of teaching 5. In depth explaination of each topic 6. Includes Hands On Session on Amazon EC2 cloud (So no need to setup at home machine for practice)

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Module 1 :  Introduction to BigData, Hadoop (HDFS and MapReduce) : Available (Length 35 Minutes)

1. BigData Inroduction
2. Hadoop Introduction
3. HDFS Introduction
4. MapReduce Introduction

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Module 2 :  Deep Dive in HDFS : Available (Length 48 Minutes)

1. HDFS Design
2. Fundamental of HDFS (Blocks, NameNode, DataNode, Secondary Name Node)
3. Rack Awareness
4. Read/Write from HDFS
5. HDFS Federation  and High Availability
6. Parallel Copying using DistCp
7. HDFS Command Line Interface
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Module 3 : Understanding MapReduce : Available (Length 60 Minutes)
1. JobTracker and TaskTracker
2. Topology Hadoop cluster
3. Example of MapReduce
Map Function
Reduce Function
4. Java Implementation of MapReduce
5. DataFlow of MapReduce
6. Use of Combiner

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Module 4 : MapReduce Internals -1 (In Detail) : Available (Length 57 Minutes)

1. How MapReduce Works
2. Anatomy of MapReduce Job (MR-1)
3. Submission & Initialization of MapReduce Job (What Happen ?)
4. Assigning & Execution of Tasks
5. Monitoring & Progress of MapReduce Job
6. Completion of Job
7. Handling of MapReduce Job
- Task Failure
- TaskTracker Failure
- JobTracker Failure

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Module 5 : MapReduce-2 (YARN : Yet Another Resource Negotiator) : Available (Length 52 Minutes)

1. Limitation of Current Architecture (Classic)
2. What are the Requirement ?
3. YARN Architecture
4. JobSubmission and Job Initialization
5. Task Assignment and Task Execution
6.  Progress and Monitoring of the Job
7.  Failure Handling in YARN
- Task Failure
- Application Master Failure
- Node Manager Failure
- Resource Manager Failure

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Module 6 : Advanced Topic for MapReduce (Performance and Optimization) : Available (Length 58 Minutes)

1. Job Sceduling
2. In Depth Shuffle and Sorting
3. Speculative Execution
4. Output Committers
5. JVM Reuse in MR1
6. Configuration and Performance Tuning

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Module 7 : Advanced MapReduce Algorithm : Available (Length 87 Minutes)

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

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Module 8 : Advanced MapReduce Algorithm -2 : Available : Private (Length 67 Minutes)

1. MapReduce Joining
- Reduce Side Join
- MapSide Join
- Semi Join
2. MapReduce Job Chaining
- MapReduce Sequence Chaining
- MapReduce Complex Chaining

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Module 9 : Features of MapReduce : Available : Private (Length 61 Minutes)

Introduction to MapReduce Counters
    Types of Counters
    Task Counters
    Job Counters
    User Defined Counters
    Propagation of Counters
Side Data Distribution
    Using JobConfiguration
    Distributed Cache
    Steps to Read and Delete Cache File

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Module 10: MapReduce DataTypes and Formats : Available : Private (Length 77 Minutes)
      1.Serialization In Hadoop
      2. Hadoop Writable and Comparable
      3. Hadoop RawComparator and Custom Writable
      4. MapReduce Types and Formats
      5. Understand Difference Between Block and InputSplit
      6. Role of RecordReader
      7. FileInputFormat
      8. ComineFileInputFormat and Processing whole file Single Mapper
      9. Each input File as a record
    10. Text/KeyValue/NLine InputFormat
    11. BinaryInput processing
    12. MultipleInputs Format
    13. DatabaseInput and Output
    14. Text/Biinary/Multiple/Lazy OutputFormat MapReduce Types

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Module 11 : Apache Pig : Available (Length 52 Minutes)

1. What is Pig ?
2. Introduction to Pig Data Flow Engine
3. Pig and MapReduce in Detail
4. When should Pig Used ?
5. Pig and Hadoop Cluster
6. Pig Interpreter and MapReduce
7. Pig Relations and Data Types
8. PigLatin Example in Detail
9. Debugging and Generating Example in Apache Pig

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Module 12 : Fundamental of Apache Hive Part-1 : Available (Length 60 Minutes)

1. What is Hive ?
2. Architecture of Hive
3. Hive Services
4. Hive Clients
5. how Hive Differs from Traditional RDBMS
6. Introduction to HiveQL
7. Data Types and File Formats in Hive
8. File Encoding
9. Common problems while working with Hive
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Module 13 : Apache Hive : Available (Length 73 Minutes )
1. HiveQL
2. Managed and External Tables
3. Understand Storage Formats
4. Querying Data
- Sorting and Aggregation
- MapReduce In Query
- Joins, SubQueries and Views
5. Writing User Defined Functions (UDFs)
3. Data types and schemas
4. Querying Data
5. HiveODBC
6. User-Defined Functions

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Module 14 : Single Node Hadoop Cluster Set Up In Amazon Cloud : Available (Length 60 Minutes Hands On Practice Session)
1. � How to create instance on Amazon EC2
2. � How to connect that Instance Using putty
3. � Installing Hadoop framework on this instance
4. � Run sample wordcount example which come with Hadoop framework.
In 30 minutes you can create Hadoop Single Node Cluster in Amazon cloud, does it interest you ?

Video URL :

Module 15 : Hands On : Implementation of NGram algorithm : Available (Length 48 Minutes Hands On Practice Session)
1. Understand the NGram concept using (Google Books NGram )
2. Step by Step Process creating and Configuring eclipse for writing MapReduce Code
3. Deploying the NGram application in Hadoop Installed in Amazon EC2
4. Analyzing the Result by Running NGram application (UniGram, BiGram, TriGram etc.)

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Module 16 : HBase : In Progress 
1. Introduction to HBase,
2. Schema Design
3. Cluster Architecture
4. HBase Components
 - RegionServer
 - Region
 - ZooKeeper
 - Master
 - Catalog Tables
5. Usage Scenerio of HBase

Video URL : In Progress

Module 17 :  Sqoop : In Progress 
1. Introduction to Sqoop
2. Database Imports
3. Database Export

Video URL : In Progress 

Module 18 :  ZoopKeeper  : In Progress
1. Introduction ZooKeeper
2. Data Modal
3. Operations
4. Implementation
5. Consistency
6. Sessions
7. States

Video URL : In Progress

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