Best Hadoop Training Provider is www.HadoopExam.com (Very less price and Best Quality)
First two modules are free (Best Quality is Promise, watch it right now)
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
Video URL : http://www.youtube.com/watch?v=R-qjyEn3bjs
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
Video URL : http://www.youtube.com/watch?v=PK6Im7tBWow
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
Video URL : Watch Private Video
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
Video URL : Watch Private Video
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
Video URL : Watch Private Video
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
Video URL : Watch Private Video
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
Video URL : Watch Private Video
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
Video URL : Watch Private Video
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
Video URL : Watch Private Video
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
Video URL : Watch Private Video
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
Video URL : Watch Private Video
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
Video URL : Watch Private Video
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
Video URL : Watch Private Video
Module 14 : Hands On : 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 : Watch Private Video
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.)
Video URL : Watch Private Video
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
First two modules are free (Best Quality is Promise, watch it right now)
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
Video URL : http://www.youtube.com/watch?v=R-qjyEn3bjs
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
Video URL : http://www.youtube.com/watch?v=PK6Im7tBWow
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
Video URL : Watch Private Video
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
Video URL : Watch Private Video
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
Video URL : Watch Private Video
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
Video URL : Watch Private Video
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
Video URL : Watch Private Video
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
Video URL : Watch Private Video
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
Video URL : Watch Private Video
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
Video URL : Watch Private Video
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
Video URL : Watch Private Video
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
Video URL : Watch Private Video
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
Video URL : Watch Private Video
Module 14 : Hands On : 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 : Watch Private Video
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.)
Video URL : Watch Private Video
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
