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HADOOP

What is Big Data?

1
What is Hadoop?
2
Relation between Big Data and Hadoop.
3
What is the need of going ahead with Hadoop?
4
Scenarios to apt Hadoop Technology in REAL TIME Projects
5
Challenges with Big Data
6
Storage
7
Processing
8
How Hadoop is addressing Big Data Challenges
9
Comparison with Other Technologies
10
RDBMS
11
Data Warehouse
12
Tera Data
13
Different Components of Hadoop Echo System
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Storage Components
15
Processing Components
16
HDFS (Hadoop Distributed File System)
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HDFS (Hadoop Distributed File System)
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Cluster Vs Hadoop Cluster.
19
Significance of HDFS in Hadoop
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Features of HDFS
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Storage aspects of HDFS
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Block
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How to Configure block size
24
Default Vs configurable block size
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Why HDFS block size is so large
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Design Principles of block size
27
HDFS Architecture 5 demons of Hadoop
28
Name Node and its functionality
29
Data node and its functionality
30
Job Tracker and its functionality
31
Task Track and its functionality
32
Secondary Name Node and its functionality
33
Replication in Hadoop – Fail Over Mechanism
34
Data Storage in Data Nodes
35
Fail Over Mechanism in Hadoop – Replication
36
Replication Configuration
37
Custom Replication
38
Design Constraints with Replication Factor
39
Accessing HDFS
40
CLI (Command Line Interface) and HDFS Commands
41
Java Based Approach

Map Reduce

1
Why Map Reduce is essential in Hadoop?
2
Processing Daemons of Hadoop
3
Job Tracker
4
Roles Of Job Tracker
5
Drawbacks w.r.to Job Tracker failure in Hadoop Cluster
6
How to configure Job Tracker in Hadoop Cluster
7
Task Tracker
8
Roles of Task Tracker
9
Drawbacks w.r.to Task Tracker Failure in Hadoop Cluster

Input Split

1
Input Split
2
Need Of Input Split in Map Reduce
3
Input Split Size
4
Input Split Size Vs Block Size
5
Input Split Vs Mappers

Map Reduce Life Cycle

1
Communication Mechanism of Job Tracker and Task Tracker
2
Input Format Class
3
Record Reader Class
4
Success Case Scenarios
5
Failure Case Scenario
6
Retry Mechanism in Map Reduce

Map Reduce Programming Model

1
Different phases of Map Reduce Algorithm
2
Different Data types in Map Reduce
3
Primitive Data types Vs Map Reduce Data types
4
How to write basic Map Reduce Program
5
Driver Code
6
Mapper Code
7
Reducer Code
8
Driver Code
9
Importance of Driver Code in a Map Reduce program
10
How to Identify the Driver Code in Map Reduce program
11
Different sections of Driver code
12
Mapper Code
13
Importance of Mapper Phase in Map Reduce
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How to Write a Mapper Class?
15
Methods in Mapper Class
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Reducer Code
17
Importance of Reduce phase in Map Reduce
18
How to Write Reducer Class?
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Methods in Reducer Class
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IDENTITY MAPPER
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Input Format’s in Map Reduce
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Text Input Format
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Key Value Text Input Format
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NL line Input Format
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DB input Format
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Sequence File input Format
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How to use the specific input format in Map Reduce
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Output Format’s in Map Reduce
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Text Output Format
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Key Value Text Output Format
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N Line Output Format
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DB Output Format
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Sequence File Output Format
34
How to use the specific Output format in Map reduce
35
Map Reduce API(Application Programming
36
New API
37
Deprecated API
38
Combiner in Map Reduce
39
Is combiner mandate in Map Reduce
40
How to use the combiner class in Map Reduce
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Performance tradeoffs w.r.to Combiner
42
Partitioner in Map Reduce
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Importance of Pratitioner class in Map Reduce
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How to use the Partitioner class in Map Reduce
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hash Partitioner functionality
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How to write a custom Partitioner
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Compression techniques in Map Reduce
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Importance of Compression in Map Reduce
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What is CODEC
50
Compression Types
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Gzip Codec
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Bzip Codec
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LZO Codec
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Snappy Codec
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Configurations w.r.to Compression Techniques
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How to customize the Compression per one job Vs all the job Joins – in Map Reduce
57
Map Side Join
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Reduce Side Join
59
Performance Trade Off
60
Distributed cache
61
How to debug Map Reduce Jobs in Local and Pseudo cluster Mode.
62
Introduction to Map Reduce Streaming
63
Data localization in Map Reduce

Apache PIG

1
Introduction to Apache Pig
2
Map Reduce Vs Apache Pig
3
SQL Vs Apache Pig
4
Different data types in Pig
5
Modes Of Execution in Pig
6
Local Mode
7
Map Reduce OR Distributed Mode
8
Execution Mechanism
9
Grunt Shell
10
Script
11
Embedded
12
Transformations in Pig
13
How to write a simple pig script
14
How to develop the Complex Pig Script
15
Bags, Tuples and fields in PIG
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UDFs in Pig
17
Need of using UDFs in PIG
18
How to use UDFs
19
REGISTER Key word in PIG
20
When to use Map Reduce

HIVE

1
Hive Introduction
2
Need of Apache HIVE in Hadoop
3
Hive Architect
4
Driver
5
Compiler
6
Executor(Semantic Analyzer)
7
Meta Store in Hive
8
Importance Of Hive Meta Store
9
Embedded Meta store configuration
10
External Meta store configuration
11
Communication mechanism with Meta store
12
Hive Integration with Hadoop
13
Hive Query Language (Hive QL)
14
Configuring Hive with MySQL Meta Store
15
SQL VS Hive QL
16
Data Slicing Mechanisms
17
Partitions In Hive
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Buckets In Hive
19
Partitioning Vs Bucketing
20
Real Time Use Cases
21
Collection Data Types in HIVE
22
Array
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Struct
24
Map
25
User Defined Functions (UDFs) in HIVE
26
UDFs
27
UDAFs
28
UDTFs
29
Need of UDFs in HIVE
30
Hive Serializer / Deserializer SerDe
31
HIVE – HBASE Integration

SQOOP

1
Introduction to sqoop
2
MySQL client and Server Installation
3
How to connect to Relational database using Sqoop
4
Different Sqoop Commands
5
Different flavors of Import’s
6
Export
7
Hive-Imports

HBASE

1
HBASE Introduction
2
HDFS Vs H Base
3
H base use cases
4
H base basics
5
Column families
6
Scans
7
H Base Architecture
8
Clients
9
REST
10
Thrift
11
Java Based
12
Avro
13
Map Reduce Integration
14
Map Reduce over H Base
15
H Base Admin
16
Schema Definition
17
Basic CRUD Operations

Flume

1
Flume Introduction
2
Flume Architecture
3
Flume Master, Flume Collector and Flume Agent
4
Flume Configurations
5
Real Time Use Case using Apache Flume

Oozie

1
Oozie Introduction
2
Oozie Architecture
3
Oozie Configuration Files
4
Oozie Job Submission
5
Workflow.xml
6
Coordinator: xml
7
Job .coordination properties

YARN (Yet Another Resource Negotiator) -

1
Next Gen. Map Reduce
2
What is YARN?
3
YARN Architecture
4
Resource Manager
5
Application Master
6
Node Manager
7
When should we go ahead with YARN
8
Classic Map Reduce Vs YARN Map Reduce
9
Different Configuration Files for YARN

Impala

1
What is Impala?
2
How can we use Impala for Query Processing
3
When should we go ahead with Impala
4
HIVE Vs Impala
5
REAL TIME Use Case with Impala

Mongo DB (No SQL Database)

1
Need of No SQL Databases
2
Relational Vs Non-Relational Databases
3
Introduction to Mongo DB
4
Features of Mongo DB
5
Installation of Mongo DB
6
Mongo DB Basic operations

Overview of Kafka

1
Topics.
2
Producers
3
Consumers.
4
Brokers.

Overview of Spark

1
Scala
2
Spark SQL
3
Joins using spark SQL.

Hadoop Administration

1
Hadoop Single Node Cluster Set Up (Hands on Installation on Laptops)
2
Operating System Installation
3
JDK Installation
4
SSH Configuration
5
Dedicated Group
6
Hadoop Installation
7
Different Configuration Files Setting
8
Name node format
9
Starting the Hadoop Daemons
10
Multi Node Hadoop Cluster Set Up (Hands on Installation on Laptops) )
11
Network related settings
12
Hosts Configuration
13
Password less SSH Communication
14
Hadoop Installation
15
Configuration Files Setting
16
Name Node Format
17
Starting the Hadoop Daemons
18
PIG Installation (Hands on Installation on Laptops)
19
Local Mode
20
Clustered Mode » Bashrc file configuration
21
SQOOP Installation (Hands on Installation on Laptops)
22
Sqoop installation with MySQL Client
23
HIVE Installation (Hands on Installation on Laptops)
24
Local Mode
25
Clustered Mode
26
H base Installation (Hands on Installation on Laptops)
27
Local Mode » Clustered Mode
28
OOZIE Installation (Hands on Installation on Laptops)
29
Mongo DB Installation (Hands on Installation on Laptops)
30
Commissioning of Nodes In Hadoop Cluster
31
Decommissioning of Nodes from Hadoop Cluster
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