Course - Overview

In today's date all large size companies have huge amount and data and growing day by day
e.g. Facebook, Youtube, Twitter etc have generated in data over Petabytes
Hence Limitation have occured in Conventional Storage Systems including Well Know Databases like Oracle, DB2 etc. Again faster processing of such a large data is an issue
This is Scenario Where Bigdata technologies like Hadoop comes into picture
Hadoop provides many modules to quickly save and retrieve with security without data losage and its FREE !

HADOOP (BIG DATA) Course Syllabus - Learn 11 Technologies

25%

Hadoop Core

25%

Core Technologies

SQOOP
- Installation
- Import Data
  - Full table
  - Only Subset
  - Target Directory
  - protecting Password
  - File format other than CSV
  - Compressing
  - Control Parallelism
  - All tables Import
- Export data to RDBMS,HIVE and HBASE
- Hands on Exercises.
FLUME
- Installation
- Introduction to Flume
- Flume Agents: Sources, Channels and Sinks
- Flume Commands
- Single agent example
- Three Agent Example
- Case Study on Twitter
Map Reduce
- Functional Programming Basics
- Map and Reduce Basics
- Anatomy of a Map Reduce Job Run
- Architecture
- Job Completion, Failures
- Shuffling and Sorting
- Splits, Record reader, Partition, Types of partitions & Combiner
- Speculative Execution
- Types of Schedulers and Counters
- YARN
- Sequential Files and Map Files
- Hands on “Word Count” in Map/Reduce in standalone and Pseudo distribution Mode

25%

Database & Related Technologies

Hive
- Installation
- Introduction and Architecture
- Hive Services, Hive Shell, Hive Server and Hive Web Interface (HWI)
- Meta store
- Hive QL
- Derby Database
- Working with Tables
- Primitive data types and complex data types
- Working with Partitions
- Hive Bucketed Tables and Sampling
- External partitioned tables
- Differences between ORDER BY, DISTRIBUTE BY and SORT BY
- Log Analysis on Hive
- Hands on Exercises
Pig
- Installation
- Execution Types
- Grunt Shell
- Pig Latin
- Data Processing
- Schema on read
- Primitive data types and complex data types
- Tuple schema, BAG Schema and MAP Schema.
- Loading and Storing
- Filtering
- Grouping & Joining
- Working with Functions
- Types of JOINS in pig and Replicated Join in detail
- SPLITS
- Error Handling, FLATTEN and ORDER BY
- User Defined Functions, Dynamic Invokers and Macros
- Hands on Exercises

25%

Highly Advanced Concepts

NOSQL
- ACID in RDBMS and BASE in NoSQL
- CAP Theorem and Types of Consistency
- Types of NoSQL Databases in detail
- Columnar Databases in Detail
HBase
- HBase Installation
- HBase concepts
- HBase Data Model and Comparison between RDBMS and NOSQL
- Master & Region Servers
- HBase Operations (DDL and DML) through Shell and Programming and HBase Architecture
- Catalog Tables
- Block Cache and sharing
- SPLITS
- DATA Modeling
- HBASE Filters
- Bulk Loading and Coprocessors
- Real world use case consisting of HDFS, MR and HBASE
FREE MODULE MongoDB