Live Technoworld is best institute learning of Big Data Handoop. The "Big data Hadoop" creates open-source software for dependable, scalable, spread computing. Bigdata Hadoop has been the dynamic force behind the enlargement of the big data production. Hadoop brings the aptitude to inexpensively process large amounts of data, regardless of its construction. By large, we indicate from 10-100 gigabytes and above. A learner gets the likelihood to learn all technical details.
Overview of the course:
Hadoop Development is a one-stop course that introduces you to the domain of hadoop development as well as gives you technical knowhow of the same. At the end of this course you will be able to earn a credential of hadoop professional and you will be capable of dealing with Terabyte scale of data and analyze it successfully using mapreduce
Who this course is for and not for?
For: Typically professionals with basic knowledge of software development, programming languages, and databases will find this course really helpful. Basic knowledge should be enough to succeed at this course
Not For: Students who are absolute beginners at software development as a discipline will find it difficult to follow the course
Phase 1: Hadoop Fundamentals Getting the Basics Rights 1. Big Data
What is Big Data
Dimensions of Big Data
Big Data in Advertising
Big Data in Banking
Big Data in Telecom
Big Data in eCommerce
Big Data in Healthcare
Big Data in Defense
Processing options of Big Data
Hadoop as an option
2. Hadoop
What is Hadoop 2.0
How Hadoop 2.0 Works
HDFS
Mapreduce
How Hadoop has an edge
3. HDFS
How storage works
Storage configuration
Role of Namenode
Role of Datanode
Role of Seconadary Namenode
Classic Mode
High Availability Mode
Zookeeper
4. MapReduce
What is MapReduce
Mapper class
Reducer class
Shuffle and Sort
Role of combiner
Role of partitioner
Phase 1: Hadoop Fundamentals
Getting Hands On
5. Hadoop Ecosystem
Sqoop
Oozie
Pig
Hive
Flume
6. Hadoop Hands On- Lab
Setting up Hadoop on a Single node cluster
Running HDFS commands
Running your Mapreduce program
Running Sqoop Import and Sqoop Export
Creating Hive tables directly from Sqoop
Creating Hive tables
Querying Hive tables
7. Multinode Setup
Setting up Multinode setup
Phase 2: Hadoop Development
Become a Pro developer
8. Advanced Mapreduce
Mapreduce Code Walkthrough
ToolRunner
MR Unit
Distributed Cache
Combiner
Partitioner
Setup and Cleanup methods
Using Java API to access HDFS
Map Side joins
Reduce side joins
Input Types in Mapreduce
Output Types in Mapreduce
Custom Input Data types
Custom Output Data types
Multiple reducer MR program
Zero Reducer Mapper Program
9. Advanced Mapreduce Hands On- Lab
MR Unit hands On
Distributed Cache hands On
Partitioner hands On
Combiner hands On
Accessing files using HDFS API hands on
Map Side joins hands on
Reduce side joins hands on
10. Mapreduce Design Patterns:- Lab
Searching
Sorting
Filtering
Inverted Index
Phase 2: Hadoop Data Analysis
Become a Pro data analyst
11. Pig
Introduction
Basic Data Analysis
Complex Data Analysis
Multi Data Set Analysis
UDFs in Pig
Troubleshooting and Optimizing Pig
12. Pig- Labs
Pig Hands On
Extending Pig
13. Hive
Introduction
Basic Data Analysis with Hive
Hive Data Management
Text Processing with Hive
Transformations in Hive
Optimizing Hive
14. Hive- Labs
Hive Hands On
Extending Hive Program
15. HData Analysis Using Pentaho as an ETL tool- Lab
