Learn Data Science – Big data: Hadoop

Course Name: – Learn Data Science – Big data: Hadoop

Date: – Sat 07th Sep and Sun 08th Sep 2019.

Cost: – 

Booking between 27 Jul to 17 Aug 2019 – 1000 INR discount, you pay 6000 INR
Booking between 18 Aug to 31 Aug 2019 – 500 INR discount, you pay 6500 INR
Booking between 01 Sep to 06 Sep 2019  – 0 INR discount, you pay 7000 INR

How to Join?

Click Here

Key Features

      • No PPT’s completely Hands-on Apache Hadoop training.
      • Tea/Coffee as refreshment will be provided.
      • All at only 7000 INR
      • Installation required in your laptop for training
        • Ubuntu Virtual Machine Images for VirtualBox and VMware download link, get from here

Day 1 – First Day

1st Hour Introduction to Hadoop (1 hr)
Hadoop Distributed File System
Hadoop Architecture
Map Reduce & HDFS Hadoop Eco Systems
Introduction to Pig
Introduction to Hive
Introduction to HBase
Other eco system Map
HDFS: Hadoop Distributed File System:
– Significance of HDFS in Hadoop
• Features of HDFS
Name Node, Secondary Name Node and its functionality
2nd Hour Data Storage in Hadoop (1 hr)
Data Storage in HDFS
Introduction about Blocks
Data replication
• Accessing HDFS
• Fault tolerance
• Installation and set-up of Hadoop
Start-up & Shut down process
3rd Hour Map Reduce: (1 hr)
• Map Reduce Story
• Map Reduce Architecture
• How Map Reduce works
• Developing Map Reduce
• Map Reduce Programming Model
4th Hour Input and Output Formats (1 hr)
• Creating Input and Output Formats in Map Reduce Jobs
Text Input Format
Key Value Input Format
Sequence File Input Format
Data localization in Map Reduce
Moving the Data into Hadoop
5th Hour Reading and Writing the files in HDFS using Java program (1 hr)
The Hadoop Java API for MapReduce
Mapper Class
Reducer Class
Driver Class
Writing Basic MapReduce Program In java
Understanding the MapReduce Internal Components
6th Hour Exploring more – Hadoop (30 mins)
7th & 8th Hour PIG (2 hrs)
• Introduction to Apache Pig
• Map Reduce vs. Apache Pig
• SQL vs. Apache Pig
• Different data types in Pig
• Modes of Execution in Pig
• Grunt shell
• Loading data
• Exploring Pig

Day 2 – Next Day

1st to 3rd Hour HIVE: (3 hrs)
• Hive introduction
• Hive architecture
• Hive vs. RDBMS
• HiveQL and the shell
• Managing tables (external vs managed)
• Data types and schemas
• Partitions and buckets
4th and 5th Hour HBASE: (2 hrs)
• Architecture and schema design
• HBase vs. RDBMS
• HMaster and Region Servers
• Column Families and Regions
• Write pipeline
• Read pipeline
• HBase commands
6th to 8th Hour Deep dive into Apache Flume & Sqoop (3 hrs)