HADOOP FOR DEVELOPERS AND ADMINISTRATORS HADOOP FOR DEVELOPERS AND ADMINISTRATORS SYLLABUS COURSE C IN PUNE

Hadoop for Developers and Administrators

Hadoop for Developers and Administrators Syllabus COURSE CONTENT
Traning at hadoop school of training Magarpatta city Pune.
(+91-93257-93756) www.hadoopschooloftraining.co.in

Next level of development and administration

Schedule:
Day 1:BigData
• Why is Big Data important
• What is Big Data
• Characteristics of Big Data
• How did data become so big
• Why should you care about Big Data
• Use Cases of Big Data Analysis
• What are possible options for analyzing big data
• Traditional Distributed Systems
• Problems with traditional distributed systems
• What is Hadoop
• History of Hadoop
• How does Hadoop solve Big Data problem
• Components of Hadoop
• What is HDFS
• How HDFS works
• What is Mapreduce
• How Mapreduce works
• How Hadoop works as a system
Day2: Hadoop ecosystem
• Pig
• What is Pig
• How it works
• An example
• Hive
• What is Hive
• How it works
• An example
• Flume
• What is Flume
• How it works
• An example
• Sqoop
• What is Sqoop
• How it works
• An example
• Oozie
• What is Oozie
• How it works
• An example
• HDFS in detail
• Map Reduce in details
Day3: Hands On-¬‐
• VMsetup
• Setting up Virtual Machine
• Installing Hadoop in Pseudo Distributed mode
Day 4:
Hands On-¬‐
• Programs
• Running your first MapReduce Program
• Sqoop Hands on
• Flume Hands
Day 5:
• Multinode cluster setup
• Setting up a multimode cluster
Day 6:
• Planning your Hadoop cluster
• Considerations for setting up Hadoop Cluster
• Hardware considerations
• Software considerations
• Other considerations
Day 7: Disecting the Wordcount Program
• Understanding the Driver
• Understanding the Mapper
• Understanding the Reducer
Day 8:
• Diving deeper into MapReduce
• API
• Understanding combiners
• Understanding partitioners
• Understanding input formats
• Understanding output formats
• Distributed Cache
• Understanding Counters
Day 9:
• Common Mapreduce patterns
• Sorting Serching
• Inverted Indexes
Day 10:
• Common Mapreduce patterns
• TF-IDF
• Word-Cooccurance
Day 11:
• Hands on Mapreduce
Day 12:
• Hands on Mapreduce
Day 13:
• Introduction to Pig and Hive
• Pig program structure and execution process
• Joins
• Filtering
• Group and Co-Group
• Schema merging and redefining schema
• Pig functions
• Motivation and Understanding Hive
• Using Hive Command line Interface
• Data types and File Formats
• Basic DDL operations
• Schema Design
Day 14:
• Hands on Hive and Pig
Day 15:
• Advanced Hadoop Concepts
• Yarn
• Hadoop Federation
• Authntication in Hadoop
• High Availbability
Day 16:
• Administration Refresher
• Setting up hadoop cluster - Considerations
• Most important configurations
• Installation options
Day 17:
• Scheduling in Hadoop
• FIFO Scheduler
• Fair Scheduler
Day 18:
• Monitoring your Hadoop Cluster
• Monitoring tools available
• Ganglia
• Monitoring best practices
Day 19:
• Administration Best practices
• Hadoop Administration best practices
• Tools of the trade
Day 20:
• Test
• Test – 50 questions test (20- Development releated, 20-
• Administration related and 10 Hadoop in General

Please Contact-

Hadoop School of Training
Destination Center, Second Floor
Magarpatta City
Pune: 411013

Phone:
India: +91-93257-93756
USA: 001-347-983-8512

www.hadoopschooloftraining.co.in
Email: learninghub01@gmail.com
Skype: learning.hub01