Hadoop Admin Training in Bangalore

Hadoop training course content and Syllabus

• Hadoop Overview, Architecture Considerations, Infrastructure, Platforms and Automation
• Use case walkthrough
• ETL
• Log Analytics
• Real Time Analytics

• NoSQL Introduction
• Traditional RDBMS approach
• NoSQL introduction
• Hadoop & Hbase positioning
• Hbase Introduction
• What it is, what it is not, its history and common use-cases
• Hbase Client Shell, exercise
• Hbase Architecture
• Building Components
• Storage, B+ tree, Log Structured Merge Trees
• Region Lifecycle
• Read/Write Path
• Hbase Schema Design
• Introduction to hbase schema
• Column Family, Rows, Cells, Cell timestamp
• Deletes
• Exercise – build a schema, load data, query data
• Hbase Java API Exercises
• Connection
• CRUD API
• Scan API
• Filters
• Counters
• Hbase MapReduce
• Hbase Bulk load
• Hbase Operations, cluster management
• Performance Tuning
• Advanced Features
• Exercise
• Recap and Q&A
• MapReduce for Developers

• Traditional Systems / Why Big Data / Why Hadoop
• Hadoop Basic Concepts/Fundamentals
• Hadoop in the Enterprise
• Where Hadoop Fits in the Enterprise
• Review Use Cases
• Architecture
• Hadoop Architecture & Building Blocks
• HDFS and MapReduce
• Hadoop CLI
• Walkthrough
• Exercise
• MapReduce Programming
• Fundamentals
• Anatomy of MapReduce Job Run
• Job Monitoring, Scheduling
• Sample Code Walk Through
• Hadoop API Walk Through
• Exercise
• MapReduce Formats
• Input Formats, Exercise
• Output Formats, Exercise
• Hadoop File Formats

• MapReduce Algorithms
• Walkthrough of 2-3 Algorithms
• MapReduce Features
• Counters, Exercise
• Map Side Join, Exercise
• Reduce Side Join, Exercise
• Sorting, Exercise
• Use Case A (Long Exercise)
• Input Formats, Exercise
• Output Formats, Exercise
• MapReduce Testing 
• Hadoop Ecosystem
• Oozie
• Flume
• Sqoop
• Exercise 1 (Sqoop)
• Streaming API
• Exercise 2 (Streaming API)
• Hcatalog
• Zookeeper
• HBase Introduction
• Introduction
• HBase Architecture
• MapReduce Performance Tuning

• Hadoop Fundamentals and Architecture
• Why Hadoop, Hadoop Basics and Hadoop Architecture
• HDFS and Map Reduce
• Hadoop Ecosystems Overview
• Hive
• Hbase
• ZooKeeper
• Pig
• Mahout
• Flume
• Sqoop
• Oozie
• Hardware and Software requirements
• Hardware, Operating System and Other Software
• Management Console
• Deploy Hadoop ecosystem services
• Hive
• ZooKeeper
• HBase
• Administration
• Pig
• Mahout
• Mysql
• Setup Security
• Enable Security Configure Users, Groups, Secure HDFS, MapReduce, HBase and Hive
• Configuring User and Groups
• Configuring Secure HDFS
• Configuring Secure MapReduce
• Configuring Secure HBase and Hive
• Manage and Monitor your cluster

• Hadoop Overview
• Why Hadoop
• Hadoop Basic Concepts
• Hadoop Ecosystem MapReduce, Hadoop Streaming, Hive, Pig, Flume, Sqoop, Hbase, Oozie, Mahout
• Where Hadoop fits in the Enterprise
• Review use cases
• Apache Hive & Pig for Developers

• Big Data and the Distributed File System
• MapReduce
• Hive Introduction
• Why Hive?
• Compare vs SQL
• Use Cases
• Hive Architecture Building Blocks
• Hive CLI and Language (Exercise)
• HDFS Shell
• Hive CLI
• Data Types
• Hive Cheat-Sheet
• Data Definition Statements
• Data Manipulation Statements
• Select, Views, GroupBy, SortBy/DistributeBy/ClusterBy/OrderBy, Joins
• Built-in Functions
• Union, Sub Queries, Sampling, Explain
• Hive Usecase implementation – (Exercise)
• Use Case 1
• Use Case 2
• Best Practices
• Advance Features
• Transform and Map-Reduce Scripts
• Custom UDF
• UDTF
• SerDe
• Recap and Q&A
• Pig Introduction
• Position Pig in Hadoop ecosystem
• Why Pig and not MapReduce
• Simple example (slides) comparing Pig and MapReduce
• Who is using Pig now and what are the main use cases
• Pig Architecture
• Discuss high level components of Pig
• Pig Grunt – How to Start and Use
• Pig Latin Programming
• Data Types
• Cheat sheet
• Schema
• Expressions
• Commands and Exercise
• Load, Store, Dump, Relational Operations, Foreach, Filter, Group, Order By, Distinct, Join, Cogroup, Union, Cross, Limit, Sample, Parallel
• Use Cases (working exercise)
• Use Case 1
• Use Case 2
• Use Case 3 (compare pig and hive)
• Advanced Features, UDFs

• Mahout & Machine Learning
• Mahout Overview
• Mahout Installation
• Introduction to the Math Library
• Vector implementation and Operations (Hands-on exercise)
• Matrix Implementation and Operations (Hands-on exercise)
• Anatomy of a Machine Learning Application
• Classification
• Introduction to Classification
• Classification Workflow
• Feature Extraction
• Classification Techniques (Hands-on exercise)
• Evaluation (Hands-on exercise)
• Clustering
• Use Cases
• Clustering algorithms in Mahout
• K-means clustering (Hands-on exercise)
• Canopy clustering (Hands-on exercise)
• Clustering
• Mixture Models
• Probabilistic Clustering Dirichlet (Hands-on exercise)
• Latent Dirichlet Model (Hands-on exercise)
• Evaluating and Improving Clustering quality (Hands-on exercise)
• Distance Measures (Hands-on exercise)
• Recommendation Systems
• Overview of Recommendation Systems
• Use cases
• Types of Recommendation Systems
• Collaborative Filtering (Hands-on exercise)
• Recommendation System Evaluation (Hands-on exercise)
• Similarity Measures
• Architecture of Recommendation Systems
• Wrap Up