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Best Hadoop Admin Training in Bangalore

TecMax is one of the leading Hadoop Admin Training Institute in Bangalore. Certified experts at TecMax are real-time consultants at multinational companies and have more than 5+ years of experience in Hadoop Admin Training. Our Trainers have conducted more than 200 classes and have extensive experience in teaching Hadoop Admin in most simple manner for the benefit of sudents.

We have advanced lab facilities for students to practice Hadoop Admin course and get hands-on experience in every topics that are covered under Hadoop Admin Training. In the presence of Hadoop Admin Trainer, students can execute all the techniques that has been explained by the instructor. Course Material for Hadoop Admin is specifically designed to cover all the advanced topics and each of the module will have both theory and practical classes. Hadoop Admin Batch Timings at TecMax are flexible and students can choose to join the batch as per their requirements. We have a batch starting every week for Hadoop Admin for regular students. Weekend batches and fast track batches for Hadoop Admin training can be arranged based on the requirement.

All our students will get placement assistance in Hadoop Admin after successfully completing the Hadoop Admin training from our institute. We are committed to provide high-quality training and provide assistance to get you the right job.

Course Content

Hadoop Course Content

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

Hbase for Developers

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

Introduction
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 Design Considerations
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
Development Best Practice and Debugging

Apache Hadoop for Administrators

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
Command Line Interface
Troubleshooting your cluster

Introduction to Big Data and Hadoop

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
Overview of Hadoop
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

Best Practices and common pitfalls
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

 

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Great place to learn. Tecmax have many courses.

About us

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