Hadoop Admin Training in Bangalore

Learn Hadoop Admin Course from Expert Oracle Trainers who are Real-time Working Professionals.
Expert Trainers | Practical Training | Mock Interviews | Placement Assistance | Job Support

Best Hadoop Admin Training in BTM Layout Bangalore

Based on Google and other third-party reviews, Softgen Infotech is recognized as one of the Hadoop Admin Training in BTM Layout Bangalore. We have completed over 2000 HADOOP training sessions with a 100% placement rate, assisting college students. For the past 5 years, the team at Softgen Infotech has been dedicated to providing High-Quality Hadoop Admin Training in BTM Layout Bangalore.

Softgen Infotech’s trainers come from the HADOOP industry and have at least 5 years of experience implementing HADOOP. All HADOOP trainers are real-time specialists who provide hands-on experience with practicals.

Our Hadoop Admin Training in BTM Layout Bangalore is well equipped with labs and good infrastructure to provide you with hands-on training. We also offer HADOOP certification training programmes. We have successfully trained and placed the majority of our students in large MNC firms. Softgen provides HADOOP programmes with 100% placement assistance for our students.

 

Contact us and let us together build a perfect career for your future!

Enroll Today

    Why Choose Softgen Infotech

    Softgen Infotech is a leading Training Institute in Bangalore providing Quality Training for Multiple IT Courses with Placement Assistance.

    Live & Interactive Sessions

    Real Time Training

    Practical Classes

    Interview & Placement Assistance

    Need Advice?

    Worried or Confused whether this is the right course for you? Feel free to reach our Expert Consultant for all your Queries !

    Salesforce Training in Bangalore

    Course Material & Syllabus

    Get all Course Content and Syllabus. Get Trained like a  Professional. We Provide Course Material, Prepare for Interviews, Arrange Mock Interviews and 100 % Placement Assistance

    Hadoop training course content and Syllabus

    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

    Hadoop Admin Training Course Duration & Batch Timings

    Duration : 30 Hours Version : latest Version
    Regular : 1 Hour per day Fast Track : 2 - 3 Hours per day: 10 days
    Weekdays : Monday - Friday Weekend : Saturday and Sunday
    Online Training : Available Class Room Training : Available
    Course Fee : Talk to our Customer Support Mode of Payment : Talk to our Customer Support

    Frequently Asked Questions for Hadoop Admin Training Course

    Click edit button to change this text. Lorem ipsum dolor sit amet, consectetur adipiscing elit. Ut elit tellus, luctus nec ullamcorper mattis, pulvinar dapibus leo.

    What Our Students Have to Say about Hadoop Admin Course

    Click edit button to change this text. Lorem ipsum dolor sit amet, consectetur adipiscing elit. Ut elit tellus, luctus nec ullamcorper mattis, pulvinar dapibus leo.
    Kelvin Black
    Click edit button to change this text. Lorem ipsum dolor sit amet, consectetur adipiscing elit. Ut elit tellus, luctus nec ullamcorper mattis, pulvinar dapibus leo.
    Zasha Swan

    Book A FREE Demo Today

    Worried or Confused whether this is the right course for you?

    Feel free to reach our Expert Consultant for all your Queries !