Hadoop Training

The Hadoop Development course covers the necessary skill set for students to set up a Hadoop cluster, store large amounts of data using Hadoop (HDFS), and process and analyze the data using Map-Reduce programming or other Hadoop ecosystems. Watch a real-time expert’s Hadoop training demonstration with Tech centerpoint.

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Hadoop Training - Curriculum

  • Basic Unix Commands
  • Core Java (OOPS Concepts, Collections , Exceptions ) for Map Reduce Programming
  • SQL Query knowledge for Hive Queries
  • Any Linux flavor OS (Ex: Ubuntu/Cent OS/Fedora/RedHat Linux) with 4 GB RAM (minimum), 100 GB HDD
  • Java 1.6+
  • Open-SSH server & client
  • MYSQL Database
  • Eclipse IDE
  • VM Ware (To use Linux OS along with Windows OS)
  • High Availability
  • Scaling
  • Advantages and Challenges 
  • Hadoop Distributed File System
  • Comparing Hadoop & SQL
  • Industries using Hadoop
  • Data Locality
  • Hadoop Architecture
  • Map Reduce & HDFS
  • Using the Hadoop single node image (Clone)
  • HDFS Design & Concepts
  • Blocks, Name nodes and Data nodes
  • HDFS High-Availability and HDFS Federation
  • Hadoop DFS The Command-Line Interface
  • Basic File System Operations
  • Anatomy of File Read,File Write
  • Block Placement Policy and Modes
  • More detailed explanation about Configuration files
  • Metadata, FS image, Edit log, Secondary Name Node and Safe Mode
  • How to add New Data Node dynamically,decommission a Data Node dynamically (Without stopping cluster)
  • FSCK Utility. (Block report)
  • How to override default configuration at system level and Programming level
  • HDFS Federation
  • ZOOKEEPER Leader Election Algorithm
  • Exercise and small use case on HDFS
  • Map Reduce Functional Programming Basics
  • Map and Reduce Basics
  • How Map Reduce Works
  • Anatomy of a Map Reduce Job Run
  • Legacy Architecture ->Job Submission, Job Initialization, Task Assignment, Task Execution, Progress and Status Updates
  • Job Completion, Failures
  • Shuffling and Sorting
  • Splits, Record reader, Partition, Types of partitions & Combiner
  • Optimization Techniques -> Speculative Execution, JVM Reuse and No. Slots
  • Types of Schedulers and Counters
  • Comparisons between Old and New API at code and Architecture Level
  • Getting the data from RDBMS into HDFS using Custom data types
  • Distributed Cache and Hadoop Streaming (Python, Ruby and R)
  • YARN
  • Sequential Files and Map Files
  • Enabling Compression Codec’s
  • Map side Join with distributed Cache
  • Types of I/O Formats: Multiple outputs, NLINE input format
  • Handling small files using Combine File Input Format
  • Hands on “Word Count” in Map Reduce in standalone and Pseudo distribution Mode
  • Sorting files using Hadoop Configuration API discussion
  • Emulating “grep” for searching inside a file in Hadoop
  • DBInput Format
  • Job Dependency API discussion
  • Input Format API discussion,Split API discussion
  • Custom Data type creation in Hadoop
  • ACID in RDBMS and BASE in NoSQL
  • CAP Theorem and Types of Consistency
  • Types of NoSQL Databases in detail
  • Columnar Databases in Detail (HBASE and CASSANDRA)
  • TTL, Bloom Filters and Compensation
  • HBase Installation, Concepts
  • HBase Data Model and Comparison between RDBMS and NOSQL
  • Master  & Region Servers
  • HBase Operations (DDL and DML) through Shell and Programming and HBase Architecture
  • Catalog Tables
  • Block Cache and sharding
  • SPLITS
  • DATA Modeling (Sequential, Salted, Promoted and Random Keys)
  • JAVA API’s and Rest Interface
  • Client Side Buffering and Process 1 million records using Client side Buffering
  • HBase Counters
  • Enabling Replication and HBase RAW Scans
  • HBase Filters
  • Bulk Loading and Co processors (Endpoints and Observers with programs)
  • Real world use case consisting of HDFS,MR and HBASE
  • Data scraping: What is it?
  • Using Data Scraping Wizard: Steps and an Example
  • Screen scraping: What is it?
  • Methods for Screen Scraping
  • Screen Scraping Wizard Instructions with an Example
  • Hive Installation, Introduction and Architecture
  • Hive Services, Hive Shell, Hive Server and Hive Web Interface (HWI)
  • Meta store, Hive QL
  • OLTP vs. OLAP
  • Working with Tables
  • Primitive data types and complex data types
  • Working with Partitions
  • User Defined Functions
  • Hive Bucketed Tables and Sampling
  • External partitioned tables, Map the data to the partition in the table, Writing the output of one query to another table, Multiple inserts
  • Dynamic Partition
  • Differences between ORDER BY, DISTRIBUTE BY and SORT BY
  • Bucketing and Sorted Bucketing with Dynamic partition
  • RC File
  • INDEXES and VIEWS
  • MAPSIDE JOINS
  • Compression on hive tables and Migrating Hive tables
  • Dynamic substation of Hive and Different ways of running Hive
  • How to enable Update in HIVE
  • Log Analysis on Hive
  • Access HBASE tables using Hive
  • Hands on Exercises
  • Pig Installation
  • Execution Types
  • Grunt Shell
  • Pig Latin
  • Data Processing
  • Schema on read
  • Primitive data types and complex data types
  • Tuple schema, BAG Schema and MAP Schema
  • Loading and Storing
  • Filtering, Grouping and Joining
  • Debugging commands (Illustrate and Explain)
  • Validations,Type casting in PIG
  • Working with Functions
  • User Defined Functions
  • Types of JOINS in pig and Replicated Join in detail
  • SPLITS and Multiquery execution
  • Error Handling, FLATTEN and ORDER BY
  • Parameter Substitution
  • Nested For Each
  • User Defined Functions, Dynamic Invokers and Macros
  • How to access HBASE using PIG, Load and Write JSON DATA using PIG
  • Piggy Bank
  • Hands on Exercises
  • Spark Overview
  • Linking with Spark, Initializing Spark
  • Using the Shell
  • Resilient Distributed Datasets (RDDs)
  • Parallelized Collections
  • External Datasets
  • RDD Operations
  • Basics, Passing Functions to Spark
  • Working with Key-Value Pairs
  • Transformations
  • Actions
  • RDD Persistence
  • Which Storage Level to Choose?
  • Removing Data
  • Shared Variables
  • Broadcast Variables
  • Accumulators
  • Deploying to a Cluster
  • Unit Testing
  • Migrating from pre-1.0 Versions of Spark
  • Where to Go from Here

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Hadoop Training - Projects

Hadoop Training - Key Features

Hadoop Training - Key Features

Customer Service
Job Assistence & Support

We'd do everything in our power to make sure you excelled at work.

24 Hours Support
24x7 Support

Multiple options (Email,Phone or Live Chat)exist to guarantee that your problem is resolved as soon as possible.

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Job Oriented Curriculum

Best-in-class curriculum is totally adaptable to meet your needs and prepareyou for the job and certification.

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Real world projects

Best-in-class instructors will lead trainees through exercies based on real-world projects.

Hadoop Training - Upcoming Batches

  • Weekday
  • Week-end

Tab 1

30 May 2024

8:00 AM IST

6 June 2024

8:00 AM IST

13 June 2024

8:00 AM IST

Tab 2

25 May 2024

8:00 AM IST

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Hadoop Training - Training Options

Live Online Training
Live Online Training
  • Interact live with industrial experts.
  • Flexible Schedule
  • Customizable Curriculum
1:1 Live Online Training
live online 1 to 1 training
  • Dedicated Trainer for you
  • 1:1 Total Online Training
  • Life-time LMS Access
  • Life-time LMS Access
Self-Paced E-Learning
Self-Paced E-Learning
  • Get E-Learning Videos
  • Learn Whenever & Wherever
  • Lifetime free Upgrade
Corporate Training
Corporate Training
  • Customized Training
  • Live Online/Classroom/Self-paced
  • 10+ years Industrial Expert Trainers

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Hadoop Training - FAQS

  • General
  • Self-Paced
  • Online
  • Corporate

Tab 1

  • Through our LMS, you can access the recording of the missed lesson.
  • Yes, we have a customised training curriculum and programme to complete.
  • There are, in fact, both group and referal discounts available.
  • The instructor will give you with all the required resources and guidance to obtain certification independently 
  • Yes, our trainer will assist you in drafting the ideal resume for your desired position.
  • Yes, we provide placement assistance by conducting simulated interviews, crafting resumes, and emailing your profile to our corporate clients.

Tab 2

  • You can change your training mode, however the cost will be prorated depending on whatever option you first choose.
  • Training at your own speed allows you to study whenever you like, with no time constraints.
  • Yes, it varies from course to course.
  • No

Tab 3

  • yes
  • yes. only first 3 sessions
  • very few times, and depends on the Trainer
  • Yes, we will arrange another trainer if that is acceptable; if not, you can receive a refund.

Tab 4

  • Yes, we can provide resources if they are available.
  • Yes, we can tailer t the course content and schedule the sessions to fit the needs of your project.
  • No, we provide assistance