Deprecated: mysql_connect(): The mysql extension is deprecated and will be removed in the future: use mysqli or PDO instead in /home/content/77/8880177/html/ipartner/db.php on line 2
Big Data & Hadoop Development -iPartner
loading...

Big Data Hadoop Developer Training

  1. Big Data Hadoop Developer Training
8/12 weeks / 550*
(* including all taxes.)


Key Features
SMALL
BATCHES
MENTORING
BY EXPERTS
FLEXIBLE
SCHEDULE
LEARN
BY DOING
GOAL
ORIENTED



Course Agenda


  • Why is Data So Important?
  • Pre-requisite – Data Scale
  • What is Big Data?
  • Big Bank: Big Challenge
  • Customer Churn Analysis
  • Point-of-Sale Transaction Analysis
  • Common Problems
  • 3 Vs of Big Data
  • Defining Big Data
  • Sources of Data Flood
  • Exploding Data Problem
  • Redefining the Challenges of Big Data
  • Possible Solutions
  • Scaling Up Vs. Scaling Out
  • Challenges of Scaling Out
  • Solution for Data Explosion-Hadoop
  • Hadoop: Introduction
  • Hadoop in Layman's Term
  • Hadoop Ecosystem
  • Evolutionary Features of Hadoop
  • Big Data Benchmarks
  • Hadoop Timeline
  • Why Learn Big Data Technologies?
  • Who is Using Big Data?
  • Yearly Salaries in Big Data World
  • Job Trends in Big Data
  • Assessments and Quiz
  • HDFS: Introduction
  • Design of HDFS
  • Why Hadoop Cluster?
  • HDFS Blocks
  • Components of Hadoop 1.x
  • NameNode and Hadoop Cluster
  • Arrangement of Racks
  • Arrangement of Machines and Racks
  • Local FS and HDFS
  • NameNode
  • Checkpointing
  • Replica Placement
  • Benefits-Replica Placement and Rack Awareness
  • URI, URL and URN
  • HDFS Commands
  • Assessments and Assignment
  • Problems with HDFS in Hadoop 1.x
  • HDFS Federation (Included in Hadoop 2.x)
  • HDFS Federation
  • High Availability
  • Configuration Files in Hadoop
  • HDFS Configurations
  • Core Configurations
  • Configuration Files in Hadoop
  • Java API to Read HDFS File
  • Java API to Write HDFS File
  • Java API - Listing of File in HDFS
  • Important Java Classes to Read From HDFS
  • Anatomy of File Read From HDFS
  • Data Read Steps
  • Checksum and Data Integrity
  • Data Read from HDFS: Additional Points
  • Important Java Classes to Write Data to HDFS
  • Anatomy of File Write to HDFS
  • Writing File to HDFS: Steps
  • Handling Failures During Writing a File
  • Assessments and Quiz
  • Building Principles
  • Introduction to MapReduce
  • Some More Real-World Examples
  • Broad Steps
  • Finding Out Maximum Temperature
  • Pseudo Code
  • Mapper Class
  • Reducer Class
  • Driver Code
  • Demo: Task 1
  • Exploring Methods of Mapper
  • Exploring Methods of Reducer
  • Demo: Task 3
  • Serialization
  • Deserialization
  • Serialization Classes in Hadoop
  • Assessments and Assignment
  • InputSplit
  • InputSplit and Data Blocks - Difference
  • Why Is The Block Size 128 MB?
  • RecordReader
  • InputFormat
  • Default Inputformat: TextInputFormat
  • MapReduce Example
  • OutputFormat
  • Using a Different OutputFormat
  • Important Points
  • Important Points
  • Data Locality
  • JobTracker and TaskTracker
  • Speculative Execution
  • Combiner
  • Using Combiner
  • Partitioner
  • Using Partitioner
  • Map Only Job
  • Flow of Operations in MapReduce
  • Assessments and Quiz

  • Serialization in MapReduce
  • Custom Writable in MapReduce
  • Custom Writable in MapReduce
  • Custom WritableComparable in MapReduce
  • Overview
  • Schedulers in YARN
  • FIFO Scheduler
  • Capacity Scheduler
  • Fair Scheduler
  • Differences between Hadoop 1.x and Hadoop 2.x
  • Assessments and Assignment
  • Apache Pig:
    • a) Introduction
    • b) Adages
    • c) Advantages
    • d) Basics
    • e) Why Pig?
    • f) Pig Deployment
    • g) Pig Terminology
    • h) Samples
  • Data Types & Handling
  • Apach Pig Architecture
  • Installation
  • Execution - Running Modes, Running Pig
  • Relation Operators
  • Assessments and Quiz
  • Hands-On:
    • a) Pig Latin Commands
    • b) Use Case with YouTube Data
  • Sentiment Analysis on Twitter data using Apache Pig
  • Assessments and Assignment
  • Hands-On:
  • Writing Pig UDF
  • Execution of xml file Using Pig
  • Advanced Joins Using Pig
  • Ebooks on real time case studies on Pig
  • Assessments and Quiz
  • Mini Project discussion Flume Introduction, Flume use case
  • What are Joins?
  • When do we need to use Joins?
  • Map Side Joins:
    • a) Introduction
    • b) What is Distributed Cache?
    • c) Map Side Join Process
    • d) Illustration to Use Distributed Cache?
    • e) Example for MAP-SIDE JOIN Using MapReduce
    • f) Hands-On
  • Reducer Side Join:
    • a) Introduction
    • b) How it Works?
    • c) Illustration to Use Reducer Side Join
    • d) Example for Reducer Side Join using MapReduce
    • e) Hands-On
    ul>
  • Assessments and Assignment

  • Pre-requisites to Understand Custom Input Format
    • a) RecordReader
    • b) WritableComparable
    • c) FileInputFormat
  • CustomerInputFormat Demo
  • Pre-requisites to Understand Sequence File Format
  • Sequence File Format Demo
  • Assessments and Quiz
  • Indroduction
  • Installing Hive
  • Execution Engines of Hive
  • Architecture
  • Services
  • Clients
  • The Metastore
  • Function
  • Query Lifecycle on Hadoop
  • Advantages & Limitations
  • A Walkthrough of Hive Components
  • Assessments and Assignment
  • Hive Data Definitions
  • Hive Data Manipulations
  • HiveQL Operations
  • Hands-On Titanic Dataset
  • Partitioning & Bucketing
  • Assessments and Quiz
  • Complex Data Types Demo
  • Hive UDF Demo
  • Thrift Server Demo
  • Join optimization aspects like Map joins,Sort Merge Bucket (SMB) joins
  • Assessments and Assignment
  • Real time use cases implementing join optimzations
  • NoSQL Databases
  • Types of NoSQL
  • CAP Theorem
  • Introduction to HBase
  • HBase Architecture
  • HBase vs RDBMS
  • HBase Scalable Deployment
  • HBase Data Model
  • Assessments and Quiz
  • Data Model Components
  • Row Example
  • What is a Column Family?
  • Column Family Concepts
  • Hbase Shell Command - Demo
  • Hbase Java API - Demo
  • Assessments and Assignment
  • Hbase Thrift Server:
    • a) What is Hbase Thrift Server?
    • b) Integrating Hbase with your Application
    • c) Sending Request and Response from Thrift Server
    • d) Example
  • HBAse Rest Server
  • Hive HBAse Integration
  • Hands-On
  • Assessments and Quiz
  • Oozie
  • Oozie Architecture
  • Oozie Workflow Nodes
  • Oozie Server
  • Oozie Workflow
  • Sqoop Hands On
  • Assessments and Assignment
  • MAJOR Project discussion. Getting started with Spark - Part 1 Discussing EBook 1 on Spark

Learn & Get

  • Understand complete Apache Hadoop Framework
  • Design and develop applications involving Big Data and Hadoop Ecosystem
  • Learn to work with Hadoop Distributed File System (HDFS)
  • Write and execute programs in YARN (MRv2) latest version of Hadoop Release 2.0Monitor
  • Differentiate between New and Old APIs for Hadoop
  • Understand how YARN engages in managing to compute resources into clusters
  • Implement HBase, MapReduce Integration, Advanced Usage and Advanced Indexing
  • Learn how MapReduce interacts with data and process it

Payment Method

PAYMENT METHODS
You need to pay through PayPal. We accept both Debit and Credit Card for transaction.
SCHOLARSHIPS
We subsidize our fees by 10% for military personnel, and college students with exceptional records. To apply for a scholarship, email info@ipartner.ca
FREQUENTLY ASKED QUESTIONS
In our iPartner self-paced training program, you will receive the training assessments, recorded sessions, course materials, Quizzes, related softwares and assignments. The courses are designed in such a way that you will the get real world exposure; the solid understanding of every concept that allows you to get the most from the online training experience and you will be able to apply the information and skills in the workplace. After the successful completion of your training program, you can take quizzes which enable you to check your level of knowledge and also enables you to clear your relevant certification at higher marks/grade where you will be able to work on the technologies independently.
In Self-paced courses, the learners are able to conduct hands-on exercises and produce learning deliverables entirely on their own at any convenient time without a facilitator whereas in the Online training courses, a facilitator will be available for answering queries at a specific time to be dedicated for learning. During your self-paced learning, you can learn more effectively when you interact with the content that is presented and a great way to facilitate this is through review questions and quizzes that strengthen key concepts. In case if you face any unexpected challenges while learning, we will arrange a live class with our trainer.
All Courses from iPartner are highly interactive to provide good exposure to learners and gives them a real time experience. You can learn only at a time where there are no distractions, which leads to effective learning. The costs of self-paced training are 75% cheaper than the online training. You will offer lifetime access hence you can refer it anytime during your project work or job.
Yes, at the top of the page of course details you can see sample videos.
As soon as you enroll to the course, your LMS (The Learning Management System) Access will be Functional. You will immediately get access to our course content in the form of a complete set of previous class recordings, PPTs, PDFs, assignments and access to our 24*7 support team. You can start learning right away.
24/7 access to video tutorials and Email Support along with online interactive session support with trainer for issue resolving.
Yes, You can pay difference amount between Online training and Self-paced course and you can be enrolled in next online training batch.
Please send an email. You can join our Live chat for instant solution.
We will provide you the links of the software to download which are open source and for proprietary tools, we will provide you the trail version if available.
You will have to work on a training project towards the end of the course. This will help you understand how the different components of courses are related to each other.
Classes are conducted via LIVE Video Streaming, where you get a chance to meet the instructor by speaking, chatting and sharing your screen. You will always have the access to videos and PPT. This would give you a clear insight about how the classes are conducted, quality of instructors and the level of Interaction in the class.
Yes, we do keep launching multiple offers that best suits your needs. Please email us at: info@ipartner.ca and we will get back to you with exciting offers.
We will help you with the issue and doubts regarding the course. You can attempt the quiz again.
Sure! Your feedbacks are greatly appreciated. Please connect with us on the email support - info@ipartner.ca.