Big Data Hadoop Programming Training Overview

The certification in Big Data Hadoop programming helps professionals to learn the concepts of the Hadoop framework, big data tools & its methodologies. It prepares them for the role of Big Data professional. Our certification program is a combination of online lectures & hands-on experience. It enables professionals like you to explore the in-depth features of Hadoop programming. Instructors will guide you through the online training to understand every chapter of the course with ease.

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Course Overview

For starters, Hadoop is an open-source framework from Apache to store, process & analyze data that are very huge in terms of quantity. Hadoop is written in JavaScript and is used for batch as well as offline processing. Internet & social media giants like Facebook, Yahoo, Google, and Twitter& LinkedIn use Hadoop to manage their large data sets. Hadoop framework scales up just by adding the nodes in the cluster.    

 

The Hadoop programming tutorial& the Big Data Hadoop Certification program is accepted by top industry experts. This course will help professionals to get a deep meaning & understanding of the Hadoop programming language & they can use these programming skills to thrive in the company. Through the Hadoop Certification Program, you can merge business with technology. You will be taught to handle projects on Hadoop development &execution.

Key Features:

  • Having a deeper knowledge of several data frameworks.
  • Candidates will have hands-on learning & experience in Big Data Analytics with Hadoop.
  • Certified Hadoop professionals will be able to work on projects related to banking, governmental sectors, e-commerce websites & many more.
  • Trained certified professionals can extract information with the Hadoop map reduce program using tools like HDFS, PIG, HIVE & Apache Accumulo.
  • Professionals with certification will be able to upgrade their career in the field of Big Data.    
Who should take this course?

This program is for students & professionals new to Hadoop programming with basic knowledge in Java & Linux. Students & professionals can also learn the Hadoop framework while learning Java & Linux side by side every day for a few hours.

  • Big corporate houses are making a beeline for Hadoop certified professionals giving a competitive edge against professionals without any certification.
  • Hadoop certified professionals beat all others in terms of the pay package as well.
  • A Hadoop certified professional has more chances of getting promoted to a higher position during internal job postings.
  • This course & certification is helpful for people trying to change over to Hadoop coming from different technical fields.
  • This certification program also authenticates your hands-on experience with Big Data.
  • This online training program verifies that you are aware of all the latest features of Hadoop programming.
  • Hadoop certified professionals speak more confidently about this technology at any company while communicating & networking with others.   

Big Data Hadoop Programming Training Course circullum
    • Big Data, Factors constituting Big Data
    • What is Hadoop?
    • Overview of Hadoop Ecosystem
    • Map Reduce -Concepts of Map, Reduce, Ordering, Concurrency, Shuffle, Reducing, Concurrency
    • Hadoop Distributed File System (HDFS) Concepts and its Importance
    • Deep Dive in Map Reduce – Execution Framework, Partitioner, Combiner, Data Types, Key pairs
    • HDFS Deep Dive – Architecture, Data Replication, Name Node, Data Node, Data Flow
    • Parallel Copying with DISTCP, Hadoop Archives
    • Installing Hadoop in Pseudo Distributed Mode, Understanding Important configuration files, their Properties and Demon Threads
    • Accessing HDFS from Command Line
    • Map Reduce – Basic Exercises
    • Understanding Hadoop Eco-system
    • Introduction to Sqoop, use cases.
    • Introduction to Hive, use cases.
    • Introduction to Pig, use cases.
    • Introduction to Oozie, use cases.
    • Introduction to Flume, use cases.
    • Introduction to Yarn
    • How to develop Map Reduce Application, writing unit test
    • Best Practices for Developing and writing, Debugging Map Reduce applications
    • Joining Data sets in Map Reduce
    • Hadoop API’s
    • Introduction to Hadoop Yarn
    • Difference between Hadoop 1.0 and 2.0
    • Project 1- Hands-on exercise – an end to end PoC using Yarn or Hadoop 2.
    1. Real World Transactions handling of Bank
    2. Moving data using Sqoop to HDFS
    3. Incremental update of data to HDFS
    4. Running Map Reduce Program
    5. Running Hive queries for data analytics
    • Project 2- Hands-on exercise – an end to end PoC using Yarn or Hadoop 2.0
    1. Running Map Reduce Code for Movie Rating and finding their fans and average rating

  1. Introduction to Pig

    1. What Is Pig?
    2. Pig’s Features
    3. Pig Use Cases
    4. Interacting with Pig

    Basic Data Analysis with Pig

    1. Pig Latin Syntax
    2. Loading Data
    3. Simple Data Types
    4. Field Definitions
    5. Data Output
    6. Viewing the Schema
    7. Filtering and Sorting Data
    8. Commonly-Used Functions
    9. Hands-On Exercise: Using Pig for ETL Processing

    Processing Complex Data with Pig

    1. Complex/Nested Data Types
    2. Grouping
    3. Iterating Grouped Data
    4. Hands-On Exercise: Analyzing Data with Pig

     

  1. Introduction to Hive

    1. What Is Hive?
    2. Hive Schema and Data Storage
    3. Comparing Hive to Traditional Databases
    4. Hive vs. Pig
    5. Hive Use Cases
    6. Interacting with Hive

    Relational Data Analysis with Hive

    1. Hive Databases and Tables
    2. Basic HiveQL Syntax
    3. Data Types
    4. Joining Data Sets
    5. Common Built-in Functions
    6. Hands-On Exercise: Running Hive Queries on the Shell, Scripts, and Hue

    Hive Data Management

    1. Hive Data Formats
    2. Creating Databases and Hive-Managed Tables
    3. Loading Data into Hive
    4. Altering Databases and Tables
    5. Self-Managed Tables
    6. Simplifying Queries with Views
    7. Storing Query Results
    8. Controlling Access to Data
    9. Hands-On Exercise: Data Management with Hive

    Hive Optimization

    1. Understanding Query Performance
    2. Partitioning
    3. Bucketing
    4. Indexing Data
    • What is Hbase
    • Where does it fits
    • What is NOSQL
    • Running Map Reduce Jobs on Cluster
    • Delving Deeper Into The Hadoop API
    • More Advanced Map Reduce Programming, Joining Data Sets in Map Reduce
    • Graph Manipulation in Hadoop
    • Major Project, Hadoop Development, Cloudera Certification Tips and Guidance, and Mock Interview Preparation, Practical Development Tips and Techniques, certification preparation

  1. Project:- Working with Map Reduce, Hive, Sqoop

    Problem Statement: It describes that how to import MySQL data using Sqoop and querying it using hive and also describes that how to run the word count MapReduce job.

    Project:- Hadoop Yarn Project – End to End PoC

    Problem Statement: It includes:-

    1. Import Movie data
    2. Append the data
    3. How to use Sqoop commands to bring the data into the Hdfs
    4. End to End flow of transaction data
    5. How to process the real word data or a huge amount of data using the map-reduce program in terms of the movie etc.

     

Market Overview
Top Hiring Company
Industry Trends
Big Data Hadoop Programming Training FAQ’s:

Hadoop Certification comes with Hadoop online training & real-timeindustry projects that candidates have to clear for gaining certification. A candidatewith high-level knowledge, skills, training process can be able to understand &acquire in-depth knowledge of Hadoop tools & concepts.

To prepare for the certification, you have to do the following:-

  • You have to follow the right guide book based on the Hadoop programming tutorial.
  • Use your skills, knowledge & experience to analyze the exam pattern.
  • Get comfortable with courses like Sqoop.
  • All the candidates preparing for the exam are expected to have a basic understanding of the Java Programming concepts.
  • Buy & give as many mock tests as you can to prepare for the certification exam
  • Always keep yourself updated regarding the new updates regarding the course & exam.

Here are some of the vital benefits that you might want to know:-

  • Certification in Hadoop Programming helps you to stay at the top. It helps in giving an edge to your skills over others.
  • In case of a slowdown in your career or any other such serious issues, a certification in big data analytics will keep your skills marketable & valuable for your employer.
  • Globally, companies are struggling to hire Hadoop professionals and those with certification have a better pay package than others.
  • Professionals with a technical background can easily learn & understand the Hadoop programming language.
  • Professionals with Hadoop Certification can easily get promotions during Internal Job Postings(I.J.Ps).
  • It authenticates your hands-on experience dealing with Big Data & also makes you aware of the latest features of Hadoop.

  • The option to get certified is either through online training or in-class training.
  • Online training is more suitable for full-time professionals.
  • Candidates should opt for institutes that are providing live online training.
  • Learning & gaining experience is so easy through online training.
  • Live online training addresses some of the key issues related to Hadoop Certification.

The Apache Hadoop programming language is an open-source framework used to efficiently store & process large datasets such as size ranging from gigabytes to petabytes of data. It also permits the clustering of multiple computers for analyzing massive datasets in parallel more quickly

The Hadoop architecture permits parallel processing of data using components such as Hadoop HDFS to store data across slave machines. The next component is Hadoop YARN known for resource management in the Hadoop cluster.

As we all know that Hadoop is an open-source software network for storing data & running applications on the clusters of community hardware. It provides massive storage for any type of data along with enormous processing power & the ability to handle almost limitless concurrent tasks or jobs.

Here are three components of the Hadoop framework that are as follows:-

  • Hadoop HDFS: The full form of Hadoop (HDFS) is Hadoop Distributed File System known as the storage unit of Hadoop
  • Hadoop mapreduce: The Hadoop mapreduce component is the processing unit of Hadoop.
  • Hadoop YARN: This component is the resource management unit of Hadoop.

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