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    Big Data Hadoop Developer Training Course

    Big Data Hadoop Developer Professional Program delivers the key concepts and expertise necessary to develop robust data processing applications using Apache Hadoop. The i...

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    ₹ 35000

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    Baroda Institute of Technology
    ₹29999  ₹ 35000  

    14% off

     
    Buy Now
    This includes following
    •  130 Hours
    •  Completion certificate : Yes
    •  Language : Hinglish 
    Big Data Hadoop Developer Professional Program delivers the key concepts and expertise necessary to develop robust data processing applications using Apache Hadoop. The interactive sessions and demonstrations carried by an industry expert will help the aspirants in understanding all the features and programming skills easily. The Hadoop developer course focuses on the fundamentals and advanced topics of Hadoop, MapReduce, Hadoop Distributed File System (HDFC), Hadoop cluster, Pig, Hive, Hbase, ZooKeeper, Sqoop, and Flume. Big Data Analytics takes into account exabytes and petabytes of data and provides solutions to deal with the rapid flow of such huge amounts of data. BIT’s Hadoop developer training will help you master complete Hadoop development. You will trained in the domains of HDFS, MapReduce, working with various components of Hadoop like Pig, Hive, Sqoop, YARN and others.

        Live Class Practical Oriented Training

        Timely Doubt Resolution

        Dedicated Student Success Mentor

        Certification & Job Assistance

        Free Access to Workshop & Webinar

        No Cost EMI Option

        Fundamentals of Hadoop and YARN and write applications using them

        Spark, Spark SQL, Streaming, Data Frame, RDD, GraphX and MLlib writing Spark applications

        Set up different configurations of Hadoop cluster

        Leverage Pig, Hive, Hbase, ZooKeeper, Sqoop, Flume, and other projects from the Apache Hadoop ecosystem

        Practicing real-life projects using Hadoop and Apache Spark

        Setting up pseudo-node and multi-node clusters on Amazon EC2

        Hadoop administration activities like cluster managing, monitoring, administration and troubleshooting

        Maintain and monitor Hadoop cluster by considering the optimal hardware and networking settings

        Hadoop testing applications using MRUnit and other automation tools

       Lecture-1 Introduction to Apache Hadoop and the Hadoop Ecosystem

       Lecture-2 Apache Hadoop File Storage

       Lecture-3 Distributed Processing on an Apache Hadoop Cluster

       Lecture-4 Apache Spark Basics

       Lecture-5 Working with DataFrames and Schemas

       Lecture-6 Analyzing Data with DataFrame Queries

       Lecture-7 RDD Overview

       Lecture-8 Transforming Data with RDDS

       Lecture-9 Aggregating Data with Pair RDDS

       Lecture-10 Querying Tables and Views with SQL

       Lecture-11 Working with Datasets in Scala

       Lecture-12 Writing, Configuring, and Running Spark Applications

       Lecture-13 Spark Distributed Processing

       Lecture-14 Distributed Data Persistence

       Lecture-15 Common Patterns in Spark Data Processing

       Lecture-16 Introduction to Structured Streaming

       Lecture-17 Structured Streaming with Apache Kafka

       Lecture-18 Aggregating and Joining Streaming DataFrames

       Lecture-19 Message Processing with Apache Kafka 

    •   Lecture 1 Introduction to Apache Hadoop and the Hadoop Ecosystem
·       Apache Hadoop Overview
·       Data Processing
·       Introduction to the Hands-On Exercises
·       Practical Exercise
    •   Lecture-2 Apache Hadoop File Storage

·       Apache Hadoop Cluster Components
·       HDFS Architecture
·       Using HDFS
·       Practical Exercise
    •   Lecture-3 Distributed Processing on an Apache Hadoop Cluster
·       YARN Architecture
·       Working With YARN
·       Practical Exercise
    •   Lecture-4 Apache Spark Basics
·       What is Apache Spark?

·       Starting the Spark Shell

·       Using the Spark Shell

·       Getting Started with Datasets and DataFrames

·       DataFrame Operations

·       Practical Exercise
    •   Lecture-5 Working with DataFrames and Schemas
·       Creating DataFrames from Data Sources

·       Saving DataFrames to Data Sources

·       DataFrame Schemas

·       Eager and Lazy Execution

·       Practical Exercise
    •   Lecture-6 Analyzing Data with DataFrame Queries
·       Querying DataFrames Using Column Expressions

·       Grouping and Aggregation Queries

·       Joining DataFrames

·       Practical Exercise
    •   Lecture-7 RDD Overview
·       RDD Overview

·       RDD Data Sources

·       Creating and Saving RDDs

·       RDD Operations

·       Practical Exercise
    •   Lecture-8 Transforming Data with RDDs
·       Writing and Passing Transformation Functions

·       Transformation Execution

·       Converting Between RDDs and DataFrames

·       Practical Exercise
    •   Lecture-9 Aggregating Data with Pair RDDs
·       Key-Value Pair RDDs

·       Map-Reduce

·       Other Pair RDD Operations

·       Practical Exercise
    •   Lecture-10 Querying Tables and Views with SQL
·       Querying Tables in Spark Using SQL

·       Querying Files and Views

·       The Catalog API

·       Practical Exercise
    •   Lecture-11 Working with Datasets in Scala
·       Datasets and DataFrames

·       Creating Datasets

·       Loading and Saving Datasets

·       Dataset Operations

·       Practical Exercise
    •   Lecture-12 Writing, Configuring, and Running Spark Applications
·       Writing a Spark Application

·       Building and Running an Application

·       Application Deployment Mode

·       The Spark Application Web UI

·       Configuring Application Properties

·       Practical Exercise
    •   Lecture-13 Spark Distributed Processing
·       Review: Apache Spark on a Cluster

·       RDD Partitions

·       Example: Partitioning in Queries

·       Stages and Tasks

·       Job Execution Planning

·       Example: Catalyst Execution Plan

·       Example: RDD Execution Plan

·       Practical Exercise
    •   Lecture-14 Distributed Data Persistence
·       DataFrame and Dataset Persistence

·       Persistence Storage Levels

·       Viewing Persisted RDDs

·       Practical Exercise
    •   Lecture-15 Common Patterns in Spark Data Processing
·       Common Apache Spark Use Cases

·       Iterative Algorithms in Apache Spark

·       Machine Learning

·       Example: k-means

·       Practical Exercise
    •   Lecture-16 Introduction to Structured Streaming
·       Apache Spark Streaming Overview

·       Creating Streaming DataFrames

·       Transforming DataFrames

·       Executing Streaming Queries

·       Practical Exercise
    •   Lecture-17 Structured Streaming with Apache Kafka
·       Overview

·       Receiving Kafka Messages

·       Sending Kafka Messages

·       Practical Exercise
    •   Lecture-18 Aggregating and Joining Streaming DataFrames
·       Streaming Aggregation

·       Joining Streaming DataFrames

·       Conclusion

·       Practical Exercise
    •   Lecture-19 Message Processing with Apache Kafka
·       What Is Apache Kafka?

·       Apache Kafka Overview

·       Scaling Apache Kafka

·       Apache Kafka Cluster Architecture

·       Apache Kafka Command Line Tools

·       Practical Exercise
    You don’t need prior knowledge of Apache Hadoop.
    The course offers a variety of online training options, including: • Live Virtual Classroom Training: Participate in real-time interactive sessions with instructors and peers. • 1:1 Doubt Resolution Sessions: Get personalized assistance and clarification on course-related queries. • Recorded Live Lectures*: Access recorded sessions for review or to catch up on missed classes. • Flexible Schedule: Enjoy the flexibility to learn at your own pace and according to your schedule.
    Live Virtual Classroom Training allows you to attend instructor-led sessions in real-time through an online platform. You can interact with the instructor, ask questions, participate in discussions, and collaborate with fellow learners, simulating the experience of a traditional classroom setting from the comfort of your own space.
    If you miss a live session, you can access recorded lectures* to review the content covered during the session. This allows you to catch up on any missed material at your own pace and ensures that you don't fall behind in your learning journey.
    The course offers a flexible schedule, allowing you to learn at times that suit you best. Whether you have other commitments or prefer to study during specific hours, the course structure accommodates your needs, enabling you to balance your learning with other responsibilities effectively.
    Education Provider
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    Baroda Institute Of Technology - Training Program

    BIT (Baroda Institute Of Technology) Is A Training And Development Organization Catering To The Learning Requirements Of Candidates Globally Through A Wide Array Of Services. Established In 2002. BIT Strength In The Area Is Signified By The Number Of Its Authorized Training Partnerships. The Organization Conducts Trainings For Microsoft, Cisco , Red Hat , Oracle , EC-Council , Etc. Domains / Specialties Corporate Institutional Boot Camp / Classroom Online – BIT Virtual Academy Skill Development Government BIT’s Vision To Directly Associate Learning With Career Establishment Has Given The Right Set Of Skilled Professionals To The Dynamic Industry. Increased Focus On Readying Candidates For On-the-job Environments Makes It A Highly Preferred Learning Provider. BIT Is Valued For Offering Training That Is At Par With The Latest Market Trends And Also Match The Potential Of Candidates. With More Than A Decade Of Experience In Education And Development, The Organization Continues To Explore Wider Avenues In Order To Provide Learners A Platform Where They Find A Solution For All Their Up- Skilling Needs!

    Graduation
    2002
    Data Sciences

    More Courses by : Baroda Institute of Technology


    Baroda Institute of Technology
    ₹29999  ₹ 35000  

    14% off

     
    Buy Now
    This includes following
    •  130 Hours
    •  Completion certificate : Yes
    •  Language : Hinglish

    More Courses by : Baroda Institute of Technology


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