Hadoop Developer Corporate Training Course

Edstellar's customizable Hadoop Developer instructor-led training course is a comprehensive solution designed to equip organizations to develop scalable applications, perform data analysis, and derive valuable insights from large datasets. Through this training, teams gain expertise in Hadoop ecosystem components, data processing, and analysis.

24 - 26 hrs
Instructor-led (On-site/Virtual)
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Hadoop Developer Training

Drive Team Excellence with Hadoop Developer Corporate Training

On-site or Online Hadoop Developer Training - Get the best Hadoop Developer training from top-rated instructors to upskill your teams.

The role of a Hadoop Developer is crucial in the ever-evolving data-driven world. Hadoop is a powerful open-source framework that allows organizations to process and analyze large volumes of data in a distributed and scalable manner. To build efficient data pipelines, perform data analysis, and develop applications that can handle big data workloads, organizations have to focus on providing virtual and onsite Hadoop Developer training for Hadoop development, covering key concepts, tools, and techniques.

Edstellar's Hadoop Developer instructor-led training course enables Hadoop developers to have a solid understanding of Hadoop's architecture, its various components, and the programming models used for data processing. Knowledge about the overall Hadoop ecosystem provides employees insight into HDFS and an understanding of how data is stored and managed in a distributed environment.

Hadoop Developer Training for Employees: Key Learning Outcomes

Develop essential skills from industry-recognized Hadoop Developer training providers. The course includes the following key learning outcomes:

  • Utilize Hadoop security mechanisms to ensure data protection and access control
  • Troubleshoot and debug Hadoop applications and resolve performance bottlenecks
  • Apply best practices for data ingestion, storage, and retrieval in Hadoop environments
  • Design and implement Hadoop data pipelines for efficient data processing and transformation
  • Create MapReduce applications to process and analyze large datasets in a distributed environment
  • Apply Hadoop ecosystem tools such as Hive and Pig for data modeling, querying, and data processing
  • Evaluate Hadoop cluster performance and optimize resource utilization for enhanced data processing efficiency
  • Analyze complex data requirements and develop scalable Hadoop-based solutions to address organizational needs

Key Benefits of the Training

  • Evaluate the performance and scalability of Hadoop applications
  • Ensure professionals understand the core concepts of Hadoop architecture, components, and ecosystem
  • Enable the professionals to create powerful and scalable applications to process and analyze large datasets
  • Develop data pipelines and perform data transformations that align with the organization's specific requirements
  • Equip the organization to extract meaningful information from vast amounts of data and make informed business decisions

Hadoop Developer Training Topics and Outline

This Hadoop Developer Training curriculum is meticulously designed by industry experts according to the current industry requirements and standards. The program provides an interactive learning experience that focuses on the dynamic demands of the field, ensuring relevance and applicability.

  1. Big Data - Big value
    • Characteristics of Big Data
    • Value of Big Data in Organizations
  2. Understanding Big Data
    • Volume, Velocity, Variety, Veracity, and Value of Data
  3. Hadoop and other Solutions
    • Comparison with other Big Data Technologies (e.g., Spark, NoSQL)
  4. Distributed Architecture - A Brief Overview
    • Distributed Computing Fundamentals
    • Hadoop Distributed File System (HDFS)
    • Hadoop Cluster Architecture
  5. Hadoop Releases
    • Versioning and Release History of Hadoop
  1. Setup Hadoop
    • Installation and Configuration of Hadoop
    • Setting Up Single-Node and Multi-Node Clusters
  2. Linux (Ubuntu) - Tips and Tricks
    • Linux Commands and Shell Basics
    • Common Linux Utilities for Hadoop
  3. HDFS commands
    • Basic HDFS Operations (e.g., ls, mkdir, put, get)
    • File Manipulation in HDFS (e.g., cp, mv, rm)
  4. Running a MapRed Program
    • Writing MapReduce Jobs in Java
    • Compiling and Executing MapReduce Programs
  1. HDFS Concepts I
    • Data Blocks and Replication
    • Namenode and Datanode
  2. HDFS Architecture
    • Namenode and Datanode Architecture
    • Block Placement and Replication
  3. HDFS Read and Write
    • Reading Data from HDFS
    • Writing Data to HDFS
  4. HDFS Concepts II
    • Rack Awareness and Data Locality
    • HDFS Federation and High Availability
  5. Special Commands
    • HDFS Administrative Commands
    • Maintenance and Monitoring of HDFS
  1. MapReduce Introduction
    • MapReduce Paradigm and Data Processing Model
    • MapReduce Workflow and Phases
  2. Understanding MapReduce
    • Mapper, Reducer, and Partitioner Functions
    • Data Shuffling and Sorting
  3. Running First MapReduce Program
    • Developing and Executing a Simple MapReduce Program
  4. Combiner And Tool Runner
    • Combiner Function for Intermediate Data Aggregation
    • Tool Runner for MapReduce Program Execution
  1. MapReduce Types and Formats
    • Input and Output Formats in MapReduce
    • Text, Sequence, and Custom Input/Output Formats
  2. Experiments with Defaults
    • Default Input and Output Formats
    • Default Data Serialization
  3. IO Format Classes
    • Using Different Input/Output Formats
    • Working with KeyValue, Avro, and Parquet Formats
  4. Experiments with File Output - Advanced Concept
    • Customizing File Output Formats
    • File Compression Techniques in MapReduce
  1. Anatomy of MapReduce job run
    • MapReduce Job Execution Flow
    • Task Execution and Communication
  2. Job Run - Classic MapReduce
    • Job Configuration and Submission
    • Monitoring and Tracking MapReduce Jobs
  3. Failure Scenarios - Classic Map Reduce
    • Handling Task Failures and Job Recovery
    • Debugging and Troubleshooting MapReduce Jobs
  4. Job Run - YARN
    • YARN Architecture and Components
    • MapReduce Job Execution on YARN
  5. Failure Scenario - YARN
    • YARN Failures and Fault Tolerance Mechanisms
    • Recovering Failed YARN Applications
  6. Job Scheduling in MapReduce
    • Task Scheduling Algorithms in MapReduce
    • Speculative Execution and Task Prioritization
  7. Shuffle and Sort
    • Map Output Shuffle and Sort Phases
    • Partitioning and Sorting Techniques
  8. Performance Tuning Features
    • Performance Optimization in MapReduce Jobs
    • Configuring MapReduce Parameters for Efficiency
  1. Looking at Counters
    • Monitoring Job Progress with Counters
    • Implementing Custom Counters
  2. Hands-on - Counters
    • Hands-on Exercises with Counters
    • Analyzing Job Metrics with Counters
  3. Sorting Ideas with Partitioner
    • Custom Partitioning Techniques
    • Partitioner Function Implementation
  4. Map Side Join Operation
    • Map-Side Join Concept and Implementation
    • Optimizing Map-Side Join Performance
  5. Reduce Side Join Operation
    • Reduce-Side Join Concept and Implementation
    • Handling Data Skew in Reduce-Side Joins
  6. Side Distribution of Data
    • Distributed Cache in MapReduce Jobs
    • Sharing Files and Archives across Nodes
  7. Hadoop Streaming and Hadoop Pipes
    • Integrating Non-Java Programs with MapReduce
    • Using Streaming API and Pipes API
  1. Introduction to Pig
    • Pig Language and Data Processing Operations
    • Executing Pig Scripts in Hadoop
  2. Introduction to Hive
    • Hive Architecture and Data Warehousing Concepts
    • Querying and Analyzing Data with Hive
  3. Introduction to Sqoop
    • Sqoop Overview and Features
    • Importing and Exporting Data using Sqoop
  4. Knowing Sqoop
    • Advanced Sqoop Techniques and Transformations
    • Sqoop Incremental Imports and ETL Operations
  5. Introduction to Ecosystem
    • Overview of Other Hadoop Ecosystem Tools and Technologies

This Corporate Training for Hadoop Developer is ideal for:

What Sets Us Apart?

Hadoop Developer Corporate Training Prices

Elevate your team's Hadoop Developer skills with our Hadoop Developer corporate training course. Choose from transparent pricing options tailored to your needs. Whether you have a training requirement for a small group or for large groups, our training solutions have you covered.

Request for a quote to know about our Hadoop Developer corporate training cost and plan the training initiative for your teams. Our cost-effective Hadoop Developer training pricing ensures you receive the highest value on your investment.

Request for a Quote

Our customized corporate training packages offer various benefits. Maximize your organization's training budget and save big on your Hadoop Developer training by choosing one of our training packages. This option is best suited for organizations with multiple training requirements. Our training packages are a cost-effective way to scale up your workforce skill transformation efforts..

Starter Package

125 licenses

64 hours of training (includes VILT/In-person On-site)

Tailored for SMBs

Most Popular
Growth Package

350 licenses

160 hours of training (includes VILT/In-person On-site)

Ideal for growing SMBs

Enterprise Package

900 licenses

400 hours of training (includes VILT/In-person On-site)

Designed for large corporations

Custom Package

Unlimited licenses

Unlimited duration

Designed for large corporations

View Corporate Training Packages

This Corporate Training for Hadoop Developer is ideal for:

The Hadoop Developer training course is designed for software developers, database administrators, data engineers, technology managers and leaders responsible for overseeing data-related projects and initiatives in the Hadoop ecosystem.

Prerequisites for Hadoop Developer Training

A prior knowledge and experience in basic programming concepts, familiarity with Linux operating systems, and an understanding of SQL and relational databases is needed to benefit from the Hadoop Developer training course.

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Bringing you the Best Hadoop Developer Trainers in the Industry

The instructor-led Hadoop Developer Training training is conducted by certified trainers with extensive expertise in the field. Participants will benefit from the instructor's vast knowledge, gaining valuable insights and practical skills essential for success in Hadoop Developer practices.

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