A self-paced course built by Hadoop Experts to teach knowledge and skills in the MapReduce Framework and assist you in solving use cases utilizing MapReduce ideas.
A self-paced course built by Hadoop Experts to teach knowledge and skills in the MapReduce Framework and assist you in solving use cases utilizing MapReduce ideas.
MapReduce initially referred to Google's proprietary technology.
MapReduce is used by companies such as Twitter, LinkedIn, AOL, eBay, and Alibaba.
Indeed.com reports that the average annual salary is $61,346.
Our Online Self-Learning Courses offer a self-paced approach, enabling participants to start learning at their preferred times. These courses provide structured training and incorporate review exercises to solidify understanding. You'll access instructional videos and PowerPoint presentations (PPTs) and engage in assignments, projects, and various activities aimed at improving learning outcomes, all tailored to your convenience.
Comprehensive MapReduce Certification Training provides individuals with a deeper understanding of MapReduce, while organizations benefit from certified professionals who can optimize job performance, process and analyze big data efficiently, and improve operational efficiency. Overall, this training can lead to improved big data analytics capabilities, enhanced team performance, and increased business value.
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Resolve Doubts in Real-time
Hands-On Project Based Learning
Industry-Relevant Projects
Course Demo Dataset & Files
Quizzes & Assignments
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Learning Objectives - In this lesson, you will learn about the Hadoop MapReduce framework and how MapReduce works with data stored in HDFS. In MapReduce, you will learn about YARN principles.
Topics - MapReduce Use Cases, Traditional approach Vs MapReduce way, Why MapReduce, Hadoop 2.x MapReduce Architecture, Hadoop 2.x MapReduce Components, YARN MR Application Execution Flow, YARN Workflow, Anatomy of MapReduce Program, Demo on MapReduce.
Learning Objectives - In this lesson, you will learn about topics such as MapReduce Input Splits, Combiner & Partitioner, and MapReduce Demos utilizing various data sets.
Topics - Input Splits in MapReduce, Combiner, Partitioner, Demos on MapReduce.
Learning Objectives - You will study advanced MapReduce concepts such as Counters, Distributed Cache, MRunit, Reduce Join, Custom Input Format, Sequence Input Format, and how to deal with complicated MapReduce applications in this module.
Topics - Counters, Distributed Cache, MRunit, Reduce Join, Custom Input Format, Sequence Input Format are all examples of data structures.
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You will be working on a project near the conclusion of the course. Based on the project examined by our expert panel, CertHippo qualifies you as a Certified Comprehensive Pig Expert.
To assist you in this attempt, we have included a résumé building feature in your LMS. You will now be able to generate a winning CV in just three simple steps. You will have limitless access to these templates across all jobs and designations. Simply log in to your LMS and select the "create your resume" option.
All of the teachers at CertHippo are industry practitioners with at least 10-12 years of relevant IT experience. They are subject matter experts who have been trained by CertHippo to provide an excellent learning experience.
You can give us a CALL at +1 302 956 2015 (US) OR email at info@certhippo.com
Hadoop's underlying engine is MapReduce. The self-paced Comprehensive MapReduce course is designed to help students understand and deploy various MapReduce frameworks. The subjects are taught using specific instances.
Course Objectives
After completion of the Comprehensive MapReduce course, you will be able to:
1. Master the concepts of MapReduce framework
2. Learn to write Complex MapReduce programs
3. Program in YARN
4. Program in MapReduce
This course is intended for professionals who want to work in Big Data Analytics utilizing the MapReduce Framework. This course is mostly beneficial to software professionals, Java developers, analytics professionals, ETL developers, project managers, and testing professionals. Other experts who want to learn more about the MapReduce Framework can also enroll in this course.
Hands-on expertise in Core Java and solid analytical ability to absorb and implement MapReduce ideas are some of the prerequisites for studying MapReduce.
Today, as data becomes more abundant and diverse, there is an increasing demand for data analytics that is versatile, adaptive, efficient, and cost effective, with little on-boarding time. Hadoop fits perfectly in this domain, and MapReduce, Hadoop's underlying engine, must be thoroughly understood.
You will install CertHippo Virtual Machine in your system for your practical work. This will be a local connection for you. The installation instructions are available in LMS.
Project #1: Analyzing Aadhar Card Data
Industry: Government Sector
Data: The following fields are included in the data set: State: This field contains state names from all around India. City: This field contains city names from all states. Approved: This field contains the total number of accepted cards. Rejected: This section contains the total number of rejected cards.
Problem Statement: Here are a couple of the issue statements we selected to focus on using this data set: 1. Determine the total number of cards issued by states. 2. Determine the total number of cards denied by states. 3. Determine the total number of cards accepted by municipalities. 4. Determine the total number of cards rejected by municipalities.
Project #2: Analysis of Afghan War Diaries
Industry: Government Sector
Data: The information was compiled by US military men and intelligence officers. To keep things simple, we will simply look at four of the data set's columns (Type, Category, Region, and Attack On).
Problem Statement: Here are a couple of the issue statements that we choose to focus on using this data set: 1.To investigate all instances involving explosive dangers. 2.To investigate explosive situations using Improvised Explosive Devices. (IEDs).
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