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MapReduce Design Patterns Certification Training

Make a map. Design patterns are used to reduce code, learn pattern shuffling, applicability, parallels to Pig and SLQ, performance analysis, and so on.

Why This Course

MapReduce Design Patterns are used by companies such as AOL, eBay, and Twitter.

MapReduce Design Patterns were employed at Google to totally rebuild Google's World Wide Web index.

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The average annual salary is $189K USD. Indeed.com is a job search site.​​

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Self Paced Online Class

MapReduce Design Patterns Certification Training

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.

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Why Enroll In MapReduce Design Patterns Course?

MapReduce Design Patterns Certification Training enhances individual skills and knowledge in big data engineering, while organizations benefit from certified professionals who can design and implement MapReduce applications, optimize performance, and troubleshoot issues. This leads to improved big data processing capabilities, enhanced team performance, and increased business value, and helps organizations stay competitive in a fast-paced business environment.

MapReduce Design Patterns Training Features

Live Interactive Learning

  World-Class Instructors

  Expert-Led Mentoring Sessions

  Instant doubt clearing

Lifetime Access

  Course Access Never Expires

  Free Access to Future Updates

  Unlimited Access to Course Content

24x7 Support

  One-On-One Learning Assistance

  Help Desk Support

  Resolve Doubts in Real-time

Hands-On Project Based Learning

  Industry-Relevant Projects

  Course Demo Dataset & Files

  Quizzes & Assignments

Industry Recognized Certification

  CertHippo Training Certificate

  Graded Performance Certificate

  Certificate of Completion

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About your AWS Course

AWS Solutions Architect Course Skills Covered

Managing Security

Designing Data Storage Solutions

Monitoring Cloud Solutions

Designing Resilient AWS Solutions

AWS Cloud Cost Optimization

Designing Identity Solutions

MapReduce Design Patterns Course Curriculum

Learning Objectives - This module will expose you to Design Patterns in relation to MapReduce, as well as the overall structure of the course and project work. Also included is a description of Summarization Patterns, which are patterns that provide a summarized top-level perspective of big data sets.

Topics- Examining MapReduce, Why are MapReduce Design Patterns required? Discussion of several Design Pattern courses, Project work and problems are discussed. About Summarization Patterns, Summarization Pattern Types - Numerical Summarization Patterns, Counting using counters and Inverted Index Pattern Description, applicability, structure (how mappers, combiners, and reducers are employed in this pattern), use examples, Pig and SLQ analogies Performance Evaluation, A walkthrough of some code and data flow.

Learning Objectives -  This lesson will go over Filtering Patterns, which are patterns that construct subsets of data for a more thorough perspective. 

Topics - Filtering Patterns, Explain & Distinguish 4 Types of Filtering Patterns: Filtering Pattern, Bloom Filter Pattern, Top Ten Pattern, and Distinct Pattern are all examples of patterns. Description, Applicability, Structure (how mappers, combiners, and reducers are utilized in this design), application cases, Pig and SLQ parallels, Performance Analysis, Example code walk-through, and data flow.

Learning Objectives - We will talk about Data Organization Patterns in this module: Patterns involving data reorganization and transformation. These pattern categories are combined to reach the ultimate goal.

Topics- In terms of organizational patterns, Explain the five types of organizational patterns: structured to hierarchical pattern, partitioning pattern, binning pattern, total order sorting pattern, and shuffle pattern. Description, Applicability, Structure (how mappers, combiners, and reducers are utilized in this design), application cases, Pig and SLQ parallels, Performance Analysis, Example code walk-through, and data flow.

Learning Objectives -This module will go through Join Patterns: Patterns to apply when your data is dispersed across several sources and you want to discover intriguing links by combining these sources.

Topics - In terms of Join Patterns, Explain the following four types of join patterns: Reduced Side Join Pattern, Replicated Join Pattern, Composite Join Pattern, and Cartesian Product Join Pattern. Description, Applicability, Structure (how mappers, combiners, and reducers are utilized in this design), application cases, Pig and SLQ parallels, Performance Analysis, Example code walk-through, and data flow. 

Learning Objectives - This lesson will go over Meta Patterns and Graph Patterns. Meta Patterns differ from the other Patterns listed above in that they are not fundamental patterns, but rather Patterns about Patterns, or an Introduction to Graph Patterns.  


Topics - About Meta Patterns, Meta Pattern Types: Job Chaining - Overview, Use Cases, Basic & Parallel Job Chaining, Chaining with Shell Scripts, Chaining with Job Control Exemplification of code, Chain Folding - What to Fold, How to Fold Chain mapper, Chain Reducer, Walkthrough of Example Code Job Merging - Definition, Procedures for Combining Two Jobs  Exemplification of code, Graph Design Pattern Overview, Patterns of Graph Design: Range Partitioning Pattern, Schimmy Pattern, and In-mapper Combining Pattern Each pattern's pseudocode is applied to the Page-rank algorithm.

Learning Objectives - In this module, we will look at the Input Output Pattern: Customizing input and output to maximize the value of map decrease, Project Review, is what Input Output Patterns are all about.  

Topics -  Partition Pruning: Description, Applicability, Structure (how mappers, combiners, and reducers are used in this pattern), use cases, analogies to Pig and SLQ, Performance Analysis Example code walkthrough and project task solution evaluation.  

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Certification

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.

MapReduce Design Patterns Online Training FAQs

We have included a resume creation feature in your LMS to assist you in this attempt. You may now design a winning CV in just three simple steps. You will have unrestricted access to these templates across all roles and designations. All you have to do is sign in to your LMS and select the "create your resume" option.

All of our instructors are working professionals with at least 10-12 years of relevant experience in diverse disciplines. They are subject matter experts who have been educated by Certhippo to deliver high-quality online training to users.

You can give us a CALL at +1 302 956 2015 (US) OR email at info@certhippo.com

Projects

The project work will consist of five distinct components based on several MapReduce Design Patterns learned during the course. Each of these components is intended to be completed by participants in their leisure time between weekly courses. Each of these components will take around 3 hours to complete. The project solution will be discussed in the final module. 

We will assist you in installing Cert Hippo Virtual Machine on your system for your practical work. This will be a local connection for you. The installation instructions are available in LMS.

Selenium Certification

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.

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