This document describes a training course on MapReduce design patterns offered by myTectra Learning Solutions. The course is titled "MapReduce Design Patterns" and covers various types of design patterns for MapReduce including summarization, filtering, data organization, joining, meta, graph, and input/output patterns. The course can be taken in an instructor-led classroom format, live virtual training, or self-paced online over 4, 6, or 8 weeks. Contact details are provided to enroll in the course.

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Course details:
Course Code : MYT1650
Course Name: MapReduce Design
Patterns
Course duration: Fast track – 4 weeks
Regular weekdays – 6 weeks
Week End – 8 weeks
Training mode:
instructor led class training | Live virtual training
Contact: +91 90191 91856
Email:info@mytectra.com
Web: www.mytectra.com
Twitter : https://twitter.com/mytectra
Facebook: https://www.facebook.com/myTectra.Global
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2. Introduction & Summarization Patterns
 Learning Objectives - In this module, you will be introduced to Design Patterns vis-
a-vis MapReduce, general structure of the course & project work. Also, discussion
on Summarization Patterns: Patterns that give a summarized top level view of
large data sets.
 Topics - Review of MapReduce, Why are Design Patterns required for MapReduce,
Discussion of different classes of Design Patterns, Discussion of project work and
problem, About Summarization Patterns, Types of Summarization Patterns –
Numerical Summarization Patterns, Inverted Index Pattern and Counting with
counters pattern, Description, Applicability, Structure (how mappers, combiners &
reducers are used in this pattern), use cases, analogies to Pig & SLQ,
Performance Analysis, Example code walk-through & data flow.
myTectra Learning Solutions private Limited
Bangalore-BTM Layout/
+91 90191 91856/ info@mytectra.com / www.mytectra.com

3. Filtering Patterns
 Learning Objectives - In this module, we will discuss about Filtering Patterns:
Patterns that create subsets of data for a more detailed view.
 Topics - About Filtering Patterns, Explain & Distinguish 4 different types of Filtering
Patterns: Filtering Pattern, Bloom Filter Pattern, Top Ten Pattern and Distinct
Pattern, Description, Applicability, Structure (how mappers, combiners & reducers
are used in this pattern), use cases, analogies to Pig & SLQ, Performance
Analysis, Example code walk-through & data flow.
Data Organization Patterns
 Learning Objectives - In this module, we will discuss about Data Organization
Patterns: Patterns that are about re-organizing and transforming data. Categories
of these patterns are used together to achieve end objective.
myTectra Learning Solutions private Limited
Bangalore-BTM Layout/
+91 90191 91856/ info@mytectra.com / www.mytectra.com

4.  Topics - About Organization patterns, Explain 5 different types of Organization
Patterns – Structured to Hierarchical Pattern, Partitioning Pattern, Binning
Pattern, Total Order Sorting Pattern and Shuffling Pattern, Description,
Applicability, Structure (how mappers, combiners & reducers are used in this
pattern), use cases, analogies to Pig & SLQ, Performance Analysis, Example code
walk-through & data flow.
Join Patterns
 Learning Objectives - In this module, we will discuss Join Patterns: Patterns to be
used when your data is scattered across multiple sources and you want to
uncover interesting relationships using these sources together.
 Topics - About Join Patterns, Explain 4 different types of Join Patterns: Reduce
Side Join Pattern, Replicated Join Pattern, Composite Join Pattern, Cartesian
Product Join Pattern, Description, Applicability, Structure (how mappers,
combiners & reducers are used in this pattern), use cases, analogies to Pig &
SLQ, Performance Analysis, Example code walk-through & data flow.
myTectra Learning Solutions private Limited
Bangalore-BTM Layout/
+91 90191 91856/ info@mytectra.com / www.mytectra.com

5. Meta Patterns & Graph Patterns
 Learning Objectives - In this module, we will discuss about Meta Patterns & Graph
Patterns. Meta Patterns are different from other Patterns discussed above i.e.
these are not basic patterns, but Pattern about Patterns, Introduction to Graph
Patterns.
 Topics - About Meta Patterns, Types of Meta Patterns: Job Chaining – Description,
use cases, chaining with driver, basic & parallel job chaining, chaining with shell
scripts, chaining with job control, Example code walk-through, Chain Folding –
Description, What to fold, Chain mapper, Chain Reducer, Example code walk-
through, Job Merging - Description, Steps for merging two jobs, Example code
walk-through, Introduction to Graph design Pattern, Types of Graph Design
Patterns: In-mapper Combining Pattern, Schimmy Pattern and Range Partitioning
Pattern Pseudo-code for each pattern applied to Page-rank algorithm.
myTectra Learning Solutions private Limited
Bangalore-BTM Layout/
+91 90191 91856/ info@mytectra.com / www.mytectra.com

6. Input Output Pattern & Project Review
 Learning Objectives - In this module, we discuss about Input Output Pattern: Input
Output Patterns are about customizing input & output to increase the value of
map reduce, Project Review.
 Topics - About Input Output Patterns, Types of Input Output Patterns –
Customizing Input & Output, Generating Data, External Source output, External
Source Input, Partition Pruning: Description, Applicability, Structure (how
mappers, combiners & reducers are used in this pattern), use cases, analogies to
Pig & SLQ, Performance Analysis, Example code walk-through & reviewing the
project work solution
myTectra Learning Solutions private Limited
Bangalore-BTM Layout/
+91 90191 91856/ info@mytectra.com / www.mytectra.com