Virtual course of:edureka |
Write MapReduce code using design patterns, learn pattern matching, applicability, Pig & SLQ analogies, performance analysis, etc.
INTRODUCTION AND SUMMARY PATTERNS. Learning Objectives: In this module, you will be introduced to the design patterns vs. MapReduce, the general structure of the course, and project work. Also, discussion of Summary Patterns: Patterns that give a top-level summary view of large data sets. Topics: MapReduce review, why design patterns are required for MapReduce, discussion of different classes of design patterns, discussion of project work and the problem, about abstract patterns, types of abstract patterns - numerical abstract patterns, inverted index pattern and count counter pattern, Description, Applicability, Structure (how mappers, combinators, and reducers are used in this pattern), use cases, analogies with Pig & SLQ, Performance Analysis, code walkthrough example and data flow.
FILTER PATTERNS. Learning Objectives: In this module, we'll look at filtering patterns: patterns that create subsets of data for a more granular view. Topics: About Filter Patterns, explains and distinguishes 4 different types of filter patterns: Filter Pattern, Bloom Filter Pattern, Top Ten Pattern and Distinctive Pattern, Description, Applicability, Structure (how mappers are used , combiners and reducers in this pattern), use cases, analogies with Pig & SLQ, Performance Analysis, example code traversal and data flow. . Click on the "go to course" button to learn more details at edureka!
DATA ORGANIZATION PATTERNS . Learning Objectives: In this module, we will discuss data organization patterns: patterns that deal with data reorganization and transformation. The categories of these patterns are used together to achieve the final goal. Topics: About organization patterns, explain 5 different types of organization patterns: structured to hierarchical pattern, partition pattern, grouping pattern, total order sorting pattern and shuffling pattern, description, applicability, structure (how to use the mappers, combiners and reducers in this pattern ), use cases, analogies with Pig & SLQ, Performance Analysis, code walkthrough example and data flow. . Click on the "go to course" button to learn more details at edureka!
MATCH PATTERNS. Learning Objectives: In this module, we will discuss Joining Patterns: Patterns to use when your data is scattered across multiple sources and you want to discover interesting relationships by 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 , the structure (how mappers, combiners and reducers are used in this pattern), use cases, analogies with Pig & SLQ, performance analysis, code walkthrough and data flow example. . Click on the "go to course" button to learn more details at edureka!
Instructor-led sessions will address all your concerns in real time.
Unlimited access to the course's online learning repository.
Develop a project with live accompaniment, based on any of the cases seen
In each class you will have practical tasks that will help you apply the concepts taught.
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