Mapreduce Design Patterns Training

• Develop a better understanding about the frequently used Design Patterns in MapReduce 
• Know the scenarios where the patterns should be applied for a better result 
• Learn to write mature code using MapReduce 
• Learn to practice the use of MapReduce

1. Introduction and Summarization Patterns

• 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) uses cases analogies to Pig & SLQ Performance Analysis
• Example code walk-through & data flow.

2. Filtering Patterns

• About Filtering Patterns
• Explain and 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

3. Data Organization Patterns

• 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

4. Join Patterns

• 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

5. Meta Patterns & Graph Patterns

• 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.

6. Input Output Pattern & Project Review

• 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