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Some Map-Reduce Application Examples and Ideas

June 13, 2013 0 Comments

Recently we have studied and applied map-reduce framework to solve different types of problem of selecting and grouping of data for analysis in different directions.

We have posted some of our posts to understand Big Data and Map-Reduce programming -

How Big Data Can Help Small Organisations?

Map Reduce Programming – Concise Definition

Map Reduce Programming in MongoDB Shell

Here we will discuss some unique scenarios where we can use Map Reduce Framework…

1> Medical Use Case -

Input Data - Repository of Disease Contents.

Map Function - use of map function for disease name as key and document name as value. Output of <<Dissease name,Content Name — Content Link>> as input to reduce function and save the output in text file or other repository.

Reduce Function - use of reduce function to count the no of documents as values and disease name as key and merge results from all machines under HDFS.

Output Data - Disease name as key and frequency of documents as values and save it to repository.

Application Navigation – Disease name (count of documents) –> Contents for the Disease –>> Navigate to Content

2> Sports Use Case -

Input Data - Repository of Cricket Sports Contents.

Map Function - use of map function for country name as key and document name as value. Output of <<Country name,Content Name — Content Link>> as input to reduce function and save the output in text file or other repository.

Reduce Function - use of reduce function to count the no of documents as values and country name as key and merge results from all machines under HDFS.

Output Data – Country name as key and frequency of documents as values and save it to repository.

Application Navigation – Country name (count of documents) –> Contents for the Country –>> Navigate to Content

Note : Here we can use Map Reduce Chaining of Work -

Map – Map of <<Player Name,Content Name>> From the Country Specific Document Sub Set.

Reduce – Player Name as key and frequency of documents as values and save it to repository.

3> Travel and Tourism Use Case -

Input Data - Repository of Tourism Contents within a country.

Map Function - use of map function for tourist place name as key and document name as value. Output of <<Place name,Content Name — Content Link>> as input to reduce function and save the output in text file or other repository.

Reduce Function - use of reduce function to count the no of documents as values and place name as key and merge results from all machines under HDFS.

Output Data - Place name as key and frequency of documents as values and save it to repository.

Application Navigation - Place name (count of documents) –> Contents for the Place –>> Navigate to Content

4> Product Brand Use Case -

Input Data - Repository of Product Brand Contents within a country.

Map Function - use of map function for product brand name as key and document name as value. Output of <<product brand name,Content Name — Content Link>> as input to reduce function and save the output in text file or other repository.

Reduce Function - use of reduce function to count the no of documents as values and product brand name as key and merge results from all machines under HDFS.

Output Data – product brand name as key and frequency of documents as values and save it to repository.

Application Navigation - product brand name (count of documents) –> Contents for the Place –>> Navigate to Content

We will discuss more of the scenarios/use cases for map reduce framework and keep this document updated as we work further.

So keep reading and commenting.

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