Digital Themes

Map and Reduce

What is MapReduce?

MapReduce is a programming model used to map input data into smaller memory blocks and reduce those blocks into digestible insights. A MapReduce job involves map and reduce tasks and algorithms. Hadoop MapReduce framework maintains the same format of a set of key value pairs for both inputs and outputs. The MapReduce program model accesses big data and filters the massive amounts of data collected through data processing mappers and reducers.

MapReduce programs are often used to migrate immense databases into more scalable, searchable, and ultimately usable formats. The map function takes a large input file, processes that data, and splits it into smaller key value pairs. Then, the map output goes to the reducers to be assigned value for analysis. As corporations now have the technology available to receive tremendous amounts of data, MapReduce can help to organize, analyze, migrate, and better interpret all of this data.

Employing MapReduce functions can reduce the amount of untapped data by pre-sorting and processing information into formats suitable for analytics. Map and reduce output values can provide clearer, actionable insights into customer behavior.

What are the business benefits of MapReduce programming?

  • New, unique sign-ups - MapReduce programming can reveal how many new sign-ups your site has received, and any pertinent data regarding those new sign-ups, including where they're located, how they accessed your site, and the length of time taken to sign-up.

  • Reconciliation - Analytics with easier access to pre-sorted and organized information can provide visibility into transactions much quicker than traditional reconciliation methods.

  • Page views - MapReduce programs can dive deeper into page views, showing which pages are viewed the most, the longest, and which aren't viewed at all. This can show not only where your customer values lie, but also reveal possible dead links and untethered pages.

  • Marketing - MapReduce can aid marketers in completing sentiment analysis, allowing for greater insight into customer attitudes and behavior.

  • Flexibility - These programming models can run with structured or unstructured data from several different sources and create more manageable data sets primed and ready for analytics.

  • Scalability - MapReduce organizes data in a way that makes data migration and scalability much more accessible options due to its agility in storing and distributing across multiple servers.
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