Blogging Tips: map reduce

Showing posts with label map reduce. Show all posts

MapReduce: Detecting Cycles in Network Graph

I recently received an email from an audience of my blog on Map/Reduce algorithm design regarding how to detect whether a graph is acyclic ...

Inspired by Dr. Gautam Shroff who teaches the class: Web Intelligence and Big data in coursera.org, there are many scenarios where we want t...

Unsupervised machine learning has broad application in many e-commerce sites and one common usage is to find clusters of consumers with comm...

Hadoop Map/Reduce model is very good in processing large amount of data in parallel. It provides a general partitioning mechanism (based o...

Looking back after 2.5 years since my previous post on scalable system design techniques , I've observed an emergence of a set of common...

Since the emerging of Hadoop implementation, I have been trying to morph existing algorithms from various areas into the map/reduce model. ...

Once common feature in Social Network site is to recommend people connection. e.g. "People you may know" from Linkedin. The basi...

In my previous post about Google's Pregel model , a general pattern of parallel graph processing can be expressed as multiple iterations...