Yet Another Introduction to MapReduce (part 2)

I’m sorry for the long delay from the first part. I’ve been pretty busy lately. On this part, I write about the idea of MapReduce, how is it work, and how it distributes the data and process. This article is heavily referenced from MapReduce paper by Google. I write it again to deepen my knowledge about the concept. Enjoy!

What is MapReduce?

According to Wikipedia, MapReduce is a software framework patented by Google to support distributed computing on large data sets on clusters of computers. This framework is presented by Jeffery Dean and Sanjay Ghemawat in OSDI’04: Sixth Symposium on Operating System Design and Implementation on December 2004. The main idea is to utilize functional programming techniques, to obtain processing simplification in distributed environment.

MapReduce processing data using list concept that usually used in functional programming. The process consists of two function, map and reduce function. Each function take list of input elements and produce list of output. Map function take inputs and produce intermediate key-value pairs. These pairs then sent to the reduce function. The reduce function take these intermediate key-value pairs as a input. Then, for the same intermediate key, the function merges together the values to produce output. According to the paper, for every reduce invocation typically produces zero or one output value. Continue reading

Yet Another Introduction to MapReduce (part 1)

There are so many article outside about what is MapReduce, the basic concepts behind it, how it works, and many other things. Even that, I still wanna write a little introduction to MapReduce. It’s mandatory, at least for me, to write about “something” in order to understand the “something”. I challenge my understanding about MapReduce in this post. I’ll use some resources available on the clouds like I mentioned earlier. This is just another introduction to MapReduce.

Data, Data, Data

We are living in the clouds era. Internet provide us with such a great resource to help our lives. In the progress, we created a lot of data. Consider a search engine like Google or Bing. They indexed all of sites across the network. If we are talking about sites these days, that’s a big number we are talking about. Netcraft reported that there are more than 200 Millions sites in the world. It means the search engine must process and analysis a lot of data. Continue reading