Google introduced the MapReduce algorithm to perform massively parallel processing of very large data sets using clusters of commodity hardware. MapReduce is a core Google technology and key to ...

When the Big Data moniker is applied to a discussion, it’s often assumed that Hadoop is, or should be, involved. But perhaps that’s just doctrinaire. Hadoop, at its core, consists of HDFS (the Hadoop ...

Implemented Map Reduce algorithms to: compute the word count, produce modified tri-grams around keywords, generate inverted indices for the given dataset and perform relational join on two datasets to ...

Finding frequent itemsets is one of the most important fields of data mining. Apriori algorithm is the most established algorithm for finding frequent itemsets from a transactional dataset; however, ...

Google and its MapReduce framework may rule the roost when it comes to massive-scale data processing, but there’s still plenty of that goodness to go around. This article gets you started with Hadoop, ...

This project implements a simple MapReduce algorithm in Rust. It reads a set of strings and counts the occurrences of each word, demonstrating basic parallel processing using threads.

Abstract: In recent years the MapReduce framework has become one of the most popular parallel computing platform for processing big data. It is frequently used by companies such as Facebook, IBM, and ...

Abstract: With the rapid development of e-commerce, how to discover useful association rules from large-scale shopping data has become a hot research topic. Apriori algorithm is a classical algorithm ...