MRQL (the Map-Reduce Query Language) is an SQL-like query language for map-reduce computations. It is implemented on top of Apache's Hadoop. MRQL is powerful enough to express most common data analysis tasks over many different kinds of raw data, including hierarchical data and nested collections, such as XML data. It is more powerful than other current languages, such as Hive and Pig Latin, since it can operate on more complex data and supports more powerful query constructs, thus eliminating the need for using explicit map-reduce code.
Almost everyone has heard of Google's MapReduce framework, but very few have ever hacked around with the idea of map and reduce. These two idioms are borrowed from functional programming, and form the basis of Google's framework. Although Python is not a functional programming language, it has built-in support for both of these concepts. A…
Following up on KMeans Clustering Now Running on Elastic MapReduce, Stephen Green has generously documented the steps that was necessary to get an example of k-Means clustering up and running on Amazon’s Elastic MapReduce (EMR) on the Apache Lucene Mahout wiki.
One night at the pub we discussed whether one could replace Hadoop (a massive and comprehensive implementation of Mapreduce) with a single bash script, an awk command, sort, and a sprinkling of netcat. This turned into a weekend project dubbed bashreduce
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