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04.03.2009
# Collaborative Map-Reduce in the Browser
What if you could contribute to a computational (Map-Reduce) job by simply pointing your browser to a URL? Surely your social network wouldn't mind opening a background tab to help you crunch a dataset or two! | 04.03.2009 10:52 Uhr | web javascript mapreduce
12.09.2008
# Cascading
Cascading is a feature rich API for defining and executing complex and fault tolerant data processing workflows on a Hadoop cluster.
The processing API lets the developer quickly assemble complex distributed processes without having to "think" in MapReduce. And to efficiently schedule them based on their dependencies and other available meta-data. | 12.09.2008 09:55 Uhr | mapreduce java
08.09.2008
# Disco
Disco is an open-source implementation of the Map-Reduce framework for distributed computing. As the original framework, Disco supports parallel computations over large data sets on unreliable cluster of computers.
The Disco core is written in Erlang, a functional language that is designed for building robust fault-tolerant distributed applications. Users of Disco typically write jobs in Python, which makes it possible to express even complex algorithms or data processing tasks often only in tens of lines of code. | 08.09.2008 09:33 Uhr | mapreduce erlang python
# Datawocky: Bridging the Gap between Relational Databases and MapReduce: Three New Approaches
Three approaches have emerged to bridge the gap between relational databases and Map Reduce. Let's examine each approach in turn and then discuss their pros and cons. | 08.09.2008 09:28 Uhr | mapreduce
# Goodbye MapReduce, Hello Cascading
Cascading abstracts away MapReduce into a more natural logical model and provides a workflow management layer to handle things like intermediate data and data staleness. | 08.09.2008 09:26 Uhr | mapreduce java google