Dryad: All content tagged as Dryad in NoSQL databases and polyglot persistence
In Dec.2010, Joab Jackson writes for IDG News Service: Microsoft’s Dryad technology to take on Google’s MapReduce. Just 11 months later, in Nov.2011, Doug Henschen writes for the same IDG News Service: Microsoft Ditches Dryad, Focuses On Hadoop - Software.
Nothing wrong with Microsoft decision. Same cannot be said though about the titles and articles published by the IDG News Service network.
Original title and link: Claim Chowder: Microsoft’s Dryad Technology to Take on Google’s MapReduce ( ©myNoSQL)
A paper from the Seattle University of Washington (Yingyi Bu, Bill Howe, Magdalena Balazinska, Michael D. Ernst):
The growing demand for large-scale data mining and data analysis applications has led both industry and academia to design new types of highly scalable data-intensive computing platforms. MapReduce and Dryad are two popular platforms in which the dataflow takes the form of a directed acyclic graph of operators. These platforms lack built-in support for iterative programs, which arise naturally in many applications including data mining, web ranking, graph analysis, model fitting, and so on. This paper presents HaLoop, a modified version of the Hadoop MapReduce framework that is designed to serve these applications. HaLoop not only extends MapReduce with programming support for iterative applications, it also dramatically improves their efficiency by making the task scheduler loop-aware and by adding various caching mechanisms. We evaluated HaLoop on real queries and real datasets. Compared with Hadoop, on average, HaLoop reduces query runtimes by 1.85, and shuffles only 4% of the data between mappers and reducers.
The embedded paper and download link after the break