资 源 简 介
Why do we develop the HaLoop project?
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. However, these new platforms do not have built-in support for iterative programs, which arise naturally in many applications including data mining, web ranking, graph processing, model fitting, and so on.
What is HaLoop?
Simply speaking, HaLoop = Ha, Loop:-) HaLoop is a modified version of the Hadoop MapReduce framework, designed to serve these applications. HaLoop not only extends MapReduce with programming support for iterative applications, but also dramatically improves their efficiency by making the task scheduler loop-aware and by adding various caching mechanisms. We evaluate HaLoop on real q
