Charles Reiss
Randy H. Katz
ABSTRACT
MapReduce was designed by Google for large-scale data analysis on slow but cheap disk-based storage. Nevertheless, memory has declined in price to where cost-effective machines offer ever larger memory capacity. Furthermore, a more diverse data analyst community, with smaller datasets, has emerged. These trends motivate new parallel processing frameworks, like Spark [2], with better support for in-memory data analysis.
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- M. Zaharia et al. Spark: Cluster computing with working sets. In HotCloud '10, 2010. Google ScholarDigital Library
Index Terms
- Recommending just enough memory for analytics
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