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PRODID:-//Microsoft Corporation//Outlook MIMEDIR//EN
VERSION:1.0
BEGIN:VEVENT
DTSTART:20111116T011500Z
DTEND:20111116T030000Z
LOCATION:WSCC North Galleria 2nd/3rd Floors
DESCRIPTION;ENCODING=QUOTED-PRINTABLE:ABSTRACT: MapReduce has been very successful in implementing large-scale data-intensive applications.  Because of its simple programming model, MapReduce has also begun being utilized as a programming tool for more general distributed and parallel HPC applications.=0AHowever, its applicability is often limited due to relatively inefficient runtime performance and hence insufficient support for flexible workflows.  In particular, the performance problem is not negligible in iterative MapReduce applications.=0AWe implemented new MapReduce framework SSS based on distributed key-value store, that supports flexible workflows. Mappers and reducers read key-values only from its local storage enjoying high throughput and low latency. =0AWe evaluated SSS comparing with Hadoop using synthetic benchmark and real application. The result showed that SSS is significantly faster than Hadoop, especially for shuffle-intensive jobs and iterative jobs.
SUMMARY:SSS：a MapReduce Framework based on Distributed Key-value Store
PRIORITY:3
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