cs.berkeley.edu

Improving mapreduce performance in heterogeneous environments

Authors: 
Zaharia, Matei; Konwinski, Andy; Joseph, Anthony D.; Katz, Randy; Stoica, Ion

Abstract
MapReduce is emerging as an important programming
model for large-scale data-parallel applications such as
web indexing, data mining, and scientific simulation.
Hadoop is an open-source implementation of MapRe-
duce enjoying wide adoption and is often used for short
jobs where low response time is critical. Hadoop’s per-
formance is closely tied to its task scheduler, which im-
plicitly assumes that cluster nodes are homogeneous and
tasks make progress linearly, and uses these assumptions
to decide when to speculatively re-execute tasks that ap-

Year: 
2008
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