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Abstract MapReduce is a framework for processing la MapReduce is a framework for processing large data sets largely used in cloud computing. MapReduce implementations like Hadoop can tolerate crashes and file corruptions, but there is evidence that general arbitrary faults do occur and can affect the correctness of job executions. Furthermore, many individual cloud outages have been reported, raising concerns about depending on a single cloud. We present a MapReduce runtime that tolerates arbitrary faults and runs in a set of clouds at a reasonable cost in terms of computation and execution time. The main challenge is to avoid sending through the internet the huge amount of data that would normally be exchanged between map and reduce tasks be exchanged between map and reduce tasks
Address San Francisco, California  +
Author Miguel Correia + , Pedro Costa + , Marcelo Pasin + , Alysson Bessani + , Fernando Ramos + , Paulo Verissimo +
Booktitle First International Workshop on Dependability Issues in Cloud Computing (DISCCO 2012)  +
Document Document for Publication-Correia2012-CoC.pdf +
Key Correia2012:CoC  +
NumPubDate 2,012  +
ResearchLine Fault and Intrusion Tolerance in Open Distributed Systems (FIT) +
Title On the Feasibility of Byzantine Fault-Tolerant MapReduce in Clouds-of-Cloud  +
Type inproceedings  +
Year 2012  +
Has improper value forThis property is a special property in this wiki. Month  + , Url  +
Categories Publication  +
Modification dateThis property is a special property in this wiki. 21 January 2013 15:31:14  +
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