LNCS 7640 - Euro-Par 2012: Parallel Processing Workshops
نویسندگان
چکیده
MapReduce is a popular programming model for distributeddata processing. Extensive research has been conducted on the reliability of MapReduce, ranging from adaptive and on-demand fault-tolerance tonew fault-tolerance models. However, realistic benchmarks are still miss-ing to analyze and compare the effectiveness of these proposals. To date, most MapReduce fault-tolerance solutions have been evaluated using mi-crobenchmarks in an ad-hoc and overly simplified setting, which may notbe representative of real-world applications. This paper presents MRBS, a comprehensive benchmark suite for evaluating the dependability ofMapReduce systems. MRBS includes five benchmarks covering severalapplication domains and a wide range of execution scenarios such as data-intensive vs. compute-intensive applications, or batch applicationsvs. online interactive applications. MRBS allows to inject various typesof faults at different rates and produces extensive reliability, availability and performance statistics. The paper illustrates the use of MRBS withHadoop clusters.
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تاریخ انتشار 2012