Reliability And Resilience

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Reliability And Resilience

机译：可靠性和弹性

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MPP databases assume that the hardware is relatively reliable and gear fault tolerance and recovery strategies around extra-operational processors. MapReduce assumes clusters large enough that hardware will fail on a regular basis and applies monitoring tools and agents to automatically identify problems and recover. The trade-offs are around cluster size and efficiency. MapReduce is architected for thousands of cluster nodes via brute-force parallelism and redundancy at the cost of processing efficiency. MPP databases, while moving towards handling larger clusters, are engineered to maximize and depend on the output of each node in the cluster, avoiding the processing costs of automated monitoring and constant replication for redundancy.

机译：MPP数据库假定硬件相对可靠，并且围绕额外的操作处理器适应了容错和恢复策略。 MapReduce假定群集足够大，以至于硬件会定期出现故障，并应用监视工具和代理来自动识别问题并进行恢复。权衡取舍于集群规模和效率。 MapReduce通过蛮力并行性和冗余为数千个群集节点设计，但以处理效率为代价。 MPP数据库在朝着处理更大的集群迈进的同时，旨在最大限度地利用并依赖集群中每个节点的输出，从而避免了自动监视和不断复制冗余的处理成本。

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《Release 1.0》 |2009年第11期|26-26|共1页
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Reliability And Resilience

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