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离散流:一个可扩展的流处理的容错模型

Discretized Streams: A Fault-Tolerant Model for Scalable Stream Processing

作者:Matei Zaharia; Tathagata Das; Haoyuan Li; Timothy Hunter; Scott Shenker ;Ion Stoica 作者单位:University of California, Berkeley 加工时间:2013-12-18 信息来源:EECS 索取原文[15 页]
关键词:离散流;可扩展;容错模型;大数据;实时到达;故障恢复
摘 要:Many “big data” applications need to act on data arriving in real time. However, current programming models for distributed stream processing are relatively low-level, often leaving the user to worry about consistency of state across the system and fault recovery. Furthermore, the models that provide fault recovery do so in an expensive manner, requiring either hot replication or long recovery times. We propose a new programming model, discretized streams (D-Streams), that offers a high-level functional API, strong consistency, and efficient fault recovery.
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