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1512 high scalability-2013-09-05-Paper: MillWheel: Fault-Tolerant Stream Processing at Internet Scale


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Introduction: Ever wonder what powers Google's world spirit sensing  Zeitgeist service ? No, it's not a homunculus of Georg Wilhelm Friedrich Hegel  sitting in each browser. It's actually a stream processing (think streaming MapReduce on steroids) system called MillWheel, described in this very well written paper:  MillWheel: Fault-Tolerant Stream Processing at Internet Scale . MillWheel isn't just used for Zeitgeist at Google, it's also used for streaming joins for a variety of Ads customers, generalized anomaly-detection service, and network switch and cluster health monitoring. Abstract: MillWheel is a framework for building low-latency data-processing applications that is widely used at Google. Users specify a directed computation graph and application code for individual nodes, and the system manages persistent state and the continuous flow of records, all within the envelope of the framework’s fault-tolerance guarantees.   This paper describes MillWheel’s programming model as well as it


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1 Ever wonder what powers Google's world spirit sensing  Zeitgeist service ? [sent-1, score-0.157]

2 It's actually a stream processing (think streaming MapReduce on steroids) system called MillWheel, described in this very well written paper:  MillWheel: Fault-Tolerant Stream Processing at Internet Scale . [sent-3, score-0.306]

3 MillWheel isn't just used for Zeitgeist at Google, it's also used for streaming joins for a variety of Ads customers, generalized anomaly-detection service, and network switch and cluster health monitoring. [sent-4, score-0.172]

4 Abstract: MillWheel is a framework for building low-latency data-processing applications that is widely used at Google. [sent-5, score-0.101]

5 Users specify a directed computation graph and application code for individual nodes, and the system manages persistent state and the continuous flow of records, all within the envelope of the framework’s fault-tolerance guarantees. [sent-6, score-0.315]

6 This paper describes MillWheel’s programming model as well as its implementation. [sent-7, score-0.171]

7 The case study of a continuous anomaly detector in use at Google serves to motivate how many of MillWheel’s features are used. [sent-8, score-0.277]

8 MillWheel’s programming model provides a notion of logical time, making it simple to write time-based aggregations. [sent-9, score-0.166]

9 MillWheel was designed from the outset with fault tolerance and scalability in mind. [sent-10, score-0.307]

10 In practice, we find that MillWheel’s unique combination of scalability, fault tolerance, and a versatile programming model lends itself to a wide variety of problems at Google. [sent-11, score-0.43]

11 It uses Apache Kafka for messaging, and Apache Hadoop YARN to provide fault tolerance, processor isolation, security, and resource management. [sent-14, score-0.101]

12 Storm : a free and open source distributed realtime computation system. [sent-15, score-0.212]

13 Storm makes it easy to reliably process unbounded streams of data, doing for realtime processing what Hadoop did for batch processing. [sent-16, score-0.356]


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