30-05-2019 дата публикации
Номер: US20190166173A1
Автор:
Jingren Zhou,
Zhengping Qian,
Peter Zabback,
Wei Lin,
ZHOU JINGREN,
QIAN ZHENGPING,
ZABBACK PETER,
LIN WEI,
Zhou, Jingren,
Qian, Zhengping,
Zabback, Peter,
Lin, Wei
Принадлежит:
A low-latency cloud-scale computation environment includes a query language, optimization, scheduling, fault tolerance and fault recovery. An event model can be used to extend a declarative query language so that temporal analysis of event of an event stream can be performed. Extractors and outputters can be used to define and implement functions that extend the capabilities of the event-based query language. A script written in the extended query language can be translated into an optimal parallel continuous execution plan. Execution of the plan can be orchestrated by a streaming job manager which schedules vertices on available computing machines. The streaming job manager can monitor overall job execution. Fault tolerance can be provided by tracking execution progress and data dependencies in each vertex. In the event of a failure, another instance of the failed vertex can be scheduled. An optimal recovery point can be determined based on checkpoints and data dependencies. 1. (canceled)2. A computing device , comprising:at least one processor:at least one memory connected to the at least one processor; and monitor execution information about streaming jobs executed by a plurality of vertices executing on a plurality of computing devices, each vertex of the plurality of vertices configured to process events associated with one or more streaming jobs,', 'detect, based on the monitored execution information, a failed vertex of the plurality of vertices, and', 'restart the failed vertex., 'a streaming job manager configured to'}, 'a distributed stream processing system that is at least partially stored in the at least one memory and executed by the at least one processor, the distributed stream processing system comprising'}3. The computing device of claim 2 , wherein the plurality of vertices includes a stream extractor vertex configured to consume events of one or more event streams claim 2 , including continually waiting for and performing computations on data ...
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