Identifying task instance outliers based on metric data in a large scale parallel processing system
Among other disclosed subject matter, a method includes receiving metric data associated with an execution of each of a plurality of task instances. The plurality of task instances include task instances associated with a task and the metric data for each task instance relating to execution performa...
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| Format | Patent |
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| Language | English |
| Published |
08.03.2016
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| Online Access | Get full text |
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| Summary: | Among other disclosed subject matter, a method includes receiving metric data associated with an execution of each of a plurality of task instances. The plurality of task instances include task instances associated with a task and the metric data for each task instance relating to execution performance of the task instance. The method includes for each task instance determining a deviation of the metric data associated with the task instance relative to an overall deviation of the metric data for the plurality of task instances of the task during each of a plurality of intervals and combining deviation measurements for the task instance that exceed a threshold deviation to obtain a combined deviation value. Each deviation measurement corresponds to the deviation of the metric data for one of the plurality of intervals. The method includes ranking the combined deviation values associated with at least a subset of the task instances. |
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