guesstimator Estimates the performance of a distributed system based on a sample set of data
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Python library Python distributed system distributed system

guesstimator Description

guesstimator is a Python module that estimates the performance of a distributed system based on a sample set of data.- Redis backed.- It's meant to be simple; pretty much all you get is an increment operation.Creating a Sample SetThis should only be done once, for each performance metric that will be tracked.guesstimator = Guesstimator()guesstimator.create_sample_set( name='sample_set_name', recording_frequency=0.5)- name the name of the sample set.- recording_frequency how frequently should we actually write the metric to Redis? 0.5 indicates that we will record the metric 50% of the time. 5% is the default.Recording Performance DataOnce you have created a sample set, workers in the distributed begin recording performance data to it.Writes will be performed to Redis with the probability set when creating the sample set.guesstimator = Guesstimator()guesstimator.record('sample_set_name')Reading Performance DataWhile there are multiple workers, there should be a single reader of performance data. A good use-case might be a Ganglia plugin.Getting the timestamp and operation countguesstimator = Guesstimator()timestamp, operation_count = guesstimator.read('sample_set_name')- timestamp is the unix time since guesstimator started tracking performance information.- operation_count the estimated number of operations that have occurred since timestamp.Reseting timestamp and operation countguesstimator = Guesstimator()guesstimator.reset('sample_set_name')This sets timestamp to the current time, and operation_count back to zero.Product's homepage

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