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https://issues.apache.org/jira/browse/APEXMALHAR-2260?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16204629#comment-16204629
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Ananth edited comment on APEXMALHAR-2260 at 10/14/17 10:24 PM:
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Scoring a scikit learn SVM model on a *2012 macbook pro* gave the following
readings. The model is a standard SVM model on the iris data set.
The test was measuring for latencies as opposed to throughput. All readings are
in *microseconds*.
Result
"github.ananthc.sampleapps.apex.scikitlearn.ScikitLearnSVMJepBenchmark.testSVMIrisPredict":
* 150.427 ±(99.9%) 7.332 us/op [Average]*
(min, avg, max) = (117.998, 150.427, 278.607), stdev = 31.045
CI (99.9%): [143.095, 157.760] (assumes normal distribution)
# Run complete. Total time: 00:08:44
Benchmark Mode Cnt Score Error Units
ScikitLearnSVMJepBenchmark.testSVMIrisPredict avgt 200 150.427 ± 7.332 us/op
was (Author: ananthg.apex):
Scoring a scikit learn SVM model on a *2012 macbook pro* gave the following
readings. The model is a standard SVM model on the iris data set.
The test was measuring for latencies as opposed to throughput. All readings are
in *microseconds*.
Result
"github.ananthc.sampleapps.apex.scikitlearn.ScikitLearnSVMJepBenchmark.testSVMIrisPredict":
* 150.427 ±(99.9%) 7.332 us/op [Average]
* (min, avg, max) = (117.998, 150.427, 278.607), stdev = 31.045
CI (99.9%): [143.095, 157.760] (assumes normal distribution)
# Run complete. Total time: 00:08:44
Benchmark Mode Cnt Score Error Units
ScikitLearnSVMJepBenchmark.testSVMIrisPredict avgt 200 150.427 ± 7.332 us/op
> Python execution for operator logic
> ------------------------------------
>
> Key: APEXMALHAR-2260
> URL: https://issues.apache.org/jira/browse/APEXMALHAR-2260
> Project: Apache Apex Malhar
> Issue Type: New Feature
> Reporter: Thomas Weise
> Assignee: Ananth
> Labels: roadmap
>
> Support execution of Python code in an operator.
> https://lists.apache.org/thread.html/9837b1dee8f909ed400c6030ce5c6a94a12f43183718019dd0bfd228@%3Cdev.apex.apache.org%3E
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