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https://issues.apache.org/jira/browse/SYSTEMML-909?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Mike Dusenberry updated SYSTEMML-909:
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Description:
The {{[determineDataFrameDimensionsIfNeeded(...) |
https://github.com/apache/incubator-systemml/blob/master/src/main/java/org/apache/sysml/api/mlcontext/MLContextConversionUtil.java#L585]}}
function in {{MLContext}} is a major bottleneck, particularly due to the
`javaRDD` call.
The issue I'm seeing is that the javaRDD.count() function causes execution of
the lazy DataFrames I pass in, which are created from another DataFrame via
df.randomSplit([0.8, 0.2]), thus a shuffle occurs. I know that this is going to
happen anyways in the internal conversion, but it wastes a lot of time by
having to also do it in this step too. Assume that I have more data than I can
efficiently cache (~7TB with the potential for much more), so I need to incur
the shuffle step only once on the way into the engine.
was:The {{[determineDataFrameDimensionsIfNeeded(...) |
https://github.com/apache/incubator-systemml/blob/master/src/main/java/org/apache/sysml/api/mlcontext/MLContextConversionUtil.java#L585]}}
function in {{MLContext}} is a major bottleneck, particularly due to the
`javaRDD` call.
> `determineDataFrameDimensionsIfNeeded(...)` is a bottleneck.
>
>
> Key: SYSTEMML-909
> URL: https://issues.apache.org/jira/browse/SYSTEMML-909
> Project: SystemML
> Issue Type: Improvement
>Reporter: Mike Dusenberry
>
> The {{[determineDataFrameDimensionsIfNeeded(...) |
> https://github.com/apache/incubator-systemml/blob/master/src/main/java/org/apache/sysml/api/mlcontext/MLContextConversionUtil.java#L585]}}
> function in {{MLContext}} is a major bottleneck, particularly due to the
> `javaRDD` call.
> The issue I'm seeing is that the javaRDD.count() function causes execution of
> the lazy DataFrames I pass in, which are created from another DataFrame via
> df.randomSplit([0.8, 0.2]), thus a shuffle occurs. I know that this is going
> to happen anyways in the internal conversion, but it wastes a lot of time by
> having to also do it in this step too. Assume that I have more data than I
> can efficiently cache (~7TB with the potential for much more), so I need to
> incur the shuffle step only once on the way into the engine.
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