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https://issues.apache.org/jira/browse/SPARK-17390?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Sean Owen updated SPARK-17390:
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Priority: Minor (was: Major)
Summary: optimize MultivariateOnlineSummerizer by making the summarized
target configurable (was: optimize MultivariantOnlineSummerizer by making the
summarized target configurable)
> optimize MultivariateOnlineSummerizer by making the summarized target
> configurable
> ----------------------------------------------------------------------------------
>
> Key: SPARK-17390
> URL: https://issues.apache.org/jira/browse/SPARK-17390
> Project: Spark
> Issue Type: Improvement
> Components: ML, MLlib
> Reporter: Weichen Xu
> Priority: Minor
> Original Estimate: 24h
> Remaining Estimate: 24h
>
> optimize MultivariantOnlineSummerizer by making the summarized target
> configurable.
> for example, if we only need to summarize `mean` and `variance`
> we only need to accumulate the following vectors.
> currMean, weightSum, currM2n.
> so that we can avoid useless computation and serialization, especially when
> we use MultivariantOnlineSummerizer in RDD.aggregate, when the data dimemsion
> is large, the extra serialization cost will be large.
> because MultivariantOnlineSummerizer can be used widely, it is worth to do
> this optimization.
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