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https://issues.apache.org/jira/browse/SPARK-11057?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Narine Kokhlikyan updated SPARK-11057:
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Summary: SQL: corr and cov for many columns (was: SparkSQL: corr and cov
for many columns)
> SQL: corr and cov for many columns
> ----------------------------------
>
> Key: SPARK-11057
> URL: https://issues.apache.org/jira/browse/SPARK-11057
> Project: Spark
> Issue Type: New Feature
> Reporter: Narine Kokhlikyan
>
> Hi there,
> As we know R has the option to calculate the correlation and covariance for
> all columns of a dataframe or between columns of two dataframes.
> If we look at apache math package we can see that, they have that too.
> http://commons.apache.org/proper/commons-math/apidocs/org/apache/commons/math3/stat/correlation/PearsonsCorrelation.html#computeCorrelationMatrix%28org.apache.commons.math3.linear.RealMatrix%29
> In case we have as input only one DataFrame:
> ------------------------------------------------------
> for correlation:
> cor[i,j] = cor[j,i]
> and for the main diagonal we can have 1s.
> ---------------------
> for covariance:
> cov[i,j] = cov[j,i]
> and for main diagonal: we can compute the variance for that specific column:
> See:
> http://commons.apache.org/proper/commons-math/apidocs/org/apache/commons/math3/stat/correlation/Covariance.html#computeCovarianceMatrix%28org.apache.commons.math3.linear.RealMatrix%29
> Let me know what do you think.
> I'm working on this and will make a pull request soon.
> Thanks,
> Narine
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