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https://issues.apache.org/jira/browse/SPARK-13943?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15204219#comment-15204219
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Liang-Chi Hsieh commented on SPARK-13943:
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Yes, I think so.
> The behavior of sum(booleantype) in Spark DataFrames is not intuitive
> ---------------------------------------------------------------------
>
> Key: SPARK-13943
> URL: https://issues.apache.org/jira/browse/SPARK-13943
> Project: Spark
> Issue Type: Bug
> Components: PySpark
> Reporter: Wes McKinney
>
> In NumPy and pandas, summing boolean data produces an integer indicating the
> number of True values:
> {code}
> In [1]: import numpy as np
> In [2]: arr = np.random.randn(1000000)
> In [3]: (arr > 0).sum()
> Out[3]: 499065
> {code}
> In PySpark, {{sql.functions.sum(expr)}} results in an error:
> {code}
> AnalysisException: u"cannot resolve 'sum((`data0` > CAST(0 AS DOUBLE)))' due
> to data type mismatch: function sum requires numeric types, not BooleanType;"
> {code}
> FWIW, R is the same:
> {code}
> > sum(rnorm(1000000) > 0)
> [1] 499139
> {code}
> Spark should consider emulating the behavior of R and Python in those
> environments.
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