Github user brkyvz commented on a diff in the pull request:
https://github.com/apache/spark/pull/5842#discussion_r29567133
--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/execution/stat/StatFunctions.scala
---
@@ -77,4 +79,27 @@ private[sql] object StatFunctions {
})
counts.cov
}
+
+ /** Generate a table of frequencies for the elements of two columns. */
+ private[sql] def crossTabulate(df: DataFrame, col1: String, col2:
String): DataFrame = {
+ val tableName = s"${col1}_$col2"
+ val counts = df.groupBy(col1, col2).agg(col(col1), col(col2),
count("*")).collect()
--- End diff --
Would taking 1e8 have such a high cost if there are only for example 100 in
total? The reason I chose 1e8, was 1e4 * 1e4, basically the limit we put on the
number of columns.
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