This allows to make an average out of date types.

Under the hood we take an average of the days since
epoch, and convert it to a date again. This requires
the date object to be casted to a double to perform
the average.

Error in invokeJava(isStatic = FALSE, objId$id, methodName, ...) :
  org.apache.spark.sql.AnalysisException: cannot resolve 'avg(date)' due to data type mismatch: function average requires numeric types, not DateType;
	at org.apache.spark.sql.catalyst.analysis.package$AnalysisErrorAt.failAnalysis(package.scala:42)
	at org.apache.spark.sql.catalyst.analysis.CheckAnalysis$$anonfun$checkAnalysis$1$$anonfun$apply$2.applyOrElse(CheckAnalysis.scala:61)
	at org.apache.spark.sql.catalyst.analysis.CheckAnalysis$$anonfun$checkAnalysis$1$$anonfun$apply$2.applyOrElse(CheckAnalysis.scala:53)
	at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$transformUp$1.apply(TreeNode.scala:293)
	at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$transformUp$1.apply(TreeNode.scala:293)
	at org.apache.spark.sql.catalyst.trees.CurrentOrigin$.withOrigin(TreeNode.scala:51)
	at org.apache.spark.sql.catalyst.trees.TreeNode.transformUp(TreeNode.scala:292)
	at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$5.apply(TreeNode.scala:290)
	at org.apache.spark.sql.

…0520

This is days since epoch

…0520