Github user tejasapatil commented on a diff in the pull request:
https://github.com/apache/spark/pull/15959#discussion_r89030028
--- Diff:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/logical/Statistics.scala
---
@@ -58,60 +61,127 @@ case class Statistics(
}
}
+
/**
- * Statistics for a column.
+ * Statistics collected for a column.
+ *
+ * 1. Supported data types are defined in `ColumnStat.supportsType`.
+ * 2. The JVM data type stored in min/max is the external data type (used
in Row) for the
+ * corresponding Catalyst data type. For example, for DateType we store
java.sql.Date, and for
+ * TimestampType we store java.sql.Timestamp.
+ * 3. For integral types, they are all upcasted to longs, i.e. shorts are
stored as longs.
+ *
+ * @param ndv number of distinct values
--- End diff --
nit: `ndv` sounds weird. Why not use `numDistinctVals` ?
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