[GitHub] [spark] HyukjinKwon commented on a change in pull request #33170: [SPARK-35967][SQL] Update nullability based on column statistics

[GitBox <gi...@apache.org>]

HyukjinKwon commented on a change in pull request #33170:
URL: https://github.com/apache/spark/pull/33170#discussion_r662870040



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File path: sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/LogicalRelation.scala
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@@ -81,6 +81,14 @@ object LogicalRelation {
     // The v1 source may return schema containing char/varchar type. We replace char/varchar
     // with "annotated" string type here as the query engine doesn't support char/varchar yet.
     val schema = CharVarcharUtils.replaceCharVarcharWithStringInSchema(relation.schema)
-    LogicalRelation(relation, schema.toAttributes, Some(table), false)
+    val attributes = schema.toAttributes
+    val output = table.stats.map(_.colStats) match {
+      case Some(colStats) =>
+        attributes
+          .map(a => a.withNullability(colStats.get(a.name).forall(_.nullCount.forall(_ > 0L))))

Review comment:
       Hmmm .. does this mean that if a table is saved with nullable schema but the table doesn't have nulls, here the schema becomes non-nullable when we read it back?




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