cloud-fan commented on code in PR #49962:
URL: https://github.com/apache/spark/pull/49962#discussion_r1962788716
##########
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/util/ResolveDefaultColumnsUtil.scala:
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@@ -340,12 +341,44 @@ object ResolveDefaultColumns extends QueryErrorsBase
throw
QueryCompilationErrors.defaultValuesMayNotContainSubQueryExpressions(
"", field.name, defaultSQL)
}
- if (!expr.resolved) {
- throw QueryCompilationErrors.defaultValuesUnresolvedExprError(
- "", field.name, defaultSQL, null)
+
+ val resolvedExpr = expr match {
+ case _: ExprLiteral => expr
+ case c: Cast if c.resolved => expr
+ case _ =>
+ fallbackResolveExistenceDefaultValue(field)
}
- coerceDefaultValue(expr, field.dataType, "", field.name, defaultSQL)
+ coerceDefaultValue(resolvedExpr, field.dataType, "", field.name,
defaultSQL)
+ }
+
+ // In most cases, column existsDefault should already be persisted as
resolved
+ // and constant-folded literal sql, but because they are fetched from
external catalog,
+ // it is possible that this assumption does not hold, so we fallback to full
analysis
+ // if we encounter an unresolved existsDefault
+ private def fallbackResolveExistenceDefaultValue(
+ field: StructField): Expression = {
+ field.getExistenceDefaultValue().map { defaultSQL: String =>
+
+ logWarning(log"Encountered unresolved exists default value: " +
+ log"'${MDC(COLUMN_DEFAULT_VALUE, defaultSQL)}' " +
+ log"for column ${MDC(COLUMN_NAME, field.name)} " +
+ log"with ${MDC(COLUMN_DATA_TYPE_SOURCE, field.dataType)}, " +
+ log"falling back to full analysis.")
+
+ val expr = analyze(field, "", EXISTS_DEFAULT_COLUMN_METADATA_KEY)
+ val literal = expr match {
+ case _: ExprLiteral | _: Cast => expr
+ case _ => throw SparkException.internalError(s"parse existence default
as literal err," +
+ s" field name: ${field.name}, value: $defaultSQL")
+ }
+ // sanity check
+ if (!literal.resolved) {
Review Comment:
I think `def analyze` already did this check?
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