stevomitric commented on code in PR #56409:
URL: https://github.com/apache/spark/pull/56409#discussion_r3386620527
##########
sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/expressions/CastSuiteBase.scala:
##########
@@ -745,6 +745,14 @@ abstract class CastSuiteBase extends SparkFunSuite with
ExpressionEvalHelper {
// ... but blocks the lossy narrowing nanos(p) -> micros to avoid silent
truncation.
assert(!Cast.canANSIStoreAssign(TimestampNTZNanosType(p),
TimestampNTZType))
assert(!Cast.canANSIStoreAssign(TimestampLTZNanosType(p), TimestampType))
+
+ // SPARK-57323: DATE <-> nanos requires an explicit CAST in both
directions (the explicit
+ // cast is rewritten through the microsecond type by
ResolveTimestampNanosCast), so STRICT
+ // store assignment and ANSI store assignment both reject it.
+ assert(!Cast.canANSIStoreAssign(DateType, TimestampNTZNanosType(p)))
+ assert(!Cast.canANSIStoreAssign(TimestampNTZNanosType(p), DateType))
+ assert(!Cast.canANSIStoreAssign(DateType, TimestampLTZNanosType(p)))
+ assert(!Cast.canANSIStoreAssign(TimestampLTZNanosType(p), DateType))
Review Comment:
The comment says STRICT store assignment also rejects it, but only
`canANSIStoreAssign` is asserted. STRICT goes through `Cast.canUpCast`, which
is false today only because `UpCastRule` has no nanos arms at all — a future
blanket datetime arm there would regress this silently. Mind adding:
```scala
assert(!Cast.canUpCast(DateType, TimestampNTZNanosType(p)))
assert(!Cast.canUpCast(TimestampNTZNanosType(p), DateType))
assert(!Cast.canUpCast(DateType, TimestampLTZNanosType(p)))
assert(!Cast.canUpCast(TimestampLTZNanosType(p), DateType))
```
##########
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/ResolveTimestampNanosCast.scala:
##########
@@ -0,0 +1,66 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements. See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.spark.sql.catalyst.analysis
+
+import org.apache.spark.sql.catalyst.expressions.Cast
+import org.apache.spark.sql.catalyst.plans.logical.LogicalPlan
+import org.apache.spark.sql.catalyst.rules.Rule
+import org.apache.spark.sql.catalyst.trees.TreePattern.CAST
+import org.apache.spark.sql.types.{DataType, DateType, TimestampLTZNanosType,
TimestampNTZNanosType, TimestampNTZType, TimestampType}
+
+/**
+ * Rewrites casts between [[DateType]] and the nanosecond-precision timestamp
types
+ * ([[TimestampLTZNanosType]] / [[TimestampNTZNanosType]]) into a two-step
cast that goes through
+ * the corresponding microsecond-precision timestamp type:
+ *
+ * - `nanos(p) -> DATE` ==> `nanos(p) -> micros -> DATE`
+ * - `DATE -> nanos(p)` ==> `DATE -> micros -> nanos(p)`
+ *
+ * where the microsecond counterpart is `TIMESTAMP` for `*_LTZ` and
`TIMESTAMP_NTZ` for `*_NTZ`.
+ * Both component casts already exist (`nanos(p) <-> micros` and `micros <->
DATE`), so no dedicated
+ * `DATE <-> nanos` conversion is needed in [[Cast]] and the semantics match
the microsecond
+ * `DATE <-> TIMESTAMP` casts: the LTZ directions are resolved in the session
time zone and the NTZ
+ * directions on the UTC wall-clock grid; sub-microsecond digits and the
time-of-day are dropped
+ * when narrowing to `DATE`.
+ *
+ * `Cast.canCast` intentionally does not allow `DATE <-> nanos` directly, so
such a cast stays
+ * unresolved until this rule rewrites it into the resolvable nested form. The
new casts inherit the
+ * original `timeZoneId` and `evalMode`; the only zone-sensitive part (the
`micros <-> DATE` cast)
+ * gets its session time zone from [[ResolveTimeZone]] within the same
fixed-point batch.
+ */
+object ResolveTimestampNanosCast extends Rule[LogicalPlan] {
+
+ /** The microsecond-precision timestamp counterpart of a
nanosecond-precision timestamp type. */
+ private def microTimestampType(dt: DataType): Option[DataType] = dt match {
+ case _: TimestampLTZNanosType => Some(TimestampType)
+ case _: TimestampNTZNanosType => Some(TimestampNTZType)
+ case _ => None
+ }
+
+ override def apply(plan: LogicalPlan): LogicalPlan =
+ plan.resolveExpressionsWithPruning(_.containsPattern(CAST), ruleId) {
Review Comment:
The single-pass resolver has no counterpart for this rewrite. Nothing under
`analysis/resolver/` knows about nanos casts and `ResolverGuard` doesn't bail
out on them, so `ExpressionResolver.validateResolvedExpressionGenerically` hits
`checkInputDataTypes().isFailure` for `CAST(date AS nanos)`:
- pure single-pass mode: the query fails with DATATYPE_MISMATCH while
fixed-point succeeds;
- dual-run mode: `HybridAnalyzer` throws
`singlePassFailedFixedPointSucceeded`.
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