[SPARK-40798][SQL][TESTS][FOLLOW-UP] Disable ANSI mode in v2 ALTER TABLE PARTITION test

[HyukjinKwon]

What changes were proposed in this pull request?

This PR is a followup of #38257 that fixes the test case of v2 when ANSI is enabled.

When ANSI mode is enabled, it fails (https://github.com/apache/spark/actions/runs/3353657619/jobs/5556624621) as below:

- ALTER TABLE .. ADD PARTITION using V2 catalog V2 command: SPARK-40798: Alter partition should verify partition value - legacy *** FAILED *** (22 milliseconds)
  org.apache.spark.SparkNumberFormatException: [CAST_INVALID_INPUT] The value 'aaa' of the type "STRING" cannot be cast to "INT" because it is malformed. Correct the value as per the syntax, or change its target type. Use `try_cast` to tolerate malformed input and return NULL instead. If necessary set "spark.sql.ansi.enabled" to "false" to bypass this error.
== SQL(line 1, position 1) ==
ALTER TABLE test_catalog.ns.tbl ADD PARTITION (p='aaa')
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  at org.apache.spark.sql.errors.QueryExecutionErrors$.invalidInputInCastToNumberError(QueryExecutionErrors.scala:164)
  at org.apache.spark.sql.catalyst.util.UTF8StringUtils$.withException(UTF8StringUtils.scala:51)
  at org.apache.spark.sql.catalyst.util.UTF8StringUtils$.toIntExact(UTF8StringUtils.scala:34)
  at org.apache.spark.sql.catalyst.expressions.Cast.$anonfun$castToInt$2(Cast.scala:927)
  at org.apache.spark.sql.catalyst.expressions.Cast.$anonfun$castToInt$2$adapted(Cast.scala:927)
  at org.apache.spark.sql.catalyst.expressions.Cast.buildCast(Cast.scala:588)
  at org.apache.spark.sql.catalyst.expressions.Cast.$anonfun$castToInt$1(Cast.scala:927)
  at org.apache.spark.sql.catalyst.expressions.Cast.nullSafeEval(Cast.scala:1285)
  at org.apache.spark.sql.catalyst.expressions.UnaryExpression.eval(Expression.scala:526)
  at org.apache.spark.sql.catalyst.analysis.ResolvePartitionSpec$.$anonfun$convertToPartIdent$1(ResolvePartitionSpec.scala:81)
  at scala.collection.immutable.List.map(List.scala:293)
  at org.apache.spark.sql.catalyst.analysis.ResolvePartitionSpec$.convertToPartIdent(ResolvePartitionSpec.scala:78)
  at org.apache.spark.sql.catalyst.analysis.ResolvePartitionSpec$.org$apache$spark$sql$catalyst$analysis$ResolvePartitionSpec$$resolvePartitionSpec(ResolvePartitionSpec.scala:71)
  at org.apache.spark.sql.catalyst.analysis.ResolvePartitionSpec$$anonfun$apply$2$$anonfun$applyOrElse$1.applyOrElse(ResolvePartitionSpec.scala:48)
  at org.apache.spark.sql.catalyst.analysis.ResolvePartitionSpec$$anonfun$apply$2$$anonfun$applyOrElse$1.applyOrElse(ResolvePartitionSpec.scala:41)
  at org.apache.spark.sql.catalyst.trees.TreeNode.$anonfun$transformDownWithPruning$1(TreeNode.scala:512)
  at org.apache.spark.sql.catalyst.trees.CurrentOrigin$.withOrigin(TreeNode.scala:104)
  at org.apache.spark.sql.catalyst.trees.TreeNode.transformDownWithPruning(TreeNode.scala:512)
  at org.apache.spark.sql.catalyst.plans.QueryPlan.$anonfun$transformExpressionsDownWithPruning$1(QueryPlan.scala:159)
  at org.apache.spark.sql.catalyst.plans.QueryPlan.$anonfun$mapExpressions$1(QueryPlan.scala:200)
  at org.apache.spark.sql.catalyst.trees.CurrentOrigin$.withOrigin(TreeNode.scala:104)
  at org.apache.spark.sql.catalyst.plans.QueryPlan.transformExpression$1(QueryPlan.scala:200)
  at org.apache.spark.sql.catalyst.plans.QueryPlan.recursiveTransform$1(QueryPlan.scala:211)
  at org.apache.spark.sql.catalyst.plans.QueryPlan.$anonfun$mapExpressions$3(QueryPlan.scala:216)
  at scala.collection.TraversableLike.$anonfun$map$1(TraversableLike.scala:286)
  at scala.collection.mutable.ResizableArray.foreach(ResizableArray.scala:62)
  at scala.collection.mutable.ResizableArray.foreach$(ResizableArray.scala:55)
  at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:49)
  at scala.collection.TraversableLike.map(TraversableLike.scala:286)
  at scala.collection.TraversableLike.map$(TraversableLike.scala:279)
  at scala.collection.AbstractTraversable.map(Traversable.scala:108)

Why are the changes needed?

To recover the broken ANSI build.

Does this PR introduce any user-facing change?

No, test-only.

How was this patch tested?

Manually ran this test case locally.

[HyukjinKwon]

@cloud-fan @gengliangwang @ulysses-you, this is a temporary fix to recover the test case.

The root case here seems like we don't care about spark.sql.storeAssignmentPolicy in V2:

spark/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/ResolvePartitionSpec.scala

Line 81 in 1dd0ca2

Cast(Literal.create(raw, StringType), dt, Some(conf.sessionLocalTimeZone)).eval()

with using a plain cast (that's controlled by the ANSI flag).

Whereas seems like V1 uses the casts from PartitioningUtils.castPartitionSpec that's independent from ANSI flag (respects spark.sql.storeAssignmentPolicy). While I guess we should use the same cast, I made this fix first to make the test pass in case there's some more things to discuss about this.

[ulysses-you]

+1 to use PartitioningUtils.castPartitionSpec

[cloud-fan]

+1, @ulysses-you can you send a PR to fix it later?

[ulysses-you]

sure

[HyukjinKwon]

Merged to master.

[gengliangwang]

@HyukjinKwon Thanks for fixing it!