Re: [PR] feat: Implement Spark-compatible CAST from floating-point/double to decimal [datafusion-comet]

["andygrove (via GitHub)" <gi...@apache.org>]

andygrove commented on code in PR #384:
URL: https://github.com/apache/datafusion-comet/pull/384#discussion_r1594407351


##########
spark/src/test/scala/org/apache/comet/CometCastSuite.scala:
##########
@@ -960,11 +958,19 @@ class CometCastSuite extends CometTestBase with AdaptiveSparkPlanHelper {
               val cometMessageModified = cometMessage
                 .replace("[CAST_INVALID_INPUT] ", "")
                 .replace("[CAST_OVERFLOW] ", "")
-              assert(cometMessageModified == sparkMessage)
+                .replace("[NUMERIC_VALUE_OUT_OF_RANGE] ", "")
+
+              if (sparkMessage.contains("cannot be represented as")) {
+                assert(cometMessage.contains("cannot be represented as"))
+              } else {
+                assert(cometMessageModified == sparkMessage)
+              }
             } else {
               // for Spark 3.2 we just make sure we are seeing a similar type of error
               if (sparkMessage.contains("causes overflow")) {
                 assert(cometMessage.contains("due to an overflow"))
+              } else if (sparkMessage.contains("cannot be represented as")) {
+                assert(cometMessage.contains("cannot be represented as"))

Review Comment:
   I can see that the approach we have for handling error message comparison for Spark 3.2 and 3.3 needs some rethinking. I am going to make a proposal to improve this.
   
   https://github.com/apache/datafusion-comet/issues/402



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