[SPARK-38748][SQL][TESTS] Test the error class: PIVOT_VALUE_DATA_TYPE…

…_MISMATCH

## What changes were proposed in this pull request?
This PR aims to add a test for the error class PIVOT_VALUE_DATA_TYPE_MISMATCH to `QueryCompilationErrorsSuite`.

### Why are the changes needed?
The changes improve test coverage, and document expected error messages in tests.

### Does this PR introduce any user-facing change?
No

### How was this patch tested?
By running new test:
```
$ build/sbt "sql/testOnly *QueryCompilationErrorsSuite*"
```

Closes apache#36400 from panbingkun/SPARK-38748.

Authored-by: panbingkun <[email protected]>
Signed-off-by: Max Gekk <[email protected]>

sql/core/src/test/scala/org/apache/spark/sql/errors/QueryCompilationErrorsSuite.scala

@@ -20,7 +20,7 @@ package org.apache.spark.sql.errors
 import org.apache.spark.sql.{AnalysisException, IntegratedUDFTestUtils, QueryTest, Row}
 import org.apache.spark.sql.api.java.{UDF1, UDF2, UDF23Test}
 import org.apache.spark.sql.expressions.SparkUserDefinedFunction
-import org.apache.spark.sql.functions.{grouping, grouping_id, sum, udf}
+import org.apache.spark.sql.functions.{grouping, grouping_id, lit, struct, sum, udf}
 import org.apache.spark.sql.internal.SQLConf
 import org.apache.spark.sql.types.{IntegerType, MapType, StringType, StructField, StructType}
 
@@ -491,6 +491,28 @@ class QueryCompilationErrorsSuite
         msg = "Field name c.X is ambiguous and has 2 matching fields in the struct.; line 1 pos 0")
     }
   }
+
+  test("PIVOT_VALUE_DATA_TYPE_MISMATCH: can't cast pivot value data type (struct) " +
+    "to pivot column data type (int)") {
+    val df = Seq(
+      ("dotNET", 2012, 10000),
+      ("Java", 2012, 20000),
+      ("dotNET", 2012, 5000),
+      ("dotNET", 2013, 48000),
+      ("Java", 2013, 30000)
+    ).toDF("course", "year", "earnings")
+
+    checkErrorClass(
+      exception = intercept[AnalysisException] {
+        df.groupBy(df("course")).pivot(df("year"), Seq(
+          struct(lit("dotnet"), lit("Experts")),
+          struct(lit("java"), lit("Dummies")))).
+          agg(sum($"earnings")).collect()
+      },
+      errorClass = "PIVOT_VALUE_DATA_TYPE_MISMATCH",
+      msg = "Invalid pivot value 'struct(col1, dotnet, col2, Experts)': value data type " +
+        "struct<col1:string,col2:string> does not match pivot column data type int")
+  }
 }
 
 class MyCastToString extends SparkUserDefinedFunction(