[SPARK-49987][SQL] Fix the error prompt when seedExpression is non-…

…foldable in `randstr`

### What changes were proposed in this pull request?
The pr aims to
- fix the `error prompt` when `seedExpression` is `non-foldable` in `randstr`.
- use `toSQLId` to set the parameter value `inputName` for `randstr ` and `uniform` of `NON_FOLDABLE_INPUT`.

### Why are the changes needed?
- Let me take an example
```scala
val df = Seq(1.1).toDF("a")
df.createOrReplaceTempView("t")
sql("SELECT randstr(1, a) from t").show(false)
```

- Before
<img width="1255" alt="image" src="https://github.com/user-attachments/assets/4e14af7f-19ab-41e7-bdef-836ce86c8ecc">

```shell
[DATATYPE_MISMATCH.NON_FOLDABLE_INPUT] Cannot resolve "randstr(1, a)" due to data type mismatch: the input seedExpression should be a foldable INT or SMALLINT expression; however, got "a". SQLSTATE: 42K09; line 1 pos 7;
'Project [unresolvedalias(randstr(1, a#5, false))]
+- SubqueryAlias t
   +- View (`t`, [a#5])
      +- Project [value#1 AS a#5]
         +- LocalRelation [value#1]
```

- After
```shell
[DATATYPE_MISMATCH.NON_FOLDABLE_INPUT] Cannot resolve "randstr(1, a)" due to data type mismatch: the input seed should be a foldable INT or SMALLINT expression; however, got "a". SQLSTATE: 42K09; line 1 pos 7;
'Project [unresolvedalias(randstr(1, a#5, false))]
+- SubqueryAlias t
   +- View (`t`, [a#5])
      +- Project [value#1 AS a#5]
         +- LocalRelation [value#1]
```

- The `parameter` name (`seedExpression`) in the error message does not match the `parameter` name (`seed`) seen  in docs by the end-user.
<img width="787" alt="image" src="https://github.com/user-attachments/assets/5c03acab-f57d-40b7-b5aa-8d37fd2cc557">

### Does this PR introduce _any_ user-facing change?
Yes, When `seed` is `non-foldable `, the end-user will get a consistent experience in the error prompt.

### How was this patch tested?
Update existed UT.

### Was this patch authored or co-authored using generative AI tooling?
No.

Closes #48490 from panbingkun/SPARK-49987.

Authored-by: panbingkun <panbingkun@baidu.com>
Signed-off-by: Max Gekk <max.gekk@gmail.com>

sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/randomExpressions.scala

@@ -21,7 +21,7 @@ import org.apache.spark.SparkException
 import org.apache.spark.sql.catalyst.InternalRow
 import org.apache.spark.sql.catalyst.analysis.{FunctionRegistry, TypeCheckResult, UnresolvedSeed}
 import org.apache.spark.sql.catalyst.analysis.TypeCheckResult.DataTypeMismatch
-import org.apache.spark.sql.catalyst.expressions.ExpectsInputTypes.{ordinalNumber, toSQLExpr, toSQLType}
+import org.apache.spark.sql.catalyst.expressions.ExpectsInputTypes.{ordinalNumber, toSQLExpr, toSQLId, toSQLType}
 import org.apache.spark.sql.catalyst.expressions.codegen.{CodegenContext, CodeGenerator, ExprCode, FalseLiteral}
 import org.apache.spark.sql.catalyst.expressions.codegen.Block._
 import org.apache.spark.sql.catalyst.trees.{BinaryLike, TernaryLike, UnaryLike}
@@ -263,7 +263,7 @@ case class Uniform(min: Expression, max: Expression, seedExpression: Expression,
             result = DataTypeMismatch(
               errorSubClass = "NON_FOLDABLE_INPUT",
               messageParameters = Map(
-                "inputName" -> name,
+                "inputName" -> toSQLId(name),
                 "inputType" -> requiredType,
                 "inputExpr" -> toSQLExpr(expr)))
           } else expr.dataType match {
@@ -374,14 +374,14 @@ case class RandStr(
     var result: TypeCheckResult = TypeCheckResult.TypeCheckSuccess
     def requiredType = "INT or SMALLINT"
     Seq((length, "length", 0),
-      (seedExpression, "seedExpression", 1)).foreach {
+      (seedExpression, "seed", 1)).foreach {
       case (expr: Expression, name: String, index: Int) =>
         if (result == TypeCheckResult.TypeCheckSuccess) {
           if (!expr.foldable) {
             result = DataTypeMismatch(
               errorSubClass = "NON_FOLDABLE_INPUT",
               messageParameters = Map(
-                "inputName" -> name,
+                "inputName" -> toSQLId(name),
                 "inputType" -> requiredType,
                 "inputExpr" -> toSQLExpr(expr)))
           } else expr.dataType match {

sql/core/src/test/resources/sql-tests/analyzer-results/random.sql.out

@@ -188,7 +188,7 @@ org.apache.spark.sql.catalyst.ExtendedAnalysisException
   "sqlState" : "42K09",
   "messageParameters" : {
     "inputExpr" : "\"col\"",
-    "inputName" : "seed",
+    "inputName" : "`seed`",
     "inputType" : "integer or floating-point",
     "sqlExpr" : "\"uniform(10, 20, col)\""
   },
@@ -211,7 +211,7 @@ org.apache.spark.sql.catalyst.ExtendedAnalysisException
   "sqlState" : "42K09",
   "messageParameters" : {
     "inputExpr" : "\"col\"",
-    "inputName" : "min",
+    "inputName" : "`min`",
     "inputType" : "integer or floating-point",
     "sqlExpr" : "\"uniform(col, 10, 0)\""
   },
@@ -436,7 +436,7 @@ org.apache.spark.sql.catalyst.ExtendedAnalysisException
   "sqlState" : "42K09",
   "messageParameters" : {
     "inputExpr" : "\"col\"",
-    "inputName" : "length",
+    "inputName" : "`length`",
     "inputType" : "INT or SMALLINT",
     "sqlExpr" : "\"randstr(col, 0)\""
   },
@@ -459,7 +459,7 @@ org.apache.spark.sql.catalyst.ExtendedAnalysisException
   "sqlState" : "42K09",
   "messageParameters" : {
     "inputExpr" : "\"col\"",
-    "inputName" : "seedExpression",
+    "inputName" : "`seed`",
     "inputType" : "INT or SMALLINT",
     "sqlExpr" : "\"randstr(10, col)\""
   },

sql/core/src/test/resources/sql-tests/results/random.sql.out

@@ -240,7 +240,7 @@ org.apache.spark.sql.catalyst.ExtendedAnalysisException
   "sqlState" : "42K09",
   "messageParameters" : {
     "inputExpr" : "\"col\"",
-    "inputName" : "seed",
+    "inputName" : "`seed`",
     "inputType" : "integer or floating-point",
     "sqlExpr" : "\"uniform(10, 20, col)\""
   },
@@ -265,7 +265,7 @@ org.apache.spark.sql.catalyst.ExtendedAnalysisException
   "sqlState" : "42K09",
   "messageParameters" : {
     "inputExpr" : "\"col\"",
-    "inputName" : "min",
+    "inputName" : "`min`",
     "inputType" : "integer or floating-point",
     "sqlExpr" : "\"uniform(col, 10, 0)\""
   },
@@ -520,7 +520,7 @@ org.apache.spark.sql.catalyst.ExtendedAnalysisException
   "sqlState" : "42K09",
   "messageParameters" : {
     "inputExpr" : "\"col\"",
-    "inputName" : "length",
+    "inputName" : "`length`",
     "inputType" : "INT or SMALLINT",
     "sqlExpr" : "\"randstr(col, 0)\""
   },
@@ -545,7 +545,7 @@ org.apache.spark.sql.catalyst.ExtendedAnalysisException
   "sqlState" : "42K09",
   "messageParameters" : {
     "inputExpr" : "\"col\"",
-    "inputName" : "seedExpression",
+    "inputName" : "`seed`",
     "inputType" : "INT or SMALLINT",
     "sqlExpr" : "\"randstr(10, col)\""
   },

sql/core/src/test/scala/org/apache/spark/sql/DataFrameFunctionsSuite.scala

@@ -478,7 +478,7 @@ class DataFrameFunctionsSuite extends QueryTest with SharedSparkSession {
       intercept[AnalysisException](df.select(expr)),
       condition = "DATATYPE_MISMATCH.NON_FOLDABLE_INPUT",
       parameters = Map(
-        "inputName" -> "length",
+        "inputName" -> "`length`",
         "inputType" -> "INT or SMALLINT",
         "inputExpr" -> "\"a\"",
         "sqlExpr" -> "\"randstr(a, 10)\""),
@@ -530,7 +530,7 @@ class DataFrameFunctionsSuite extends QueryTest with SharedSparkSession {
       intercept[AnalysisException](df.select(expr)),
       condition = "DATATYPE_MISMATCH.NON_FOLDABLE_INPUT",
       parameters = Map(
-        "inputName" -> "min",
+        "inputName" -> "`min`",
         "inputType" -> "integer or floating-point",
         "inputExpr" -> "\"a\"",
         "sqlExpr" -> "\"uniform(a, 10)\""),