[SPARK-49909][SQL] Fix the pretty name of some expressions

### What changes were proposed in this pull request?
The pr aims to fix the `pretty name` of some `expressions`, includes: `random`, `to_varchar`, `current_database`, `curdate`, `dateadd` and `array_agg`.

### Why are the changes needed?
The actual function name used does not match the displayed name, as shown below:
- Before:
<img width="573" alt="image" src="https://github.com/user-attachments/assets/f5785c80-f6cb-494f-a15e-9258eca688a7">

- After:
<img width="570" alt="image" src="https://github.com/user-attachments/assets/792a7092-ccbf-49f4-a616-19110e5c2361">

### Does this PR introduce _any_ user-facing change?
Yes, Make the header of the data seen by the end-user from `Spark SQL` consistent with the `actual function name` used.

### How was this patch tested?
- Pass GA.
- Update existed UT.

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

Closes apache#48385 from panbingkun/SPARK-49909.

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

python/pyspark/sql/functions/builtin.py

@@ -4921,44 +4921,44 @@ def array_agg(col: "ColumnOrName") -> Column:
     >>> from pyspark.sql import functions as sf
     >>> df = spark.createDataFrame([[1],[1],[2]], ["c"])
     >>> df.agg(sf.sort_array(sf.array_agg('c'))).show()
-    +---------------------------------+
-    |sort_array(collect_list(c), true)|
-    +---------------------------------+
-    |                        [1, 1, 2]|
-    +---------------------------------+
+    +------------------------------+
+    |sort_array(array_agg(c), true)|
+    +------------------------------+
+    |                     [1, 1, 2]|
+    +------------------------------+
 
     Example 2: Using array_agg function on a string column
 
     >>> from pyspark.sql import functions as sf
     >>> df = spark.createDataFrame([["apple"],["apple"],["banana"]], ["c"])
     >>> df.agg(sf.sort_array(sf.array_agg('c'))).show(truncate=False)
-    +---------------------------------+
-    |sort_array(collect_list(c), true)|
-    +---------------------------------+
-    |[apple, apple, banana]           |
-    +---------------------------------+
+    +------------------------------+
+    |sort_array(array_agg(c), true)|
+    +------------------------------+
+    |[apple, apple, banana]        |
+    +------------------------------+
 
     Example 3: Using array_agg function on a column with null values
 
     >>> from pyspark.sql import functions as sf
     >>> df = spark.createDataFrame([[1],[None],[2]], ["c"])
     >>> df.agg(sf.sort_array(sf.array_agg('c'))).show()
-    +---------------------------------+
-    |sort_array(collect_list(c), true)|
-    +---------------------------------+
-    |                           [1, 2]|
-    +---------------------------------+
+    +------------------------------+
+    |sort_array(array_agg(c), true)|
+    +------------------------------+
+    |                        [1, 2]|
+    +------------------------------+
 
     Example 4: Using array_agg function on a column with different data types
 
     >>> from pyspark.sql import functions as sf
     >>> df = spark.createDataFrame([[1],["apple"],[2]], ["c"])
     >>> df.agg(sf.sort_array(sf.array_agg('c'))).show()
-    +---------------------------------+
-    |sort_array(collect_list(c), true)|
-    +---------------------------------+
-    |                    [1, 2, apple]|
-    +---------------------------------+
+    +------------------------------+
+    |sort_array(array_agg(c), true)|
+    +------------------------------+
+    |                 [1, 2, apple]|
+    +------------------------------+
     """
     return _invoke_function_over_columns("array_agg", col)
 
@@ -8712,31 +8712,31 @@ def dateadd(start: "ColumnOrName", days: Union["ColumnOrName", int]) -> Column:
     >>> spark.createDataFrame(
     ...     [('2015-04-08', 2,)], ['dt', 'add']
     ... ).select(sf.dateadd("dt", 1)).show()
-    +---------------+
-    |date_add(dt, 1)|
-    +---------------+
-    |     2015-04-09|
-    +---------------+
+    +--------------+
+    |dateadd(dt, 1)|
+    +--------------+
+    |    2015-04-09|
+    +--------------+
 
     >>> import pyspark.sql.functions as sf
     >>> spark.createDataFrame(
     ...     [('2015-04-08', 2,)], ['dt', 'add']
     ... ).select(sf.dateadd("dt", sf.lit(2))).show()
-    +---------------+
-    |date_add(dt, 2)|
-    +---------------+
-    |     2015-04-10|
-    +---------------+
+    +--------------+
+    |dateadd(dt, 2)|
+    +--------------+
+    |    2015-04-10|
+    +--------------+
 
     >>> import pyspark.sql.functions as sf
     >>> spark.createDataFrame(
     ...     [('2015-04-08', 2,)], ['dt', 'add']
     ... ).select(sf.dateadd("dt", -1)).show()
-    +----------------+
-    |date_add(dt, -1)|
-    +----------------+
-    |      2015-04-07|
-    +----------------+
+    +---------------+
+    |dateadd(dt, -1)|
+    +---------------+
+    |     2015-04-07|
+    +---------------+
     """
     days = _enum_to_value(days)
     days = lit(days) if isinstance(days, int) else days
@@ -10343,11 +10343,11 @@ def current_database() -> Column:
     Examples
     --------
     >>> spark.range(1).select(current_database()).show()
-    +----------------+
-    |current_schema()|
-    +----------------+
-    |         default|
-    +----------------+
+    +------------------+
+    |current_database()|
+    +------------------+
+    |           default|
+    +------------------+
     """
     return _invoke_function("current_database")
 

sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/aggregate/collect.scala

@@ -21,7 +21,7 @@ import scala.collection.mutable
 import scala.collection.mutable.Growable
 
 import org.apache.spark.sql.catalyst.InternalRow
-import org.apache.spark.sql.catalyst.analysis.TypeCheckResult
+import org.apache.spark.sql.catalyst.analysis.{FunctionRegistry, TypeCheckResult}
 import org.apache.spark.sql.catalyst.analysis.TypeCheckResult.DataTypeMismatch
 import org.apache.spark.sql.catalyst.expressions._
 import org.apache.spark.sql.catalyst.trees.UnaryLike
@@ -118,7 +118,8 @@ case class CollectList(
 
   override def createAggregationBuffer(): mutable.ArrayBuffer[Any] = mutable.ArrayBuffer.empty
 
-  override def prettyName: String = "collect_list"
+  override def prettyName: String =
+    getTagValue(FunctionRegistry.FUNC_ALIAS).getOrElse("collect_list")
 
   override def eval(buffer: mutable.ArrayBuffer[Any]): Any = {
     new GenericArrayData(buffer.toArray)

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

@@ -150,7 +150,8 @@ case class CurrentDate(timeZoneId: Option[String] = None)
   override def withTimeZone(timeZoneId: String): TimeZoneAwareExpression =
     copy(timeZoneId = Option(timeZoneId))
 
-  override def prettyName: String = "current_date"
+  override def prettyName: String =
+    getTagValue(FunctionRegistry.FUNC_ALIAS).getOrElse("current_date")
 }
 
 // scalastyle:off line.size.limit
@@ -329,7 +330,7 @@ case class DateAdd(startDate: Expression, days: Expression)
     })
   }
 
-  override def prettyName: String = "date_add"
+  override def prettyName: String = getTagValue(FunctionRegistry.FUNC_ALIAS).getOrElse("date_add")
 
   override protected def withNewChildrenInternal(
     newLeft: Expression, newRight: Expression): DateAdd = copy(startDate = newLeft, days = newRight)

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

@@ -202,7 +202,8 @@ object AssertTrue {
 case class CurrentDatabase() extends LeafExpression with Unevaluable {
   override def dataType: DataType = SQLConf.get.defaultStringType
   override def nullable: Boolean = false
-  override def prettyName: String = "current_schema"
+  override def prettyName: String =
+    getTagValue(FunctionRegistry.FUNC_ALIAS).getOrElse("current_database")
   final override val nodePatterns: Seq[TreePattern] = Seq(CURRENT_LIKE)
 }
 

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

@@ -19,7 +19,7 @@ package org.apache.spark.sql.catalyst.expressions
 
 import java.util.Locale
 
-import org.apache.spark.sql.catalyst.analysis.{ExpressionBuilder, TypeCheckResult}
+import org.apache.spark.sql.catalyst.analysis.{ExpressionBuilder, FunctionRegistry, TypeCheckResult}
 import org.apache.spark.sql.catalyst.analysis.TypeCheckResult.DataTypeMismatch
 import org.apache.spark.sql.catalyst.expressions.Cast._
 import org.apache.spark.sql.catalyst.expressions.codegen.{CodegenContext, CodeGenerator, ExprCode}
@@ -307,7 +307,10 @@ case class ToCharacter(left: Expression, right: Expression)
       inputTypeCheck
     }
   }
-  override def prettyName: String = "to_char"
+
+  override def prettyName: String =
+    getTagValue(FunctionRegistry.FUNC_ALIAS).getOrElse("to_char")
+
   override def nullSafeEval(decimal: Any, format: Any): Any = {
     val input = decimal.asInstanceOf[Decimal]
     numberFormatter.format(input)

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

@@ -19,7 +19,7 @@ package org.apache.spark.sql.catalyst.expressions
 
 import org.apache.spark.SparkException
 import org.apache.spark.sql.catalyst.InternalRow
-import org.apache.spark.sql.catalyst.analysis.{TypeCheckResult, UnresolvedSeed}
+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.codegen.{CodegenContext, CodeGenerator, ExprCode, FalseLiteral}
@@ -128,8 +128,12 @@ case class Rand(child: Expression, hideSeed: Boolean = false) extends Nondetermi
   }
 
   override def flatArguments: Iterator[Any] = Iterator(child)
+
+  override def prettyName: String =
+    getTagValue(FunctionRegistry.FUNC_ALIAS).getOrElse("rand")
+
   override def sql: String = {
-    s"rand(${if (hideSeed) "" else child.sql})"
+    s"$prettyName(${if (hideSeed) "" else child.sql})"
   }
 
   override protected def withNewChildInternal(newChild: Expression): Rand = copy(child = newChild)

sql/connect/common/src/test/resources/query-tests/explain-results/function_array_agg.explain

@@ -1,2 +1,2 @@
-Aggregate [collect_list(a#0, 0, 0) AS collect_list(a)#0]
+Aggregate [array_agg(a#0, 0, 0) AS array_agg(a)#0]
 +- LocalRelation <empty>, [id#0L, a#0, b#0, d#0, e#0, f#0, g#0]

sql/connect/common/src/test/resources/query-tests/explain-results/function_curdate.explain

@@ -1,2 +1,2 @@
-Project [current_date(Some(America/Los_Angeles)) AS current_date()#0]
+Project [curdate(Some(America/Los_Angeles)) AS curdate()#0]
 +- LocalRelation <empty>, [d#0, t#0, s#0, x#0L, wt#0]

sql/connect/common/src/test/resources/query-tests/explain-results/function_current_database.explain

@@ -1,2 +1,2 @@
-Project [current_schema() AS current_schema()#0]
+Project [current_database() AS current_database()#0]
 +- LocalRelation <empty>, [id#0L, a#0, b#0, d#0, e#0, f#0, g#0]

sql/connect/common/src/test/resources/query-tests/explain-results/function_dateadd.explain

@@ -1,2 +1,2 @@
-Project [date_add(d#0, 2) AS date_add(d, 2)#0]
+Project [dateadd(d#0, 2) AS dateadd(d, 2)#0]
 +- LocalRelation <empty>, [d#0, t#0, s#0, x#0L, wt#0]

sql/connect/common/src/test/resources/query-tests/explain-results/function_random_with_seed.explain

@@ -1,2 +1,2 @@
-Project [random(1) AS rand(1)#0]
+Project [random(1) AS random(1)#0]
 +- LocalRelation <empty>, [id#0L, a#0, b#0, d#0, e#0, f#0, g#0]

sql/connect/common/src/test/resources/query-tests/explain-results/function_to_varchar.explain

@@ -1,2 +1,2 @@
-Project [to_char(cast(b#0 as decimal(30,15)), $99.99) AS to_char(b, $99.99)#0]
+Project [to_varchar(cast(b#0 as decimal(30,15)), $99.99) AS to_varchar(b, $99.99)#0]
 +- LocalRelation <empty>, [id#0L, a#0, b#0, d#0, e#0, f#0, g#0]

sql/core/src/test/resources/sql-functions/sql-expression-schema.md

@@ -99,9 +99,9 @@
 | org.apache.spark.sql.catalyst.expressions.Csc | csc | SELECT csc(1) | struct<CSC(1):double> |
 | org.apache.spark.sql.catalyst.expressions.CsvToStructs | from_csv | SELECT from_csv('1, 0.8', 'a INT, b DOUBLE') | struct<from_csv(1, 0.8):struct<a:int,b:double>> |
 | org.apache.spark.sql.catalyst.expressions.CumeDist | cume_dist | SELECT a, b, cume_dist() OVER (PARTITION BY a ORDER BY b) FROM VALUES ('A1', 2), ('A1', 1), ('A2', 3), ('A1', 1) tab(a, b) | struct<a:string,b:int,cume_dist() OVER (PARTITION BY a ORDER BY b ASC NULLS FIRST RANGE BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW):double> |
-| org.apache.spark.sql.catalyst.expressions.CurDateExpressionBuilder | curdate | SELECT curdate() | struct<current_date():date> |
+| org.apache.spark.sql.catalyst.expressions.CurDateExpressionBuilder | curdate | SELECT curdate() | struct<curdate():date> |
 | org.apache.spark.sql.catalyst.expressions.CurrentCatalog | current_catalog | SELECT current_catalog() | struct<current_catalog():string> |
-| org.apache.spark.sql.catalyst.expressions.CurrentDatabase | current_database | SELECT current_database() | struct<current_schema():string> |
+| org.apache.spark.sql.catalyst.expressions.CurrentDatabase | current_database | SELECT current_database() | struct<current_database():string> |
 | org.apache.spark.sql.catalyst.expressions.CurrentDatabase | current_schema | SELECT current_schema() | struct<current_schema():string> |
 | org.apache.spark.sql.catalyst.expressions.CurrentDate | current_date | SELECT current_date() | struct<current_date():date> |
 | org.apache.spark.sql.catalyst.expressions.CurrentTimeZone | current_timezone | SELECT current_timezone() | struct<current_timezone():string> |
@@ -110,7 +110,7 @@
 | org.apache.spark.sql.catalyst.expressions.CurrentUser | session_user | SELECT session_user() | struct<session_user():string> |
 | org.apache.spark.sql.catalyst.expressions.CurrentUser | user | SELECT user() | struct<user():string> |
 | org.apache.spark.sql.catalyst.expressions.DateAdd | date_add | SELECT date_add('2016-07-30', 1) | struct<date_add(2016-07-30, 1):date> |
-| org.apache.spark.sql.catalyst.expressions.DateAdd | dateadd | SELECT dateadd('2016-07-30', 1) | struct<date_add(2016-07-30, 1):date> |
+| org.apache.spark.sql.catalyst.expressions.DateAdd | dateadd | SELECT dateadd('2016-07-30', 1) | struct<dateadd(2016-07-30, 1):date> |
 | org.apache.spark.sql.catalyst.expressions.DateDiff | date_diff | SELECT date_diff('2009-07-31', '2009-07-30') | struct<date_diff(2009-07-31, 2009-07-30):int> |
 | org.apache.spark.sql.catalyst.expressions.DateDiff | datediff | SELECT datediff('2009-07-31', '2009-07-30') | struct<datediff(2009-07-31, 2009-07-30):int> |
 | org.apache.spark.sql.catalyst.expressions.DateFormatClass | date_format | SELECT date_format('2016-04-08', 'y') | struct<date_format(2016-04-08, y):string> |
@@ -264,7 +264,7 @@
 | org.apache.spark.sql.catalyst.expressions.RPadExpressionBuilder | rpad | SELECT rpad('hi', 5, '??') | struct<rpad(hi, 5, ??):string> |
 | org.apache.spark.sql.catalyst.expressions.RaiseErrorExpressionBuilder | raise_error | SELECT raise_error('custom error message') | struct<raise_error(USER_RAISED_EXCEPTION, map(errorMessage, custom error message)):void> |
 | org.apache.spark.sql.catalyst.expressions.Rand | rand | SELECT rand() | struct<rand():double> |
-| org.apache.spark.sql.catalyst.expressions.Rand | random | SELECT random() | struct<rand():double> |
+| org.apache.spark.sql.catalyst.expressions.Rand | random | SELECT random() | struct<random():double> |
 | org.apache.spark.sql.catalyst.expressions.RandStr | randstr | SELECT randstr(3, 0) AS result | struct<result:string> |
 | org.apache.spark.sql.catalyst.expressions.Randn | randn | SELECT randn() | struct<randn():double> |
 | org.apache.spark.sql.catalyst.expressions.Rank | rank | SELECT a, b, rank(b) OVER (PARTITION BY a ORDER BY b) FROM VALUES ('A1', 2), ('A1', 1), ('A2', 3), ('A1', 1) tab(a, b) | struct<a:string,b:int,RANK() OVER (PARTITION BY a ORDER BY b ASC NULLS FIRST ROWS BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW):int> |
@@ -340,7 +340,7 @@
 | org.apache.spark.sql.catalyst.expressions.TimeWindow | window | SELECT a, window.start, window.end, count(*) as cnt FROM VALUES ('A1', '2021-01-01 00:00:00'), ('A1', '2021-01-01 00:04:30'), ('A1', '2021-01-01 00:06:00'), ('A2', '2021-01-01 00:01:00') AS tab(a, b) GROUP by a, window(b, '5 minutes') ORDER BY a, start | struct<a:string,start:timestamp,end:timestamp,cnt:bigint> |
 | org.apache.spark.sql.catalyst.expressions.ToBinary | to_binary | SELECT to_binary('abc', 'utf-8') | struct<to_binary(abc, utf-8):binary> |
 | org.apache.spark.sql.catalyst.expressions.ToCharacterBuilder | to_char | SELECT to_char(454, '999') | struct<to_char(454, 999):string> |
-| org.apache.spark.sql.catalyst.expressions.ToCharacterBuilder | to_varchar | SELECT to_varchar(454, '999') | struct<to_char(454, 999):string> |
+| org.apache.spark.sql.catalyst.expressions.ToCharacterBuilder | to_varchar | SELECT to_varchar(454, '999') | struct<to_varchar(454, 999):string> |
 | org.apache.spark.sql.catalyst.expressions.ToDegrees | degrees | SELECT degrees(3.141592653589793) | struct<DEGREES(3.141592653589793):double> |
 | org.apache.spark.sql.catalyst.expressions.ToNumber | to_number | SELECT to_number('454', '999') | struct<to_number(454, 999):decimal(3,0)> |
 | org.apache.spark.sql.catalyst.expressions.ToRadians | radians | SELECT radians(180) | struct<RADIANS(180):double> |
@@ -402,7 +402,7 @@
 | org.apache.spark.sql.catalyst.expressions.aggregate.BoolOr | any | SELECT any(col) FROM VALUES (true), (false), (false) AS tab(col) | struct<any(col):boolean> |
 | org.apache.spark.sql.catalyst.expressions.aggregate.BoolOr | bool_or | SELECT bool_or(col) FROM VALUES (true), (false), (false) AS tab(col) | struct<bool_or(col):boolean> |
 | org.apache.spark.sql.catalyst.expressions.aggregate.BoolOr | some | SELECT some(col) FROM VALUES (true), (false), (false) AS tab(col) | struct<some(col):boolean> |
-| org.apache.spark.sql.catalyst.expressions.aggregate.CollectList | array_agg | SELECT array_agg(col) FROM VALUES (1), (2), (1) AS tab(col) | struct<collect_list(col):array<int>> |
+| org.apache.spark.sql.catalyst.expressions.aggregate.CollectList | array_agg | SELECT array_agg(col) FROM VALUES (1), (2), (1) AS tab(col) | struct<array_agg(col):array<int>> |
 | org.apache.spark.sql.catalyst.expressions.aggregate.CollectList | collect_list | SELECT collect_list(col) FROM VALUES (1), (2), (1) AS tab(col) | struct<collect_list(col):array<int>> |
 | org.apache.spark.sql.catalyst.expressions.aggregate.CollectSet | collect_set | SELECT collect_set(col) FROM VALUES (1), (2), (1) AS tab(col) | struct<collect_set(col):array<int>> |
 | org.apache.spark.sql.catalyst.expressions.aggregate.Corr | corr | SELECT corr(c1, c2) FROM VALUES (3, 2), (3, 3), (6, 4) as tab(c1, c2) | struct<corr(c1, c2):double> |

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

@@ -722,19 +722,19 @@ Project [chr(cast(167 as bigint)) AS chr(167)#x, chr(cast(247 as bigint)) AS chr
 -- !query
 SELECT to_varchar(78.12, '$99.99')
 -- !query analysis
-Project [to_char(78.12, $99.99) AS to_char(78.12, $99.99)#x]
+Project [to_varchar(78.12, $99.99) AS to_varchar(78.12, $99.99)#x]
 +- OneRowRelation
 
 
 -- !query
 SELECT to_varchar(111.11, '99.9')
 -- !query analysis
-Project [to_char(111.11, 99.9) AS to_char(111.11, 99.9)#x]
+Project [to_varchar(111.11, 99.9) AS to_varchar(111.11, 99.9)#x]
 +- OneRowRelation
 
 
 -- !query
 SELECT to_varchar(12454.8, '99,999.9S')
 -- !query analysis
-Project [to_char(12454.8, 99,999.9S) AS to_char(12454.8, 99,999.9S)#x]
+Project [to_varchar(12454.8, 99,999.9S) AS to_varchar(12454.8, 99,999.9S)#x]
 +- OneRowRelation

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

@@ -2,5 +2,5 @@
 -- !query
 select current_database(), current_schema(), current_catalog()
 -- !query analysis
-Project [current_schema() AS current_schema()#x, current_schema() AS current_schema()#x, current_catalog() AS current_catalog()#x]
+Project [current_database() AS current_database()#x, current_schema() AS current_schema()#x, current_catalog() AS current_catalog()#x]
 +- OneRowRelation

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

@@ -1133,7 +1133,7 @@ SELECT
 FROM VALUES
   (1), (2), (1) AS tab(col)
 -- !query analysis
-Aggregate [collect_list(col#x, 0, 0) AS collect_list(col)#x, collect_list(col#x, 0, 0) AS collect_list(col)#x]
+Aggregate [collect_list(col#x, 0, 0) AS collect_list(col)#x, array_agg(col#x, 0, 0) AS array_agg(col)#x]
 +- SubqueryAlias tab
    +- LocalRelation [col#x]
 
@@ -1147,7 +1147,7 @@ FROM VALUES
   (1,4),(2,3),(1,4),(2,4) AS v(a,b)
 GROUP BY a
 -- !query analysis
-Aggregate [a#x], [a#x, collect_list(b#x, 0, 0) AS collect_list(b)#x, collect_list(b#x, 0, 0) AS collect_list(b)#x]
+Aggregate [a#x], [a#x, collect_list(b#x, 0, 0) AS collect_list(b)#x, array_agg(b#x, 0, 0) AS array_agg(b)#x]
 +- SubqueryAlias v
    +- LocalRelation [a#x, b#x]
 

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

@@ -776,7 +776,7 @@ Project [NULL AS Expected#x, variablereference(system.session.var1=CAST(NULL AS
 -- !query
 DECLARE OR REPLACE VARIABLE var1 STRING DEFAULT CURRENT_DATABASE()
 -- !query analysis
-CreateVariable defaultvalueexpression(cast(current_schema() as string), CURRENT_DATABASE()), true
+CreateVariable defaultvalueexpression(cast(current_database() as string), CURRENT_DATABASE()), true
 +- ResolvedIdentifier org.apache.spark.sql.catalyst.analysis.FakeSystemCatalog$@xxxxxxxx, session.var1
 
 

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

@@ -1235,22 +1235,22 @@ struct<chr(167):string,chr(247):string,chr(215):string>
 -- !query
 SELECT to_varchar(78.12, '$99.99')
 -- !query schema
-struct<to_char(78.12, $99.99):string>
+struct<to_varchar(78.12, $99.99):string>
 -- !query output
 $78.12
 
 
 -- !query
 SELECT to_varchar(111.11, '99.9')
 -- !query schema
-struct<to_char(111.11, 99.9):string>
+struct<to_varchar(111.11, 99.9):string>
 -- !query output
 ##.#
 
 
 -- !query
 SELECT to_varchar(12454.8, '99,999.9S')
 -- !query schema
-struct<to_char(12454.8, 99,999.9S):string>
+struct<to_varchar(12454.8, 99,999.9S):string>
 -- !query output
 12,454.8+

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

@@ -2,6 +2,6 @@
 -- !query
 select current_database(), current_schema(), current_catalog()
 -- !query schema
-struct<current_schema():string,current_schema():string,current_catalog():string>
+struct<current_database():string,current_schema():string,current_catalog():string>
 -- !query output
 default	default	spark_catalog