[SPARK-31393][SQL] Show the correct alias in schema for expression

### What changes were proposed in this pull request?
Some alias of expression can not display correctly in schema. This PR will fix them.
- `TimeWindow`
- `MaxBy`
- `MinBy`
- `UnaryMinus`
- `BitwiseCount`

This PR also fix a typo issue, please look at https://github.com/apache/spark/blob/b7cde42b04b21c9bfee6535199cf385855c15853/sql/core/src/test/scala/org/apache/spark/sql/ExpressionsSchemaSuite.scala#L142

Note:

1. `MaxBy` and `MinBy` extends `MaxMinBy` and the latter add a method `funcName` not needed.  We can reuse `prettyName` to replace `funcName`.
2. Spark SQL exists some function no elegant implementation.For example: `BitwiseCount` override the sql method show below:
`override def sql: String = s"bit_count(${child.sql})"`
I don't think it's elegant enough. Because `Expression` gives the following definitions.
```
  def sql: String = {
    val childrenSQL = children.map(_.sql).mkString(", ")
    s"$prettyName($childrenSQL)"
  }
```
By this definition, `BitwiseCount` should override `prettyName` method.

### Why are the changes needed?
Improve the implement of some expression.

### Does this PR introduce any user-facing change?
 'Yes'. This PR will let user see the correct alias in schema.

### How was this patch tested?
Jenkins test.

Closes #28164 from beliefer/elegant-pretty-name-for-function.

Lead-authored-by: beliefer <[email protected]>
Co-authored-by: gengjiaan <[email protected]>
Signed-off-by: HyukjinKwon <[email protected]>
(cherry picked from commit a89006a)
Signed-off-by: HyukjinKwon <[email protected]>

Author: beliefer

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

@@ -253,7 +253,7 @@ object FunctionRegistry {
     expression[Log2]("log2"),
     expression[Log]("ln"),
     expression[Remainder]("mod", true),
-    expression[UnaryMinus]("negative"),
+    expression[UnaryMinus]("negative", true),
     expression[Pi]("pi"),
     expression[Pmod]("pmod"),
     expression[UnaryPositive]("positive"),

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

@@ -63,6 +63,7 @@ case class TimeWindow(
   override def dataType: DataType = new StructType()
     .add(StructField("start", TimestampType))
     .add(StructField("end", TimestampType))
+  override def prettyName: String = "window"
 
   // This expression is replaced in the analyzer.
   override lazy val resolved = false

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

@@ -31,7 +31,6 @@ abstract class MaxMinBy extends DeclarativeAggregate {
   def valueExpr: Expression
   def orderingExpr: Expression
 
-  protected def funcName: String
   // The predicate compares two ordering values.
   protected def predicate(oldExpr: Expression, newExpr: Expression): Expression
   // The arithmetic expression returns greatest/least value of all parameters.
@@ -46,7 +45,7 @@ abstract class MaxMinBy extends DeclarativeAggregate {
   override def dataType: DataType = valueExpr.dataType
 
   override def checkInputDataTypes(): TypeCheckResult =
-    TypeUtils.checkForOrderingExpr(orderingExpr.dataType, s"function $funcName")
+    TypeUtils.checkForOrderingExpr(orderingExpr.dataType, s"function $prettyName")
 
   // The attributes used to keep extremum (max or min) and associated aggregated values.
   private lazy val extremumOrdering =
@@ -101,7 +100,8 @@ abstract class MaxMinBy extends DeclarativeAggregate {
   group = "agg_funcs",
   since = "3.0.0")
 case class MaxBy(valueExpr: Expression, orderingExpr: Expression) extends MaxMinBy {
-  override protected def funcName: String = "max_by"
+
+  override def prettyName: String = "max_by"
 
   override protected def predicate(oldExpr: Expression, newExpr: Expression): Expression =
     oldExpr > newExpr
@@ -120,7 +120,8 @@ case class MaxBy(valueExpr: Expression, orderingExpr: Expression) extends MaxMin
   group = "agg_funcs",
   since = "3.0.0")
 case class MinBy(valueExpr: Expression, orderingExpr: Expression) extends MaxMinBy {
-  override protected def funcName: String = "min_by"
+
+  override def prettyName: String = "min_by"
 
   override protected def predicate(oldExpr: Expression, newExpr: Expression): Expression =
     oldExpr < newExpr

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

@@ -86,7 +86,12 @@ case class UnaryMinus(child: Expression) extends UnaryExpression
     case _ => numeric.negate(input)
   }
 
-  override def sql: String = s"(- ${child.sql})"
+  override def sql: String = {
+    getTagValue(FunctionRegistry.FUNC_ALIAS).getOrElse("-") match {
+      case "-" => s"(- ${child.sql})"
+      case funcName => s"$funcName(${child.sql})"
+    }
+  }
 }
 
 @ExpressionDescription(

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

@@ -172,6 +172,8 @@ case class BitwiseCount(child: Expression) extends UnaryExpression with ExpectsI
 
   override def toString: String = s"bit_count($child)"
 
+  override def prettyName: String = "bit_count"
+
   override def doGenCode(ctx: CodegenContext, ev: ExprCode): ExprCode = child.dataType match {
     case BooleanType => defineCodeGen(ctx, ev, c => s"if ($c) 1 else 0")
     case _ => defineCodeGen(ctx, ev, c => s"java.lang.Long.bitCount($c)")
@@ -184,6 +186,4 @@ case class BitwiseCount(child: Expression) extends UnaryExpression with ExpectsI
     case IntegerType => java.lang.Long.bitCount(input.asInstanceOf[Int])
     case LongType => java.lang.Long.bitCount(input.asInstanceOf[Long])
   }
-
-  override def sql: String = s"bit_count(${child.sql})"
 }

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

@@ -1,4 +1,4 @@
-<!-- Automatically generated byExpressionsSchemaSuite -->
+<!-- Automatically generated by ExpressionsSchemaSuite -->
 ## Summary
   - Number of queries: 328
   - Number of expressions that missing example: 34
@@ -273,7 +273,7 @@
 | org.apache.spark.sql.catalyst.expressions.TruncTimestamp | date_trunc | SELECT date_trunc('YEAR', '2015-03-05T09:32:05.359') | struct<date_trunc(YEAR, CAST(2015-03-05T09:32:05.359 AS TIMESTAMP)):timestamp> |
 | org.apache.spark.sql.catalyst.expressions.TypeOf | typeof | SELECT typeof(1) | struct<typeof(1):string> |
 | org.apache.spark.sql.catalyst.expressions.UnBase64 | unbase64 | SELECT unbase64('U3BhcmsgU1FM') | struct<unbase64(U3BhcmsgU1FM):binary> |
-| org.apache.spark.sql.catalyst.expressions.UnaryMinus | negative | SELECT negative(1) | struct<(- 1):int> |
+| org.apache.spark.sql.catalyst.expressions.UnaryMinus | negative | SELECT negative(1) | struct<negative(1):int> |
 | org.apache.spark.sql.catalyst.expressions.UnaryPositive | positive | N/A | N/A |
 | org.apache.spark.sql.catalyst.expressions.Unhex | unhex | SELECT decode(unhex('537061726B2053514C'), 'UTF-8') | struct<decode(unhex(537061726B2053514C), UTF-8):string> |
 | org.apache.spark.sql.catalyst.expressions.UnixTimestamp | unix_timestamp | SELECT unix_timestamp() | struct<unix_timestamp(current_timestamp(), yyyy-MM-dd HH:mm:ss):bigint> |
@@ -312,9 +312,9 @@
 | org.apache.spark.sql.catalyst.expressions.aggregate.Last | last_value | SELECT last_value(col) FROM VALUES (10), (5), (20) AS tab(col) | struct<last_value(col, false):int> |
 | org.apache.spark.sql.catalyst.expressions.aggregate.Last | last | SELECT last(col) FROM VALUES (10), (5), (20) AS tab(col) | struct<last(col, false):int> |
 | org.apache.spark.sql.catalyst.expressions.aggregate.Max | max | SELECT max(col) FROM VALUES (10), (50), (20) AS tab(col) | struct<max(col):int> |
-| org.apache.spark.sql.catalyst.expressions.aggregate.MaxBy | max_by | SELECT max_by(x, y) FROM VALUES (('a', 10)), (('b', 50)), (('c', 20)) AS tab(x, y) | struct<maxby(x, y):string> |
+| org.apache.spark.sql.catalyst.expressions.aggregate.MaxBy | max_by | SELECT max_by(x, y) FROM VALUES (('a', 10)), (('b', 50)), (('c', 20)) AS tab(x, y) | struct<max_by(x, y):string> |
 | org.apache.spark.sql.catalyst.expressions.aggregate.Min | min | SELECT min(col) FROM VALUES (10), (-1), (20) AS tab(col) | struct<min(col):int> |
-| org.apache.spark.sql.catalyst.expressions.aggregate.MinBy | min_by | SELECT min_by(x, y) FROM VALUES (('a', 10)), (('b', 50)), (('c', 20)) AS tab(x, y) | struct<minby(x, y):string> |
+| org.apache.spark.sql.catalyst.expressions.aggregate.MinBy | min_by | SELECT min_by(x, y) FROM VALUES (('a', 10)), (('b', 50)), (('c', 20)) AS tab(x, y) | struct<min_by(x, y):string> |
 | org.apache.spark.sql.catalyst.expressions.aggregate.Percentile | percentile | SELECT percentile(col, 0.3) FROM VALUES (0), (10) AS tab(col) | struct<percentile(col, CAST(0.3 AS DOUBLE), 1):double> |
 | org.apache.spark.sql.catalyst.expressions.aggregate.Skewness | skewness | SELECT skewness(col) FROM VALUES (-10), (-20), (100), (1000) AS tab(col) | struct<skewness(CAST(col AS DOUBLE)):double> |
 | org.apache.spark.sql.catalyst.expressions.aggregate.StddevPop | stddev_pop | SELECT stddev_pop(col) FROM VALUES (1), (2), (3) AS tab(col) | struct<stddev_pop(CAST(col AS DOUBLE)):double> |

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

@@ -437,7 +437,7 @@ struct<abs(-3.13):decimal(3,2),abs(CAST(-2.19 AS DOUBLE)):double>
 -- !query
 select positive('-1.11'), positive(-1.11), negative('-1.11'), negative(-1.11)
 -- !query schema
-struct<(+ CAST(-1.11 AS DOUBLE)):double,(+ -1.11):decimal(3,2),(- CAST(-1.11 AS DOUBLE)):double,(- -1.11):decimal(3,2)>
+struct<(+ CAST(-1.11 AS DOUBLE)):double,(+ -1.11):decimal(3,2),negative(CAST(-1.11 AS DOUBLE)):double,negative(-1.11):decimal(3,2)>
 -- !query output
 -1.11	-1.11	1.11	1.11
 

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

@@ -142,7 +142,7 @@ class ExpressionsSchemaSuite extends QueryTest with SharedSparkSession {
     }
 
     val header = Seq(
-      s"<!-- Automatically generated by${getClass.getSimpleName} -->",
+      s"<!-- Automatically generated by ${getClass.getSimpleName} -->",
       "## Summary",
       s"  - Number of queries: ${outputs.size}",
       s"  - Number of expressions that missing example: ${missingExamples.size}",