[SPARK-31808][SQL] Makes struct function's output name and class name pretty

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

@@ -19,7 +19,7 @@ package org.apache.spark.sql.catalyst.expressions
 
 import org.apache.spark.sql.catalyst.InternalRow
 import org.apache.spark.sql.catalyst.analysis.{TypeCheckResult, TypeCoercion}
-import org.apache.spark.sql.catalyst.analysis.FunctionRegistry.FunctionBuilder
+import org.apache.spark.sql.catalyst.analysis.FunctionRegistry.{FUNC_ALIAS, FunctionBuilder}
 import org.apache.spark.sql.catalyst.expressions.codegen._
 import org.apache.spark.sql.catalyst.expressions.codegen.Block._
 import org.apache.spark.sql.catalyst.util._
@@ -311,7 +311,12 @@ case object NamePlaceholder extends LeafExpression with Unevaluable {
 /**
  * Returns a Row containing the evaluation of all children expressions.
  */
-object CreateStruct extends FunctionBuilder {
+object CreateStruct {
+  /**
+   * Returns a named struct with generating names or using the names when available.
+   * It should not be used for `struct` expressions or functions explicitly called
+   * by users.
+   */
   def apply(children: Seq[Expression]): CreateNamedStruct = {
     CreateNamedStruct(children.zipWithIndex.flatMap {
       case (e: NamedExpression, _) if e.resolved => Seq(Literal(e.name), e)
@@ -320,12 +325,23 @@ object CreateStruct extends FunctionBuilder {
     })
   }
 
+  /**
+   * Returns a named struct with a pretty SQL name. It will show the pretty SQL string
+   * in its output column name as if `struct(...)` was called. Should be
+   * used for `struct` expressions or functions explicitly called by users.
+   */
+  def create(children: Seq[Expression]): CreateNamedStruct = {
+    val expr = CreateStruct(children)
+    expr.setTagValue(FUNC_ALIAS, "struct")
+    expr
+  }
+
   /**
    * Entry to use in the function registry.
    */
   val registryEntry: (String, (ExpressionInfo, FunctionBuilder)) = {
     val info: ExpressionInfo = new ExpressionInfo(
-      "org.apache.spark.sql.catalyst.expressions.NamedStruct",
+      classOf[CreateNamedStruct].getCanonicalName,
       null,
       "struct",
       "_FUNC_(col1, col2, col3, ...) - Creates a struct with the given field values.",
@@ -335,7 +351,7 @@ object CreateStruct extends FunctionBuilder {
       "",
       "",
       "")
-    ("struct", (info, this))
+    ("struct", (info, this.create))
   }
 }
 
@@ -433,7 +449,12 @@ case class CreateNamedStruct(children: Seq[Expression]) extends Expression {
        """.stripMargin, isNull = FalseLiteral)
   }
 
-  override def prettyName: String = "named_struct"
+  override def prettyName: String = getTagValue(FUNC_ALIAS).getOrElse("named_struct")
+
+  override def sql: String = getTagValue(FUNC_ALIAS).map { alias =>
+    val childrenSQL = children.indices.filter(_ % 2 == 1).map(children(_).sql).mkString(", ")
+    s"$alias($childrenSQL)"
+  }.getOrElse(super.sql)
 }
 
 /**

sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/parser/AstBuilder.scala

@@ -1534,7 +1534,7 @@ class AstBuilder(conf: SQLConf) extends SqlBaseBaseVisitor[AnyRef] with Logging
    * Create a [[CreateStruct]] expression.
    */
   override def visitStruct(ctx: StructContext): Expression = withOrigin(ctx) {
-    CreateStruct(ctx.argument.asScala.map(expression))
+    CreateStruct.create(ctx.argument.asScala.map(expression))
   }
 
   /**

sql/core/src/main/scala/org/apache/spark/sql/functions.scala

@@ -1306,7 +1306,7 @@ object functions {
    * @since 1.4.0
    */
   @scala.annotation.varargs
-  def struct(cols: Column*): Column = withExpr { CreateStruct(cols.map(_.expr)) }
+  def struct(cols: Column*): Column = withExpr { CreateStruct.create(cols.map(_.expr)) }
 
   /**
    * Creates a new struct column that composes multiple input columns.

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

@@ -2,7 +2,7 @@
 ## Summary
   - Number of queries: 336
   - Number of expressions that missing example: 34
-  - Expressions missing examples: and,string,tinyint,double,smallint,date,decimal,boolean,float,binary,bigint,int,timestamp,cume_dist,dense_rank,input_file_block_length,input_file_block_start,input_file_name,lag,lead,monotonically_increasing_id,ntile,struct,!,not,or,percent_rank,rank,row_number,spark_partition_id,version,window,positive,count_min_sketch
+  - Expressions missing examples: and,string,tinyint,double,smallint,date,decimal,boolean,float,binary,bigint,int,timestamp,struct,cume_dist,dense_rank,input_file_block_length,input_file_block_start,input_file_name,lag,lead,monotonically_increasing_id,ntile,!,not,or,percent_rank,rank,row_number,spark_partition_id,version,window,positive,count_min_sketch
 ## Schema of Built-in Functions
 | Class name | Function name or alias | Query example | Output schema |
 | ---------- | ---------------------- | ------------- | ------------- |
@@ -79,6 +79,7 @@
 | org.apache.spark.sql.catalyst.expressions.CreateArray | array | SELECT array(1, 2, 3) | struct<array(1, 2, 3):array<int>> |
 | org.apache.spark.sql.catalyst.expressions.CreateMap | map | SELECT map(1.0, '2', 3.0, '4') | struct<map(1.0, 2, 3.0, 4):map<decimal(2,1),string>> |
 | org.apache.spark.sql.catalyst.expressions.CreateNamedStruct | named_struct | SELECT named_struct("a", 1, "b", 2, "c", 3) | struct<named_struct(a, 1, b, 2, c, 3):struct<a:int,b:int,c:int>> |
+| org.apache.spark.sql.catalyst.expressions.CreateNamedStruct | struct | N/A | N/A |
 | 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.Cube | cube | SELECT name, age, count(*) FROM VALUES (2, 'Alice'), (5, 'Bob') people(age, name) GROUP BY cube(name, age) | struct<name:string,age:int,count(1):bigint> |
 | org.apache.spark.sql.catalyst.expressions.CumeDist | cume_dist | N/A | N/A |
@@ -170,7 +171,7 @@
 | org.apache.spark.sql.catalyst.expressions.MapEntries | map_entries | SELECT map_entries(map(1, 'a', 2, 'b')) | struct<map_entries(map(1, a, 2, b)):array<struct<key:int,value:string>>> |
 | org.apache.spark.sql.catalyst.expressions.MapFilter | map_filter | SELECT map_filter(map(1, 0, 2, 2, 3, -1), (k, v) -> k > v) | struct<map_filter(map(1, 0, 2, 2, 3, -1), lambdafunction((namedlambdavariable() > namedlambdavariable()), namedlambdavariable(), namedlambdavariable())):map<int,int>> |
 | org.apache.spark.sql.catalyst.expressions.MapFromArrays | map_from_arrays | SELECT map_from_arrays(array(1.0, 3.0), array('2', '4')) | struct<map_from_arrays(array(1.0, 3.0), array(2, 4)):map<decimal(2,1),string>> |
-| org.apache.spark.sql.catalyst.expressions.MapFromEntries | map_from_entries | SELECT map_from_entries(array(struct(1, 'a'), struct(2, 'b'))) | struct<map_from_entries(array(named_struct(col1, 1, col2, a), named_struct(col1, 2, col2, b))):map<int,string>> |
+| org.apache.spark.sql.catalyst.expressions.MapFromEntries | map_from_entries | SELECT map_from_entries(array(struct(1, 'a'), struct(2, 'b'))) | struct<map_from_entries(array(struct(1, a), struct(2, b))):map<int,string>> |
 | org.apache.spark.sql.catalyst.expressions.MapKeys | map_keys | SELECT map_keys(map(1, 'a', 2, 'b')) | struct<map_keys(map(1, a, 2, b)):array<int>> |
 | org.apache.spark.sql.catalyst.expressions.MapValues | map_values | SELECT map_values(map(1, 'a', 2, 'b')) | struct<map_values(map(1, a, 2, b)):array<string>> |
 | org.apache.spark.sql.catalyst.expressions.MapZipWith | map_zip_with | SELECT map_zip_with(map(1, 'a', 2, 'b'), map(1, 'x', 2, 'y'), (k, v1, v2) -> concat(v1, v2)) | struct<map_zip_with(map(1, a, 2, b), map(1, x, 2, y), lambdafunction(concat(namedlambdavariable(), namedlambdavariable()), namedlambdavariable(), namedlambdavariable(), namedlambdavariable())):map<int,string>> |
@@ -185,7 +186,6 @@
 | org.apache.spark.sql.catalyst.expressions.Murmur3Hash | hash | SELECT hash('Spark', array(123), 2) | struct<hash(Spark, array(123), 2):int> |
 | org.apache.spark.sql.catalyst.expressions.NTile | ntile | N/A | N/A |
 | org.apache.spark.sql.catalyst.expressions.NaNvl | nanvl | SELECT nanvl(cast('NaN' as double), 123) | struct<nanvl(CAST(NaN AS DOUBLE), CAST(123 AS DOUBLE)):double> |
-| org.apache.spark.sql.catalyst.expressions.NamedStruct | struct | N/A | N/A |
 | org.apache.spark.sql.catalyst.expressions.NextDay | next_day | SELECT next_day('2015-01-14', 'TU') | struct<next_day(CAST(2015-01-14 AS DATE), TU):date> |
 | org.apache.spark.sql.catalyst.expressions.Not | ! | N/A | N/A |
 | org.apache.spark.sql.catalyst.expressions.Not | not | N/A | N/A |

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

@@ -272,7 +272,7 @@ struct<foo:string,approx_count_distinct(a) FILTER (WHERE (b >= 0)):bigint>
 -- !query
 SELECT 'foo', MAX(STRUCT(a)) FILTER (WHERE b >= 1) FROM testData WHERE a = 0 GROUP BY 1
 -- !query schema
-struct<foo:string,max(named_struct(a, a)) FILTER (WHERE (b >= 1)):struct<a:int>>
+struct<foo:string,max(struct(a)) FILTER (WHERE (b >= 1)):struct<a:int>>
 -- !query output
 
 

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

@@ -87,7 +87,7 @@ struct<foo:string,approx_count_distinct(a):bigint>
 -- !query
 SELECT 'foo', MAX(STRUCT(a)) FROM testData WHERE a = 0 GROUP BY 1
 -- !query schema
-struct<foo:string,max(named_struct(a, a)):struct<a:int>>
+struct<foo:string,max(struct(a)):struct<a:int>>
 -- !query output
 
 

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

@@ -83,7 +83,7 @@ struct<ID:int,NST:string>
 -- !query
 SELECT ID, STRUCT(ST.C as STC, ST.D as STD).STD FROM tbl_x
 -- !query schema
-struct<ID:int,named_struct(STC, ST.C AS `C` AS `STC`, STD, ST.D AS `D` AS `STD`).STD:string>
+struct<ID:int,struct(ST.C AS `C` AS `STC`, ST.D AS `D` AS `STD`).STD:string>
 -- !query output
 1	delta
 2	eta

sql/core/src/test/resources/sql-tests/results/typeCoercion/native/mapZipWith.sql.out

@@ -85,7 +85,7 @@ FROM various_maps
 struct<>
 -- !query output
 org.apache.spark.sql.AnalysisException
-cannot resolve 'map_zip_with(various_maps.`decimal_map1`, various_maps.`decimal_map2`, lambdafunction(named_struct(NamePlaceholder(), k, NamePlaceholder(), v1, NamePlaceholder(), v2), k, v1, v2))' due to argument data type mismatch: The input to function map_zip_with should have been two maps with compatible key types, but the key types are [decimal(36,0), decimal(36,35)].; line 1 pos 7
+cannot resolve 'map_zip_with(various_maps.`decimal_map1`, various_maps.`decimal_map2`, lambdafunction(struct(k, v1, v2), k, v1, v2))' due to argument data type mismatch: The input to function map_zip_with should have been two maps with compatible key types, but the key types are [decimal(36,0), decimal(36,35)].; line 1 pos 7
 
 
 -- !query
@@ -113,7 +113,7 @@ FROM various_maps
 struct<>
 -- !query output
 org.apache.spark.sql.AnalysisException
-cannot resolve 'map_zip_with(various_maps.`decimal_map2`, various_maps.`int_map`, lambdafunction(named_struct(NamePlaceholder(), k, NamePlaceholder(), v1, NamePlaceholder(), v2), k, v1, v2))' due to argument data type mismatch: The input to function map_zip_with should have been two maps with compatible key types, but the key types are [decimal(36,35), int].; line 1 pos 7
+cannot resolve 'map_zip_with(various_maps.`decimal_map2`, various_maps.`int_map`, lambdafunction(struct(k, v1, v2), k, v1, v2))' due to argument data type mismatch: The input to function map_zip_with should have been two maps with compatible key types, but the key types are [decimal(36,35), int].; line 1 pos 7
 
 
 -- !query

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

@@ -87,7 +87,7 @@ struct<foo:string,CAST(udf(cast(approx_count_distinct(cast(udf(cast(a as string)
 -- !query
 SELECT 'foo', MAX(STRUCT(udf(a))) FROM testData WHERE a = 0 GROUP BY udf(1)
 -- !query schema
-struct<foo:string,max(named_struct(col1, CAST(udf(cast(a as string)) AS INT))):struct<col1:int>>
+struct<foo:string,max(struct(CAST(udf(cast(a as string)) AS INT))):struct<col1:int>>
 -- !query output