[SPARK-29187][SQL] Return null from date_part() for the null field

### What changes were proposed in this pull request?

In the PR, I propose to change behavior of the `date_part()` function in handling `null` field, and make it the same as PostgreSQL has. If `field` parameter is `null`, the function should return `null` of the `double` type as PostgreSQL does:
```sql
# select date_part(null, date '2019-09-20');
 date_part
-----------

(1 row)

# select pg_typeof(date_part(null, date '2019-09-20'));
    pg_typeof
------------------
 double precision
(1 row)
```

### Why are the changes needed?
The `date_part()` function was added to maintain feature parity with PostgreSQL but current behavior of the function is different in handling null as `field`.

### Does this PR introduce any user-facing change?
Yes.

Before:
```sql
spark-sql> select date_part(null, date'2019-09-20');
Error in query: null; line 1 pos 7
```

After:
```sql
spark-sql> select date_part(null, date'2019-09-20');
NULL
```

### How was this patch tested?
Add new tests to `DateFunctionsSuite for 2 cases:
- `field` = `null`, `source` = a date literal
- `field` = `null`, `source` = a date column

Closes #25865 from MaxGekk/date_part-null.

Authored-by: Maxim Gekk <max.gekk@gmail.com>
Signed-off-by: Dongjoon Hyun <dhyun@apple.com>

Author: MaxGekk

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

@@ -2053,10 +2053,15 @@ case class DatePart(field: Expression, source: Expression, child: Expression)
       if (!field.foldable) {
         throw new AnalysisException("The field parameter needs to be a foldable string value.")
       }
-      val fieldStr = field.eval().asInstanceOf[UTF8String].toString
-      DatePart.parseExtractField(fieldStr, source, {
-        throw new AnalysisException(s"Literals of type '$fieldStr' are currently not supported.")
-      })
+      val fieldEval = field.eval()
+      if (fieldEval == null) {
+        Literal(null, DoubleType)
+      } else {
+        val fieldStr = fieldEval.asInstanceOf[UTF8String].toString
+        DatePart.parseExtractField(fieldStr, source, {
+          throw new AnalysisException(s"Literals of type '$fieldStr' are currently not supported.")
+        })
+      }
     })
   }
 

sql/core/src/test/resources/sql-tests/inputs/date_part.sql

@@ -66,3 +66,5 @@ select date_part('secs', c) from t;
 select date_part('not_supported', c) from t;
 
 select date_part(c, c) from t;
+
+select date_part(null, c) from t;

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

@@ -1,5 +1,5 @@
 -- Automatically generated by SQLQueryTestSuite
--- Number of queries: 51
+-- Number of queries: 52
 
 
 -- !query 0
@@ -410,3 +410,11 @@ struct<>
 -- !query 50 output
 org.apache.spark.sql.AnalysisException
 The field parameter needs to be a foldable string value.;; line 1 pos 7
+
+
+-- !query 51
+select date_part(null, c) from t
+-- !query 51 schema
+struct<date_part(NULL, t.`c`):double>
+-- !query 51 output
+NULL

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

@@ -27,6 +27,7 @@ import org.apache.spark.sql.catalyst.util.DateTimeUtils
 import org.apache.spark.sql.functions._
 import org.apache.spark.sql.internal.SQLConf
 import org.apache.spark.sql.test.SharedSparkSession
+import org.apache.spark.sql.types.{DoubleType, StructField, StructType}
 import org.apache.spark.unsafe.types.CalendarInterval
 
 class DateFunctionsSuite extends QueryTest with SharedSparkSession {
@@ -796,4 +797,13 @@ class DateFunctionsSuite extends QueryTest with SharedSparkSession {
         Seq(Row(Instant.parse(timestamp))))
     }
   }
+
+  test("handling null field by date_part") {
+    val input = Seq(Date.valueOf("2019-09-20")).toDF("d")
+    Seq("date_part(null, d)", "date_part(null, date'2019-09-20')").foreach { expr =>
+      val df = input.selectExpr(expr)
+      assert(df.schema.headOption.get.dataType == DoubleType)
+      checkAnswer(df, Row(null))
+    }
+  }
 }