[SPARK-23927][SQL] Add "sequence" expression

## What changes were proposed in this pull request?
The PR adds the SQL function ```sequence```.
https://issues.apache.org/jira/browse/SPARK-23927

The behavior of the function is based on Presto's one.
Ref: https://prestodb.io/docs/current/functions/array.html

- ```sequence(start, stop) → array<bigint>```
Generate a sequence of integers from ```start``` to ```stop```, incrementing by ```1``` if ```start``` is less than or equal to ```stop```, otherwise ```-1```.
- ```sequence(start, stop, step) → array<bigint>```
Generate a sequence of integers from ```start``` to ```stop```, incrementing by ```step```.
- ```sequence(start_date, stop_date) → array<date>```
Generate a sequence of dates from ```start_date``` to ```stop_date```, incrementing by ```interval 1 day``` if ```start_date``` is less than or equal to ```stop_date```, otherwise ```- interval 1 day```.
- ```sequence(start_date, stop_date, step_interval) → array<date>```
Generate a sequence of dates from ```start_date``` to ```stop_date```, incrementing by ```step_interval```. The type of ```step_interval``` is ```CalendarInterval```.
- ```sequence(start_timestemp, stop_timestemp) → array<timestamp>```
Generate a sequence of timestamps from ```start_timestamps``` to ```stop_timestamps```, incrementing by ```interval 1 day``` if ```start_date``` is less than or equal to ```stop_date```, otherwise ```- interval 1 day```.
- ```sequence(start_timestamp, stop_timestamp, step_interval) → array<timestamp>```
Generate a sequence of timestamps from ```start_timestamps``` to ```stop_timestamps```, incrementing by ```step_interval```. The type of ```step_interval``` is ```CalendarInterval```.

## How was this patch tested?

Added unit tests.

Author: Vayda, Oleksandr: IT (PRG) <[email protected]>

Closes #21155 from wajda/feature/array-api-sequence.

Author: wajda

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

@@ -432,6 +432,7 @@ object FunctionRegistry {
     expression[Reverse]("reverse"),
     expression[Concat]("concat"),
     expression[Flatten]("flatten"),
+    expression[Sequence]("sequence"),
     expression[ArrayRepeat]("array_repeat"),
     expression[ArrayRemove]("array_remove"),
     expression[ArrayDistinct]("array_distinct"),

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

@@ -544,6 +544,13 @@ object TypeCoercion {
           case None => aj
         }
 
+      case s @ Sequence(_, _, _, timeZoneId) if !haveSameType(s.coercibleChildren) =>
+        val types = s.coercibleChildren.map(_.dataType)
+        findWiderCommonType(types) match {
+          case Some(widerDataType) => s.castChildrenTo(widerDataType)
+          case None => s
+        }
+
       case m @ CreateMap(children) if m.keys.length == m.values.length &&
         (!haveSameType(m.keys) || !haveSameType(m.values)) =>
         val newKeys = if (haveSameType(m.keys)) {