InList Expr: expr and list values must can be converted to a same data type

[liukun4515]

Describe the bug
In current inList implemention, we don't consider the data type of the list value.

For example:

I create a table

❯ \d food
+---------------+--------------+------------+-------------+-----------------+-------------+
| table_catalog | table_schema | table_name | column_name | data_type       | is_nullable |
+---------------+--------------+------------+-------------+-----------------+-------------+
| datafusion    | public       | food       | a           | Decimal(10, 5)  | NO          |
| datafusion    | public       | food       | b           | Decimal(20, 15) | NO          |
| datafusion    | public       | food       | c           | Boolean         | NO          |
+---------------+--------------+------------+-------------+-----------------+-------------+

with data

❯  select * from food;
+---------+-------------------+-------+
| a       | b                 | c     |
+---------+-------------------+-------+
| 0.00001 | 0.000000000001000 | true  |
| 0.00002 | 0.000000000002000 | false |
| 0.00002 | 0.000000000002000 | false |
| 0.00003 | 0.000000000003000 | true  |
| 0.00003 | 0.000000000003000 | true  |
| 0.00003 | 0.000000000003000 | true  |
| 0.00004 | 0.000000000004000 | false |
| 0.00004 | 0.000000000004000 | false |
| 0.00004 | 0.000000000004000 | false |
| 0.00004 | 0.000000000004000 | false |
| 0.00005 | 0.000000000005000 | true  |
| 0.00005 | 0.000000000005000 | true  |
| 0.00005 | 0.000000000005000 | true  |
| 0.00005 | 0.000000000005000 | true  |
| 0.00005 | 0.000000000005000 | true  |
+---------+-------------------+-------+

using the in filter to select data

❯  select * from food where c in (true,123);
+---------+-------------------+------+
| a       | b                 | c    |
+---------+-------------------+------+
| 0.00001 | 0.000000000001000 | true |
| 0.00003 | 0.000000000003000 | true |
| 0.00003 | 0.000000000003000 | true |
| 0.00003 | 0.000000000003000 | true |
| 0.00005 | 0.000000000005000 | true |
| 0.00005 | 0.000000000005000 | true |
| 0.00005 | 0.000000000005000 | true |
| 0.00005 | 0.000000000005000 | true |
| 0.00005 | 0.000000000005000 | true |
+---------+-------------------+------+

The column of c is bool data type, we can apply the compare operations to diff data type.

The behavior of other database, such as spark

spark-sql> desc t3;
c1                      int

we will get the error message

spark-sql> select * from t3 where c1 in(1,23,false);
Error in query: cannot resolve '(spark_catalog.default.t3.c1 IN (1, 23, false))' due to data type mismatch: Arguments must be same type but were: int != boolean; line 1 pos 26;
'Project [*]
+- 'Filter c1#358 IN (1,23,false)
   +- SubqueryAlias spark_catalog.default.t3
      +- HiveTableRelation [`default`.`t3`, org.apache.hadoop.hive.serde2.lazy.LazySimpleSerDe, Data Cols: [c1#358], Partition Cols: []]

To Reproduce
Steps to reproduce the behavior:

Expected behavior
A clear and concise description of what you expected to happen.

Additional context
Add any other context about the problem here.

[liukun4515]

In the datafusion, we can convert NULL value of the NULL type to any other NULL value of data type.
For example: Convert NULL(NULL) to INT32(NULL) or FLOAT(NULL);

❯ EXPLAIN select cast(NULL as FLOAT);
+---------------+------------------------------------------------------+
| plan_type     | plan                                                 |
+---------------+------------------------------------------------------+
| logical_plan  | Projection: Float32(NULL) AS CAST(NULL AS Float32)   |
|               |   EmptyRelation                                      |
| physical_plan | ProjectionExec: expr=[NULL as CAST(NULL AS Float32)] |
|               |   EmptyExec: produce_one_row=true                    |
|               |                                                      |
+---------------+------------------------------------------------------+
2 rows in set. Query took 0.002 seconds.
❯ EXPLAIN select cast(NULL as INT);
+---------------+----------------------------------------------------+
| plan_type     | plan                                               |
+---------------+----------------------------------------------------+
| logical_plan  | Projection: Int32(NULL) AS CAST(NULL AS Int32)     |
|               |   EmptyRelation                                    |
| physical_plan | ProjectionExec: expr=[NULL as CAST(NULL AS Int32)] |
|               |   EmptyExec: produce_one_row=true                  |
|               |                                                    |
+---------------+----------------------------------------------------+

[liukun4515]

If we want to use the NULL in the list expr. The data type of NULL is NULL

[liukun4515]

In the spark, we can't compare decimal with boolean, but can compare decimal with Null.

spark-sql> DESC T1;
c1                      decimal(10,3)

spark-sql>  select * from t1 where c1 in(NULL);
Time taken: 0.082 seconds

spark-sql>  select * from t1 where c1 in(CAST(NULL AS BOOLEAN));
Error in query: cannot resolve '(spark_catalog.default.t1.c1 IN (CAST(NULL AS BOOLEAN)))' due to data type mismatch: Arguments must be same type but were: decimal(10,3) != boolean; line 1 pos 27;
'Project [*]
+- 'Filter c1#656 IN (cast(null as boolean))
   +- SubqueryAlias spark_catalog.default.t1
      +- HiveTableRelation [`default`.`t1`, org.apache.hadoop.hive.serde2.lazy.LazySimpleSerDe, Data Cols: [c1#656], Partition Cols: []]