[SPARK-29627][PYTHON][SQL] Allow array_contains to take column instances

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

This PR proposes to allow `array_contains` to take column instances.

### Why are the changes needed?

For consistent support in Scala and Python APIs. Scala allows column instances at `array_contains`

Scala:

```scala
import org.apache.spark.sql.functions._
val df = Seq(Array("a", "b", "c"), Array.empty[String]).toDF("data")
df.select(array_contains($"data", lit("a"))).show()
```

Python:

```python
from pyspark.sql.functions import array_contains, lit
df = spark.createDataFrame([(["a", "b", "c"],), ([],)], ['data'])
df.select(array_contains(df.data, lit("a"))).show()
```

However, PySpark sides does not allow.

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

Yes.

```python
from pyspark.sql.functions import array_contains, lit
df = spark.createDataFrame([(["a", "b", "c"],), ([],)], ['data'])
df.select(array_contains(df.data, lit("a"))).show()
```

**Before:**

```
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/.../spark/python/pyspark/sql/functions.py", line 1950, in array_contains
    return Column(sc._jvm.functions.array_contains(_to_java_column(col), value))
  File "/.../spark/python/lib/py4j-0.10.8.1-src.zip/py4j/java_gateway.py", line 1277, in __call__
  File "/.../spark/python/lib/py4j-0.10.8.1-src.zip/py4j/java_gateway.py", line 1241, in _build_args
  File "/.../spark/python/lib/py4j-0.10.8.1-src.zip/py4j/java_gateway.py", line 1228, in _get_args
  File "/.../spark/python/lib/py4j-0.10.8.1-src.zip/py4j/java_collections.py", line 500, in convert
  File "/.../spark/python/pyspark/sql/column.py", line 344, in __iter__
    raise TypeError("Column is not iterable")
TypeError: Column is not iterable
```

**After:**

```
+-----------------------+
|array_contains(data, a)|
+-----------------------+
|                   true|
|                  false|
+-----------------------+
```

### How was this patch tested?

Manually tested and added a doctest.

Closes #26288 from HyukjinKwon/SPARK-29627.

Authored-by: HyukjinKwon <gurwls223@apache.org>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>

python/pyspark/sql/functions.py

@@ -1940,13 +1940,16 @@ def array_contains(col, value):
     given value, and false otherwise.
 
     :param col: name of column containing array
-    :param value: value to check for in array
+    :param value: value or column to check for in array
 
     >>> df = spark.createDataFrame([(["a", "b", "c"],), ([],)], ['data'])
     >>> df.select(array_contains(df.data, "a")).collect()
     [Row(array_contains(data, a)=True), Row(array_contains(data, a)=False)]
+    >>> df.select(array_contains(df.data, lit("a"))).collect()
+    [Row(array_contains(data, a)=True), Row(array_contains(data, a)=False)]
     """
     sc = SparkContext._active_spark_context
+    value = value._jc if isinstance(value, Column) else value
     return Column(sc._jvm.functions.array_contains(_to_java_column(col), value))