.sql() does not recognize watermark defined upstream

I have a data pipeline set up in such a way that it reads data from a Kafka source, does some transformation on the data using pyspark, then writes the output into a sink (Kafka, Redis, etc).

My entire pipeline in written in SQL, so I wish to use the .sql() method to execute SQL on my streaming source directly.

However, I'm running into the issue where my watermark is not being recognized by the downstream query via the .sql() method.

```
Python 3.11.8 | packaged by conda-forge | (main, Feb 16 2024, 20:49:36) [Clang 16.0.6 ] on darwin
Type "help", "copyright", "credits" or "license" for more information.
>>> import pyspark
>>> print(pyspark._version_)
3.5.1
>>> from pyspark.sql import SparkSession
>>>
>>> session = SparkSession.builder \
...     .config("spark.jars.packages", "org.apache.spark:spark-sql-kafka-0-10_2.12:3.5.1")\
...     .getOrCreate()
>>> from pyspark.sql.functions import col, from_json
>>> from pyspark.sql.types import StructField, StructType, TimestampType, LongType, DoubleType, IntegerType
>>> schema = StructType(
...     [
...         StructField('createTime', TimestampType(), True),
...         StructField('orderId', LongType(), True),
...         StructField('payAmount', DoubleType(), True),
...         StructField('payPlatform', IntegerType(), True),
...         StructField('provinceId', IntegerType(), True),
...     ])
>>>
>>> streaming_df = session.readStream\
...     .format("kafka")\
...     .option("kafka.bootstrap.servers", "localhost:9092")\
...     .option("subscribe", "payment_msg")\
...     .option("startingOffsets","earliest")\
...     .load()\
...     .select(from_json(col("value").cast("string"), schema).alias("parsed_value"))\
...     .select("parsed_value.*")\
...     .withWatermark("createTime", "10 seconds")
>>>
>>> streaming_df.createOrReplaceTempView("streaming_df")
>>> session.sql("""
... SELECT
...     window.start, window.end, provinceId, sum(payAmount) as totalPayAmount
...     FROM streaming_df
...     GROUP BY provinceId, window('createTime', '1 hour', '30 minutes')
...     ORDER BY window.start
... """)\
...   .writeStream\
...   .format("kafka") \
...   .option("checkpointLocation", "checkpoint") \
...   .option("kafka.bootstrap.servers", "localhost:9092") \
...   .option("topic", "sink") \
...   .start()
```
 
This throws exception
```
pyspark.errors.exceptions.captured.AnalysisException: Append output mode not supported when there are streaming aggregations on streaming DataFrames/DataSets without watermark; line 6 pos 4;
```