I have Apache Spark set up in Docker containers running on my Windows host machine using WSL (Windows Subsystem for Linux) environment. I would like to connect PyCharm, which is running directly on the Windows host, to these Spark containers for developing and running Spark applications.

Here are the details of my setup:

1. Docker containers running Apache Spark on the Windows host machine using WSL for Linux environment.
2. PyCharm IDE installed and running on the Windows host machine.
3. Docker Desktop with WSL integration enabled for managing containers.
   Spark Standalone cluster

How can I correctly configure PyCharm to connect to Apache Spark Docker containers running on a Windows host machine via WSL? Specifically, what steps are necessary to set up the remote interpreter and ensure that PyCharm can execute Spark applications on these containers and create delta-tables?

from pyspark.sql import SparkSession
from delta.tables import DeltaTable

spark = SparkSession.builder 
.appName("Create Delta Table Example") 
.config("spark.sql.extensions", "io.delta.sql.DeltaSparkSessionExtension") 
.config("spark.sql.catalog.spark_catalog", "org.apache.spark.sql.delta.catalog.DeltaCatalog") 
.config("spark.jars.packages", "io.delta:delta-core_2.12:1.0.0") \  # Adjust Delta version as needed
.getOrCreate()

data = [(1, "Alice"), (2, "Bob"), (3, "Charlie")]
df = spark.createDataFrame(data, ["id", "name"])
delta_table_path = "/path/to/your/delta/table"
df.write.format("delta").mode("overwrite").save(delta_table_path)
delta_table = DeltaTable.forPath(spark, delta_table_path)
delta_table.vacuum()
spark.stop()