Add pyspark model base class

[schuderer]

using system from #7

supporting pyspark (possibly very little user-model-related stuff necessary, except maybe convenience base-class-to-use to deal with spark context.

[schuderer]

Actually, I found that it makes much more sense to just use the (currently experimental) Spark DataSource #145 --> It will create the connection and spark object/context for you based on the config. Furthermore, once you get your hands on a spark dataframe (which the Spark DataSource provides through get_spark_dataframe()), you usually don't need to handle the spark context explicitly any more anyway (unless you want to store spark DFs -- ideally, a data sink should be created for this. Let me know if you need this, and I'll take a look at it).

So, in essence, spark context handling is against the gist of what ML Launchpad tries to achieve -- getting the I/O as much as possible out of your hair. That's what the Spark DataSource should provide.

If you absolutely need a spark context (and are not querying a spark dataframe), you can configure a dummy spark datasource (e.g. with query 'select 1 as dummy'). That SQL query does not even get executed unless you call get_spark_dataframe() or get_dataframe(), but you have access to the connection through data_source.spark anyway.