Where is RDD or Spark SQL dataframe stored or persisted in client deploy mode on a Spark 2.1 Standalone cluster?
If i understand correctly, then what you will get on the client side is an int. At least should be, if setup correctly. So the answer is no, the DF is not going to hit your local RAM.
You are interacting with the cluster via SparkSession (SparkContext for earlier versions). Even though you are developing -i.e. writing code- on the client machine, the actual computation of spark operations -i.e. running pyspark code-  will not be performed on your local machine.
I am deploying a Jupyter notebook(using python 2.7 kernel) on client side which accesses data on a remote and does processing in a remote Spark standalone cluster (using pyspark library). I am deploying spark cluster in Client mode. The client machine does not have any Spark worker nodes.
The client does not have enough memory(RAM). I wanted to know that if I perform a Spark action operation on dataframe like df.count()on client machine, will the dataframe be stored in Client's RAM or will it stored on Spark worker's memory?