Delete RLTimelineOperator and RLExtractStateOperator

Summary:
no execution: https://fburl.com/daiquery/gk2sargj
no references: https://fburl.com/code/otg0rfbm

Reviewed By: koronthaly

Differential Revision: D52003864

fbshipit-source-id: e29f6ee2d9f10c1e7e0bd15d2d2559e8097dc399

Author: Michael Brandow

docs/usage.rst

@@ -149,7 +149,7 @@ Once you have data on this format, you can move on to Step 2.
 Step 2 - Convert the data to the ``Timeline`` format
 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
 
-Models are trained on consecutive pairs of state/action tuples. To assist in creating this table, we have an ``RLTimelineOperator`` spark operator. Let's build and run the timeline operator on the data:
+Models are trained on consecutive pairs of state/action tuples. To assist in creating this table, we have a deleted spark operator. Let's build and run the timeline operator on the data:
 
 First, we need to build the Spark library that will execute the timeline.  Apache Spark is a platform for doing massively-parallel processing.  Although we are running this on a single file, Spark is designed to work on thousands of files distribued across many machines.  Explaining HDFS, Hive, and Spark are beyond the scope of this tutorial, but for large datasets it's important to understand these concepts and that it's possible to run ReAgent in a distributed environment by simply changing the location of the input from a file to an HDFS folder.