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assign9.md

@@ -6,7 +6,7 @@ tasks. For this assignment, we will use relatively small datasets and we won't
 run anything in distributed mode; however Spark can be easily used to run the
 same programs on much larger datasets.
 
-### Setup
+## Setup
 
 Download files for Assignment 9 <a href="https://ceres.cs.umd.edu/424/assign/assignment9Dist.tgz?1">here</a>.
 
@@ -27,9 +27,6 @@ tasks are written as chains of these operations.
 Spark can be used with the Hadoop ecosystem, including the HDFS file system and
 the YARN resource manager.
 
-Note that bash is the default shell everywhere, but the `.cshrc` is set up
-correctly if you feel like dropping into `tcsh`.
-
 
 ### Vagrant
 This is the **recommended** way to do this project. 
@@ -56,7 +53,8 @@ approach has been checked out (soon).
 ### Docker
 Probably before Thanksgiving.
 
-### Spark and Python
+
+## Spark and Python
 
 Spark primarily supports three languages: Scala (Spark is written in Scala),
 Java, and Python. We will use Python here -- you can follow the instructions at
@@ -118,7 +116,7 @@ The `lambda` representation is more compact and preferable, especially for small
 functions, but for large functions, it is better to separate out the
 definitions.
 
-### Running it as an Application
+### Running as an Application
 
 Instead of using a shell, you can also write your code as a python file, and
 *submit* that to the spark cluster. The `assignment9` directory contains a