Doc --net=host requirements for su

(c) Copyright IBM Corp. 2015

all-spark-notebook/README.md

@@ -93,6 +93,7 @@ This configuration allows your compute cluster to scale with your data.
 0. [Deploy Spark on Mesos](http://spark.apache.org/docs/latest/running-on-mesos.html).
 1. Configure each slave with [the `--no-switch_user` flag](https://open.mesosphere.com/reference/mesos-slave/) or create the `jovyan` user on every slave node.
 2. Run the Docker container with `--net=host` in a location that is network addressable by all of your Spark workers. (This is a [Spark networking requirement](http://spark.apache.org/docs/latest/cluster-overview.html#components).)
+    * NOTE: When using `--net=host`, you must also use the flags `--pid=host -e TINI_SUBREAPER=true`. See https://github.com/jupyter/docker-stacks/issues/64 for details.
 3. Follow the language specific instructions below.
 
 ### In a Python Notebook

pyspark-notebook/README.md

@@ -55,6 +55,7 @@ This configuration allows your compute cluster to scale with your data.
 1. Configure each slave with [the `--no-switch_user` flag](https://open.mesosphere.com/reference/mesos-slave/) or create the `jovyan` user on every slave node.
 2. Ensure Python 2.x and/or 3.x and any Python libraries you wish to use in your Spark lambda functions are installed on your Spark workers.
 3. Run the Docker container with `--net=host` in a location that is network addressable by all of your Spark workers. (This is a [Spark networking requirement](http://spark.apache.org/docs/latest/cluster-overview.html#components).)
+    * NOTE: When using `--net=host`, you must also use the flags `--pid=host -e TINI_SUBREAPER=true`. See https://github.com/jupyter/docker-stacks/issues/64 for details.
 4. Open a Python 2 or 3 notebook.
 5. Create a `SparkConf` instance in a new notebook pointing to your Mesos master node (or Zookeeper instance) and Spark binary package location.
 6. Create a `SparkContext` using this configuration.