This configuration allows your compute cluster to scale with your data.
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).
0.[Deploy Spark on Mesos](http://spark.apache.org/docs/latest/running-on-mesos.html).
1. 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).)
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. Follow the language specific instructions below.
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).)
3. Follow the language specific instructions below.
This configuration allows your compute cluster to scale with your data.
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).
0.[Deploy Spark on Mesos](http://spark.apache.org/docs/latest/running-on-mesos.html).
1. 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.
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).)
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. Open a Python 2 or 3 notebook.
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).)
4. Create a `SparkConf` instance in a new notebook pointing to your Mesos master node (or Zookeeper instance) and Spark binary package location.
4. Open a Python 2 or 3 notebook.
5. Create a `SparkContext` using this configuration.
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.
For example, the first few cells in a Python 3 notebook might read:
For example, the first few cells in a Python 3 notebook might read:
