Advanced Data Analysis Techniques with Apache Spark

Getting ready for the workshop (required before the day of workshop)

You will need to request access to the Adroit cluster, install Apache Spark and some packages on your laptop, and optionally complete a set of pre-exercises.

All the pre-exercises are supposed to be completed on your laptops. Some of the workshop exercises will be done on your laptops, and some will be done on the cluster.

Request an Adroit computing account

Please make sure you have and Adroit computing account or request it following the instructions on the page: https://www.princeton.edu/researchcomputing/computational-hardware/adroit/

Test connection to the cluster

If you have the account, login to Adroit with X11 forwarding enabled:

ssh -XC your_username@adroit3.princeton.edu

Install ssh client on your laptop if necessary (for instance, Putty on Windows. On Mac or Linux operating systems one can simply use terminal).

Install with Docker

Note: this is for the laptops portion of the exercise only. Spark is already installed on Adroit cluster

Docker is a containerisation engine that makes it much easier to run softwares. It essentially works as a lightweight VM manager, allowing you to spin instances up or down very easily. First step is to install Docker.

Once you have Docker, run the following to download all of the images required to spin up a Spark Notebook:

docker pull jupyter/all-spark-notebook

This will take a little while, but once it's complete you are basically ready to go. Clone the repo, and run a Docker container with the following commands:

git clone https://github.com/ASvyatkovskiy/BigDataCourse && cd BigDataCourse
docker run -it --rm -p 8888:8888 -v $(pwd)/:/home/jovyan/work jupyter/all-spark-notebook

Enter the URL that pops up in your terminal into a browser, and you should be good to go.

Install manually

Note: this is for the laptops portion of the exercise only. Spark is already installed on Adroit cluster

If Docker is not an option for you, you can always install manually from source or binaries.

Install Apache Spark on your laptop

Install Apache Spark 2.2.0 on your laptop. Here are some instructions on how to do that:

1. Go to the Spark download page: http://spark.apache.org/downloads.html select installation from source: http://apache.cs.utah.edu/spark/spark-2.2.0/spark-2.2.0-bin-hadoop2.7.tgz

Download, unpack, and build it with Maven:

#cd spark-2.2.0/
build/mvn -DskipTests clean package

You are going to need to install Maven build tool for that. Maven can be downloaded from the web: https://maven.apache.org/download.cgi unpack it, and add to the PATH:

export PATH=<path to your maven>/apache-maven-3.3.9/bin:$PATH

2. Update following environmental variables to point to the new Spark location:

export SPARK_HOME=/home/<your_username>/your_local_spark/spark-2.2.0
export PATH=$SPARK_HOME/sbin:$SPARK_HOME/bin:$PATH

these lines should be added to the .bashrc file on your laptop, otherwise you would have to export these values each time you log in!

Download and install Anaconda, install necessary Python packages

Please go to the following website: https://www.continuum.io/downloads download and install the latest Anaconda version for Python 3 for your operating system.

Note: we are going to need Anaconda 5.x or later

After that, type:

conda --help

and read the manual. Once Anaconda is ready, proceed with setting up the environment:

#if you do not have git, you can download the repo as a zip https://github.com/ASvyatkovskiy/BigDataCourse/archive/master.zip
git clone https://github.com/ASvyatkovskiy/BigDataCourse && cd BigDataCourse
conda create --name my_conda --file 0_Preexercise/conda-requirements.txt
source activate my_conda

Set up Spark-enabled Jupyter notebook

Locate your anaconda python:

#source activate my_env
which python

this query will return something like /path/to/my/anaconda/bin/python, copy the path up to the bin folder.

Set environmental variables to launch Spark-enabled jupyter notebook.

export PYSPARK_DRIVER_PYTHON="/path/to/my/anaconda/bin/jupyter"
export PYSPARK_DRIVER_PYTHON_OPTS="notebook"
export PYSPARK_PYTHON="/path/to/my/anaconda/bin/python"

and add them to your .profile so that you do not need to retype every time you open a command line window.

Next launch of pyspark shell will prompt you to the notebook:

pyspark [options]

where [options] is the list of flags you pass to pyspark. Proceed to pre-exercise.

Additional installations (optional)

Pre-requisites

First, ensure you got the right version of jupyter and Java by typing:

jupyter --version

it should print a value >= 5.0, and

java -version

it should print a value like "1.8.0". If have version 1.7 on your laptops then go to http://download.oracle.com website and download it. Here is the direct link for Mac users: http://download.oracle.com/otn-pub/java/jdk/8u101-b13/jdk-8u101-macosx-x64.dmg

Finally, check the SPARK_HOME environmental variable is set:

echo $SPARK_HOME

(should return a non empty string on the screen)

Install Apache Toree

If all the prerequisites are in order, proceed to install Apache Toree - it provides a Scala Spark kernel for Jupyter.

#cd BigDataCourse
pip install --user Toree/toree-0.2.0.dev1.tar.gz

Configure Apache Toree installation with Jupyter:

jupyter toree install --spark_home=$SPARK_HOME

If you get an error message like: jupyter: 'toree' is not a Jupyter command, then you would need to set:

export PATH=~/.local/bin:$PATH

and re-issue the command.

Confirm installation:

jupyter kernelspec list

You should see something like:

Available kernels:
  python2               /Users/alexey/anaconda/envs/BDcourseFall2016/lib/python2.7/site-packages/ipykernel/resources
  apache_toree_scala    /usr/local/share/jupyter/kernels/apache_toree_scala

Next launch of jupyter notebook will give you an option to choose Apache Toree kernel from the upper right menu, which supports Scala and Spark.

In case help needed

If you are experiencing any problems with the installation part or pre-exercises: please email me at alexeys@princeton.edu or come see me at the regular CSES office hours on Tuesday.