Docker is a container management platform for automating deployments of re-usable environemnets.
Containers are a type of virtualization. They virtualize environments at the operating system level by sharing the base libraries. This removes the need for boot drives and hardware interfaces for each environment. This makes a container use much less resources than a virtual machine (VM) which can make environments more efficient because lack of duplication of resources.
Using Docker we can keep a fresh deployment of our Hadoop/Jupyter/Spark environment readily avaliable. Taking around 2 minutes to remove and launch a new environment with the same initial configuration everytime.
Download Docker Community Edition from Docker
docker pull w261/w261-environment
In the container for W261 we use docker-compose to build our container. Let's review the configuration file docker-compose.yml in its current state at the time of writing
version: '2'
services:
quickstart.cloudera:
# from repo
image: w261/w261-environment:latest
# from local
# image: w261:latest
hostname: quickstart.cloudera
privileged: true
command: bash -c "/root/start-notebook-python.sh; /root/start-notebook-pyspark.sh;/usr/bin/docker-quickstart; conda install -c conda-forge mrjob=0.5.5"
ports:
- "8887:8888" # Hue server
- "8889:8889" # jupyter
- "10020:10020" # mapreduce job history server
- "8022:22" # ssh
- "7180:7180" # Cloudera Manager
- "11000:11000" # Oozie
- "50070:50070" # HDFS REST Namenode
- "50075:50075" # hdfs REST Datanode
- "8088:8088" # yarn resource manager webapp address
- "19888:19888" # mapreduce job history webapp address
- "8983:8983" # Solr console
- "8032:8032" # yarn resource manager access
- "8042:8042" # yarn node manager
- "60010:60010" # hbase
tty: true
stdin_open: true
volumes:
# windows example
# - C:\Users\winegarj\w261:/media/notebooks
# linux example
# - /home/winegarj/w261-repo:/media/notebooks
- C:\Users\winegarj\w261:/media/notebooks
- version: this item says use v2 syntax
- services: list of containers
- quickstart.cloudera: the name of a container, the label being quickstart.cloudera
- image: use this base container
- hostname: DNS name for the container
- privledged: allow access to other machines such as the local machine
- commands: run this commands on start
- ports: map ports so that services running on the container are accessible from the local computer
- remote port:local port
- tty: allow a shell to be initiated
- stdin_open: allow interactivity with the shell
- volumes: location to map from local computer to the docker container so they can share.
- /local/path:/media/notebook
- quickstart.cloudera: the name of a container, the label being quickstart.cloudera
If we review the bash scripts startup.sh
we can see that the jupyter notebook is launched from the /media/notebook
directory. This is very important for our deployment.
- Install Docker (Restart as needed)
- Copy the contents of the
docker-compose.yml
file in this repo to somewhere on your computer with the same name - Edit the
Volume
section to match where you want to store your notebooks/homework locally - Open up a terminal or Powershell windows and change directory to where you stored your
docker-compose.yml
file - Run
docker-compose up
- Open your browser and go to
localhost:8889
for regular Python, MRJob, and Pyspark - If using spark a sparkContext is automatically defined during initialization, in the
sc
variable
Using python packages against HDFS
Add the following parameter to Map Reduce Streaming and MRJob commands:
-cmdenv PATH=/opt/anaconda/bin:$PATH
Apply the quickstart.cloudera
alias for 127.0.0.1
aka localhost
- Linux & Mac
- Open Terminal
- Open hostfile by running
sudo nano /etc/hosts
- Append the following line, then save:
127.0.0.1 quickstart.cloudera
- Refresh DNS with
sudo killall -HUP mDNSResponder
- Windows:
- Open notepad as administrator (otherwise you'll not be able to save the file)
- Open
C:\Windows\System32\drivers\etc\hosts
in notepad. Note the file has no extension - Append the following line, then save:
127.0.0.1 quickstart.cloudera
- Refresh DNS by running
ipconfig /flushdns
in command prompt or powershell
Docker needs 2 CPUs and 4 GB of RAM to ensure resource managers don't crash during normal operation.
- Linux
- By default Docker shares the same resources as the local computer.
- Windows
- Right click Docker in the notification area
- Click Settings
- Click Advanced
- Slide Memory to 4096 MB
- Mac OS
- Click Docker in the clock(?) area
- Click Settings
- Click Advanced
- Slide Memory to 4096 MB
- Windows 10 Pro/Education is required to run Docker on Windows. A free license of Windows 10 Education is avaliable to all students through UCB Software Central
- jupyter/notebook#484 This has been addressed with Jupyter 5.1.0 which is being used for latest build of the container.
- Macs require a computer capable of virtualization to test this run
sysctl kern.hv_support
in a terminal.- If 1 then good to go
- If 0 then you need a new computer