Spark Mail Tutorial On Docker

See medale spark-mail-docker github repo

Installing Docker

Obtaining medale/spark-mail-docker from DockerHub

sudo docker pull medale/spark-mail-docker:v1.2.1

Run spark-mail-docker image

Simple run (no shared drive)

  • -P map image ports to host port (see docker ps -l for mapping)
  • -i run in interactive mode
  • -t with tty terminal
  • -h sets hostname of the image to “sandbox”
  • medale/spark-mail-docker:v1.2.1 image and version of image
  • /etc/ - complete bootstrap
  • bash - then run bash (login as root)

    sudo docker run -P -i -t -h sandbox medale/spark-mail-docker:v1.2.1 /etc/ bash

Mounting a share drive to the image

-v Mount host /opt/rpm1 on image /opt/rpm1 (share files between image and host)

sudo docker run -v /opt/rpm1:/opt/rpm1 -P -i -t -h sandbox medale/spark-mail-docker:v1.2.1 /etc/ bash
> Starting sshd:                                             [  OK  ]
> Starting namenodes on [sandbox]
> sandbox: starting namenode, logging to /usr/local/hadoop/logs/hadoop-root-namenode-sandbox.out
> localhost: starting datanode, logging to /usr/local/hadoop/logs/hadoop-root-datanode-sandbox.out

Image layout

Running the image with the bash command brings you to a shell prompt as root:

> /root
> enron-small.avro  mailrecord-utils-0.9.0-SNAPSHOT-shaded.jar
hdfs dfs -ls
> Found 2 items
> -rw-r--r--   1 root supergroup  324088129 2015-03-01 22:11 enron.avro
> drwxr-xr-x   - root supergroup          0 2015-01-15 04:05 input
> SPARK_HOME=/usr/local/spark
> JAVA_HOME=/usr/java/default
> YARN_CONF_DIR=/usr/local/hadoop/etc/hadoop
> ...

Running Spark with minimum logging and kryo serialization

(if you are not in /root, cd /root)
> Spark assembly has been built with Hive, including Datanucleus jars on classpath
> ...
> scala>

Analytic 1

    import org.apache.spark.SparkContext._
    import org.apache.spark.rdd._
    import com.uebercomputing.mailparser.enronfiles.AvroMessageProcessor
    import com.uebercomputing.mailrecord._
    import com.uebercomputing.mailrecord.Implicits.mailRecordToMailRecordOps
    val args = Array("--avroMailInput", "enron.avro")
    val config = CommandLineOptionsParser.getConfigOpt(args).get
    val recordsRdd = MailRecordAnalytic.getMailRecordsRdd(sc, config)
    val d = recordsRdd.filter(record => record.getFrom == "")
    > resN: Long = 8

Accessing Spark Web UI

Docker creates an internal IP address for the image we started. To determine this IP address we can either do this from the host machine:

sudo docker ps
> CONTAINER ID        IMAGE                      COMMAND                CREATED             STATUS              PORTS
> bb5cf832bd76        medale/spark-mail-docker:v1.2.1   "/etc/ /   13 minutes ago      Up 13 minutes       0.0.0
sudo docker inspect --format=".NetworkSettings.IPAddress" bb5cf832bd76

Or we could run the following on the image container:

> eth0      Link encap:Ethernet  HWaddr 02:42:AC:11:00:12  
           inet addr:  Bcast:  Mask:

Now we can go to the Resource Manager from local browser on host:


From there, click on ApplicationMaster (under TrackingUI column). The link goes to something like:

  • http://sandbox:8088/proxy/application_1425314491113_0001/ (which does not exist)
  • Replace sandbox with the previously obtained IP address, for example:

Creating a host alias to avoid having to replace “sandbox”

Alternatively, on Linux, we can use the HOSTALIASES environment variable to temporarily map sandbox to the container IP address and then run our browser with that environment variable to translate sandbox references to the container IP:

On your host, edit host-alias with the container IP address. For example this host-alias:



export HOSTALIASES=host-alias
# start firefox in background with that environment variable set

In the browser, go to http://sandbox:8088/. Now all http://sandbox… links on that page should work.

Image Overview

In addition to Hadoop we have:

Customized spark-1.2.1

We then add a customized spark-1.2.1.tar.gz. See these instructions on how to build this distro (tar assumes directory spark-1.2.1-hadoop2.4 inside of the tar.gz file).

Other files not in this github repo

  • enron-small.avro - an arbitrary subset (however big you want to process) of Avro version of Enron emails. See Spark Mail for overview of how to obtain the emails and convert them to .avro format. Also see Main.scala.

Additional files

  • - suppresses DEBUG and INFO messages for less clutter
  • - script to start up Spark shell in yarn-client mode with Kryo

Building medale/spark-mail-docker locally

  • must create spark-1.2.1.tar.gz (see above)
  • must create enron-small.avro (see above)

Add both files to docker-spark directory (same directory as Dockerfile).

sudo docker build -t medale/spark-mail-docker .
sudo docker images  #lists container id (assumed here to be e57ff7c77397)
sudo docker tag e57ff7c77397 medale/spark-mail-docker:v1.2.1

(Optional) Publish to DockerHub

After creating account on DockerHub you can publish your image to a public repo so others can find and pull it without having to build the image locally:

sudo docker push medale/spark-mail-docker:v1.2.1
sudo docker search medale
sudo docker pull medale/spark-mail-docker:v1.2.1

Other useful Docker commands

    # Show available images
    sudo docker images
    > REPOSITORY                 TAG                 IMAGE ID            CREATED             VIRTUAL SIZE
    > medale/spark-mail-docker          v1.2.1              5e4665af6d6e        13 hours ago        2.84 GB
    > ...

    # Delete a local image
    sudo docker rmi training/sinatra

    # Delete a stopped instance
    sudo docker ps -a -q # show all containers, just id
    sudo docker rm <container id>

    # Show docker container ids
    sudo docker ps -l

    # Commit changes to an image
    sudo docker commit <container_id> medale/new_image

For background see dockerimages and Docker builder reference.

Dockerfiles lore

ADD local.jar /some-container-location If src is a local tar archive in a recognized compression format (identity, gzip, bzip2 or xz) then it is unpacked as a directory