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Maven Central

spark-simple-archetype

Creating a project

Simple maven archetype to startup a Java-based Apache Spark project.

To create your project:

mvn archetype:generate \
  -DgroupId=your.group \
  -DartifactId=your_project \
  -DarchetypeGroupId=fr.uha.ensisa.ff \
  -DarchetypeArtifactId=spark-simple-archetype \
  -DarchetypeVersion=0.0.8 \
  -DinteractiveMode=false

Compile project

To compile your project: mvn clean verify

To run locally (once compiled): java -jar target/your_project-*.jar

In case you're running a JDK ≥ 16 : java --add-opens java.base/java.util=ALL-UNNAMED --add-opens java.base/java.lang=ALL-UNNAMED --add-opens java.base/java.util.concurrent=ALL-UNNAMED --add-opens java.base/java.net=ALL-UNNAMED --add-opens java.base/java.nio=ALL-UNNAMED --add-opens java.base/java.lang.invoke=ALL-UNNAMED --add-opens java.base/sun.nio.ch=ALL-UNNAMED -jar target/your_project-*.jar

Running a cluster using docker swarm

You need to run commands using a bash command line (for windows user, use git bash).

Getting a docker swarm using Vagrant

First install Vagrant and VirtualBox.

The following fires a 3 node cluster (can be changed using the NODES environment variable).

git clone --depth=1 https://github.com/fondemen/docker-swarm-vagrant.git
cd docker-swarm-vagrant
vagrant up
until vagrant ssh node01 -c 'etcdctl cluster-health' ; do sleep 1; done
SWARM=on vagrant up

You might need to select an ethernet interface to connect to ; usually, the first one is best.

To re-use an previously started-then-stopped cluster

cd docker-swarm-vagrant
vagrant up

You might need to vagrant destroy -f and retry in case the above fails.

Please, check the docker-swarm-vagrant project for more details on setting up the swarm cluster.

Uploading jar to Vagrant node

The easiest is to install the scp plugin: vagrant plugin install vagrant-scp Compile you project as explained above

for m in $(vagrant status --machine-readable | grep ',state,' | cut -d, -f2); do vagrant scp ../your_project/target/your_project-*.jar $m:~/ana.jar; done

Firing up a spark cluster

Not ready for production !

In case you use the Vagrant approach, login to the first node : vagrant ssh.

docker network create -d overlay spark-nw
docker service create --name spark-master --replicas 1 --network spark-nw  -e INIT_DAEMON_STEP=setup_spark -p 8080:8080 bde2020/spark-master:3.1.1-hadoop3.2-java11
docker service create --name spark-worker --mode global --network spark-nw  -e "SPARK_MASTER=spark://spark-master:7077" --limit-memory 1280M bde2020/spark-worker:3.1.1-hadoop3.2-java11

The master (and only the master) is visible at http://192.168.59.99:8080. To see also workers activity, use a proxy such as Sqid :

docker service create --name squid --replicas 1 --network spark-nw -p 3128:3128 chrisdaish/squid

Then configure your browser to use an HTTP proxy server with host 192.168.59.99 and port 3128.

Submitting your Spark analysis

In case you use the Vagrant approach, you must have uploaded your Spark program and logged in to node01 using vagrant ssh.

We assume here that your Spark analysis is available on ./ana.jar.

Change the main class path in the following command (don't forget to change main class - [your.group.Main]):

docker service create --name ana -p 4040:4040 --network spark-nw --restart-condition none -e ENABLE_INIT_DAEMON=false -e SPARK_APPLICATION_JAR_NAME=ana -e SPARK_APPLICATION_JAR_LOCATION=/app/ana.jar -e SPARK_APPLICATION_MAIN_CLASS=[your.group.Main] --mount source=$(pwd)/ana.jar,target=/app/ana.jar,type=bind bde2020/spark-submit:3.1.1-hadoop3.2-java11

You can read your application driver logs: docker service logs -f ana

Once finished, delete the ana service: docker service rm ana

Stopping the Vagrant swarm cluster

Exit the node01 node (exit command).

vagrant destroy -f