Informations relatives cluster spark
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SWARM MANAGER
docker swarm init --advertise-addr IP_FLOATINGc1:PORTx --data-path-addr IP_FLOATINGc1 --listen-addr 0.0.0.0:PORTx

SWARM  WORKER
docker swarm join --token <...> --advertise-addr IP_FLOATINGc2:PORTy IP_FLOATINGc1:PORTx

NB: PORTx et PORTy >= 50000 (restriction INSA)

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MASTER
docker run -dit --name spark-master --network sparknet -p 8080:8080 chasik/sparkmaster:v1

SUBMIT
docker run -it --name spark-submit -v /home/user/entry:/entry --network sparknet -p 4040:4040 chasik/sparksubmit:v1 bash

WORKER1
docker run -dit --name spark-worker1 --network sparknet -p 8081:8081 -e CORES=2 chasik/sparkworker:v1
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WORKER2
docker run -dit --name spark-worker2 --network sparknet -p 8081:8081 -e CORES=2 chasik/sparkworker:v1

WORKER3
docker run -dit --name spark-worker3 --network sparknet -p 8082:8081 -e CORES=2 chasik/sparkworker:v1
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WORKER4
docker run -dit --name spark-worker4 --network sparknet -p 8081:8081 -e CORES=2 chasik/sparkworker:v1

WORKER5
docker run -dit --name spark-worker5 --network sparknet -p 8082:8081 -e CORES=2 chasik/sparkworker:v1
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WORKER6
docker run -dit --name spark-worker6 --network sparknet -p 8081:8081 -e CORES=2 chasik/sparkworker:v1

WORKER7
docker run -dit --name spark-worker7 --network sparknet -p 8082:8081 -e CORES=2 chasik/sparkworker:v1
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Task Submit (nœud spark-submit)
/spark/bin/spark-submit --conf spark.executor.cores=2 --conf spark.executor.memory=5G --master spark://spark-master:7077 /spark/examples/src/main/python/<pi.py> <2000> .param2.. <.paramn..>

Information: files can be put in folder "entry" in order be easily launchable in spark-submit