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Materials for the 'Let's break Apache Spark' workshop

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workshop-break-spark

Materials for the 'Let's break Apache Spark' workshop

Useful commands

# show master logs
docker exec -it jupyter-spark-master tail -f /opt/spark/logs/spark--org.apache.spark.deploy.master.Master-1-spark-master.out -n 1000

# show slave1 logs
docker exec -it jupyter-spark-slave-1 tail -f /opt/spark/logs/spark--org.apache.spark.deploy.worker.Worker-1-spark-slave-1.out -n 1000

# show slave2 logs
docker exec -it jupyter-spark-slave-2 tail -f /opt/spark/logs/spark--org.apache.spark.deploy.worker.Worker-2-spark-slave-2.out -n 1000

# run bash on jupyter-notebook
docker exec -it jupyter-notebook bash
cd /opt/spark-2.2.0-bin-without-hadoop/

# run spark-submit
bin/spark-submit --executor-memory=1G --conf "spark.driver.memory=1G" --conf "spark.cores.max=10" --conf "spark.executor.cores=1" --master spark://spark-master:7077 examples/src/main/python/pi.py

# bring the whole system up
docker-compose up

# bring the whole system down
docker-compose down

# show running docker containers
docker ps

# show configuration of a container
docker inspect jupyter-notebook

# stop one of the 'boxes'
docker stop jupyter-spark-master

# start one of the 'boxes'
docker start jupyter-spark-master

# create a required network to connect the containers
docker network create dimajix

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Materials for the 'Let's break Apache Spark' workshop

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