First project of SABD A.A. 2019/2020
Open a terminal in the main directory of the project and exec the command
sudo docker-compose up
It will begin to pull the docker images used. We have used docker images mostly revisited by us present in our docker hub.
When Docker compose has started the master, open a new terminal and type:
sudo docker exec -it master /bin/bash
And then, in the same terminal type
sh data/startHDFS.sh
This command will format the HDFS and run it. From now on you can open on your browser a new web page and type http://localhost:9870/ to see the status of the HDFS from webUI.
To see the NiFi status open a new web page on your browser and type http://localhost:8080/nifi
Now, after Nifi and HDFS have been started, the Spark master will automatically start.
Finally the results of the executions will be available in the HDFS, in the "results" folder and in Redis at the address link http://localhost:5001.
By opening the Redis web page, type redis
in place of localhost, next to the host
entry.
Selecting the database ID, with ID = 1 we will go to view the result of query1, with ID = 2 we will go to view the result of query 2, with ID = 3 we will go to view the result of query 3 with Spark MLlib and with ID = 4 we will go to view the result of query 3 with K-means naive.
For run Spark-Master, open a terminal and type:
sh script/avvoSparkMaster.sh
For run Spark-Workers, open a terminal and type:
docker run -it --network=project_network --name spark-worker-1 --link spark-master:spark-master -e ENABLE_INIT_DAEMON=false bde2020/spark-worker:2.4.5-hadoop2.7
docker run -it --network=project_network --name spark-worker-2 --link spark-master:spark-master -e ENABLE_INIT_DAEMON=false bde2020/spark-worker:2.4.5-hadoop2.7
docker run -it --network=project_network --name spark-worker-2 --link spark-master:spark-master -e ENABLE_INIT_DAEMON=false bde2020/spark-worker:2.4.5-hadoop2.7
For run Spark-Submitter, open a terminal and type:
sh script/avvoSparkSubmit.sh
To kill all the containers, type CTRL + C
on the terminal where the sudo docker-compose up
command was launched and finally to remove them, run the command
sh stopAndClean.sh