A faster way to setup spark-standalone on a docker environment or any kubernetes cluster.
For running spark-standalone you simply place a compiled version of Spark on each node on the cluster.The installation steps were taken from the official documentation and containerized for running it on a docker environment or Kubernetes environment. To install spark on any of these environments we need to have:
- Docker and docker-compose installed on your machine.
- Kubernetes cluster installed on your machine if you want to install spark on kubernetes.
| Service | Version |
|---|---|
| Spark | 2.4.7 |
| Hadoop | 2.10.1 |
- Clone the project abd navigate to the main directory
git clone -b spark-2.4 https://github.com/romans-weapon/spark-on-kubernetes.git && cd spark-on-kubernetes/
- Run the script file to setup spark using docker-compose with the below command
sh spark-docker-setup.sh
kmaster@ubuntu:~/spark-on-kubernetes$ sh spark-docker-setup.sh
[Wed Feb 16 02:36:38 AM PST 2022] INFO:[+]Deploying spark onto docker env [started]
[Wed Feb 16 02:36:38 AM PST 2022] INFO:[+]Starting containers for spark master and worker [started]
Creating network "docker-compose_default" with the default driver
Creating spark-master ... done
Creating spark-worker_2 ... done
Creating spark-worker_1 ... done
[Wed Feb 16 02:36:52 AM PST 2022] INFO:[+]Starting containers for spark master and worker [success]
[Wed Feb 16 02:36:52 AM PST 2022] INFO:[+]Deploying spark onto docker env [success]
- Once spark deployment is successful as shown above,check whether your containers are up and running as shown below
kmaster@ubuntu:~/spark-on-kubernetes$ docker ps
CONTAINER ID IMAGE COMMAND CREATED STATUS PORTS NAMES
6d385f3290a7 spearframework/spark-2.4:kubernetes "/bin/sh /spark-work…" 24 seconds ago Up 22 seconds 0.0.0.0:8081->8081/tcp, :::8081->8081/tcp spark-worker_1
60a16c12e1d9 spearframework/spark-2.4:kubernetes "/bin/sh /spark-work…" 24 seconds ago Up 22 seconds 0.0.0.0:8082->8082/tcp, :::8082->8082/tcp spark-worker_2
3faca27d35bc spearframework/spark-2.4:kubernetes "/bin/sh /spark-mast…" 25 seconds ago Up 23 seconds 0.0.0.0:7077->7077/tcp, :::7077->7077/tcp, 0.0.0.0:8080->8080/tcp, :::8080->8080/tcp spark-master
- Once they are healthy and running, you can exec into any of the worker nodes and start running spark as shown below
kmaster@ubuntu:~/spark-on-kubernetes$ docker exec -it spark-worker_1 bash
root@6d385f3290a7:/# spark-shell
Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
Setting default log level to "WARN".
To adjust logging level use sc.setLogLevel(newLevel). For SparkR, use setLogLevel(newLevel).
Spark context Web UI available at http://6d385f3290a7:4040
Spark context available as 'sc' (master = spark://spark-master:7077, app id = app-20220216103753-0000).
Spark session available as 'spark'.
Welcome to
____ __
/ __/__ ___ _____/ /__
_\ \/ _ \/ _ `/ __/ '_/
/___/ .__/\_,_/_/ /_/\_\ version 2.4.7
/_/
Using Scala version 2.11.12 (OpenJDK 64-Bit Server VM, Java 1.8.0_111)
Type in expressions to have them evaluated.
Type :help for more information.
scala>
git clone -b spark-2.4 https://github.com/romans-weapon/spark-on-kubernetes.git && cd spark-on-kubernetes/
- Run the script file
sh spark-kubernetes-setup.sh
Below is what you see when you run the script mentioned above
kmaster@ubuntu:~/spark-on-kubernetes$ sh spark-kubernetes-setup.sh
[Wed Feb 16 07:16:41 PM PST 2022] INFO:[+]Deploying spark-standalone onto kubernetes cluster [started]
[Wed Feb 16 07:16:41 PM PST 2022] INFO:[+]Creating namespace for spark [started]
namespace/spark-cluster created
[Wed Feb 16 07:16:42 PM PST 2022] INFO:[+]Creating namespace for spark [success]
[Wed Feb 16 07:16:42 PM PST 2022] INFO:[+]Spark master and worker deployment [started]
service/spark-master created
service/spark-webui created
deployment.apps/spark-master-deploy created
deployment.apps/spark-worker-deploy created
[Wed Feb 16 07:16:52 PM PST 2022] INFO:[+]Spark master and worker deployment [success]
NAME READY STATUS RESTARTS AGE
pod/spark-master-deploy-5bb86d9bdd-r9m9k 1/1 Running 0 10s
pod/spark-worker-deploy-6c8fcf4968-4zkg7 1/1 Running 0 10s
pod/spark-worker-deploy-6c8fcf4968-trn59 1/1 Running 0 10s
pod/spark-worker-deploy-6c8fcf4968-v27rd 1/1 Running 0 10s
NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE
service/spark-master ClusterIP 10.245.120.133 <none> 7077/TCP 11s
service/spark-webui ClusterIP 10.245.69.153 <none> 8080/TCP 11s
NAME READY UP-TO-DATE AVAILABLE AGE
deployment.apps/spark-master-deploy 1/1 1 1 11s
deployment.apps/spark-worker-deploy 3/3 3 3 10s
NAME DESIRED CURRENT READY AGE
replicaset.apps/spark-master-deploy-5bb86d9bdd 1 1 1 11s
replicaset.apps/spark-worker-deploy-6c8fcf4968 3 3 3 10s
[Wed Feb 16 07:16:53 PM PST 2022] INFO:[+]Deploying spark onto kubernetes cluster [success]
kmaster@ubuntu:~/spark-on-kubernetes$
Once the above deployment is successful you can exec into any of the worker nodes and run your spark jobs as shown below
kmaster@ubuntu:~/spark-on-kubernetes$ kubectl exec -it spark-worker-deploy-6c8fcf4968-trn59 -n spark-cluster -- bash
root@spark-worker-deploy-6c8fcf4968-trn59:/# spark-shell
Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
Setting default log level to "WARN".
To adjust logging level use sc.setLogLevel(newLevel). For SparkR, use setLogLevel(newLevel).
Spark context Web UI available at http://spark-worker-deploy-6c8fcf4968-trn59:4040
Spark context available as 'sc' (master = spark://spark-master:7077, app id = app-20220217054900-0000).
Spark session available as 'spark'.
Welcome to
____ __
/ __/__ ___ _____/ /__
_\ \/ _ \/ _ `/ __/ '_/
/___/ .__/\_,_/_/ /_/\_\ version 2.4.7
/_/
Using Scala version 2.11.12 (OpenJDK 64-Bit Server VM, Java 1.8.0_111)
Type in expressions to have them evaluated.
Type :help for more information.
scala>
Once you are able to submit your spark jobs you can view then on your webui at
http://<host_name>:8080
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