kyuubi/docs/deployment/on_kubernetes.md
Cheng Pan a76c344042
[KYUUBI #951] [LICENSE] Add license header on all docs
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Closes #951 from pan3793/license.

Closes #951

4629eecd [Cheng Pan] Fix
c45a0784 [Cheng Pan] nit
b9a46b42 [Cheng Pan] pin license header at first line
80d1a71b [Cheng Pan] nit
b2a46e4c [Cheng Pan] Update
f6acaaf8 [Cheng Pan] minor
ef99183f [Cheng Pan] Add license header on all docs

Authored-by: Cheng Pan <chengpan@apache.org>
Signed-off-by: Cheng Pan <chengpan@apache.org>
2021-08-19 09:53:52 +08:00

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<div align=center>
![](../imgs/kyuubi_logo.png)
</div>
# Deploy Kyuubi engines on Kubernetes
## Requirements
When you want to run Kyuubi's Spark SQL engines on Kubernetes, you'd better have cognition upon the following things.
* Read about [Running Spark On Kubernetes](http://spark.apache.org/docs/latest/running-on-kubernetes.html)
* An active Kubernetes cluster
* [Kubectl](https://kubernetes.io/docs/reference/kubectl/overview/)
* KubeConfig of the target cluster
## Configurations
### Master
Spark on Kubernetes config master by using a special format.
`spark.master=k8s://https://<k8s-apiserver-host>:<k8s-apiserver-port>`
You can use cmd `kubectl cluster-info` to get api-server host and port.
### Docker Image
Spark ships a `./bin/docker-image-tool.sh` script to build and publish the Docker images for running Spark applications on Kubernetes.
When deploying Kyuubi engines against a Kubernetes cluster, we need to set up the docker images in the Docker registry first.
Example usage is:
```shell
./bin/docker-image-tool.sh -r <repo> -t my-tag build
./bin/docker-image-tool.sh -r <repo> -t my-tag push
# To build docker image with specify openJdk
./bin/docker-image-tool.sh -r <repo> -t my-tag -b java_image_tag=<openjdk:${java_image_tag}> build
# To build additional PySpark docker image
./bin/docker-image-tool.sh -r <repo> -t my-tag -p ./kubernetes/dockerfiles/spark/bindings/python/Dockerfile build
# To build additional SparkR docker image
./bin/docker-image-tool.sh -r <repo> -t my-tag -R ./kubernetes/dockerfiles/spark/bindings/R/Dockerfile build
```
### Test Cluster
You can use the shell code to test your cluster whether it is normal or not.
```shell
$SPARK_HOME/bin/spark-submit \
--master k8s://https://<k8s-apiserver-host>:<k8s-apiserver-port> \
--class org.apache.spark.examples.SparkPi \
--conf spark.executor.instances=5 \
--conf spark.dynamicAllocation.enabled=false \
--conf spark.shuffle.service.enabled=false \
--conf spark.kubernetes.container.image=<spark-image> \
local://<path_to_examples.jar>
```
When running shell, you can use cmd `kubectl describe pod <podName>` to check if the information meets expectations.
### ServiceAccount
When use Client mode to submit application, spark driver use the kubeconfig to access api-service to create and watch executor pods.
When use Cluster mode to submit application, spark driver pod use serviceAccount to access api-service to create and watch executor pods.
In both cases, you need to figure out whether you have the permissions under the corresponding namespace. You can use following cmd to create serviceAccount (You need to have the kubeconfig which have the create serviceAccount permission).
```shell
# create serviceAccount
kubectl create serviceaccount spark -n <namespace>
# binding role
kubectl create clusterrolebinding spark-role --clusterrole=edit --serviceaccount=<namespace>:spark --namespace=<namespace>
```
### Volumes
As it known to us all, Kubernetes can use configurations to mount volumes into driver and executor pods.
* hostPath: mounts a file or directory from the host nodes filesystem into a pod.
* emptyDir: an initially empty volume created when a pod is assigned to a node.
* nfs: mounts an existing NFS(Network File System) into a pod.
* persistentVolumeClaim: mounts a PersistentVolume into a pod.
Note: Please
see [the Security section of this document](http://spark.apache.org/docs/latest/running-on-kubernetes.html#security) for security issues related to volume mounts.
```
spark.kubernetes.driver.volumes.<type>.<name>.options.path=<dist_path>
spark.kubernetes.driver.volumes.<type>.<name>.mount.path=<container_path>
spark.kubernetes.executor.volumes.<type>.<name>.options.path=<dist_path>
spark.kubernetes.executor.volumes.<type>.<name>.mount.path=<container_path>
```
Read [Using Kubernetes Volumes](http://spark.apache.org/docs/latest/running-on-kubernetes.html#using-kubernetes-volumes) for more about volumes.
### PodTemplateFile
Kubernetes allows defining pods from template files. Spark users can similarly use template files to define the driver or executor pod configurations that Spark configurations do not support.
To do so, specify the spark properties `spark.kubernetes.driver.podTemplateFile` and `spark.kubernetes.executor.podTemplateFile` to point to local files accessible to the spark-submit process.
### Other
You can read Spark's official documentation for [Running on Kubernetes](http://spark.apache.org/docs/latest/running-on-kubernetes.html) for more information.