mirror of https://github.com/k3s-io/k3s
245 lines
9.3 KiB
Markdown
245 lines
9.3 KiB
Markdown
<!-- BEGIN MUNGE: UNVERSIONED_WARNING -->
|
|
|
|
<!-- BEGIN STRIP_FOR_RELEASE -->
|
|
|
|
<img src="http://kubernetes.io/img/warning.png" alt="WARNING"
|
|
width="25" height="25">
|
|
<img src="http://kubernetes.io/img/warning.png" alt="WARNING"
|
|
width="25" height="25">
|
|
<img src="http://kubernetes.io/img/warning.png" alt="WARNING"
|
|
width="25" height="25">
|
|
<img src="http://kubernetes.io/img/warning.png" alt="WARNING"
|
|
width="25" height="25">
|
|
<img src="http://kubernetes.io/img/warning.png" alt="WARNING"
|
|
width="25" height="25">
|
|
|
|
<h2>PLEASE NOTE: This document applies to the HEAD of the source tree</h2>
|
|
|
|
If you are using a released version of Kubernetes, you should
|
|
refer to the docs that go with that version.
|
|
|
|
<strong>
|
|
The latest 1.0.x release of this document can be found
|
|
[here](http://releases.k8s.io/release-1.0/examples/spark/README.md).
|
|
|
|
Documentation for other releases can be found at
|
|
[releases.k8s.io](http://releases.k8s.io).
|
|
</strong>
|
|
--
|
|
|
|
<!-- END STRIP_FOR_RELEASE -->
|
|
|
|
<!-- END MUNGE: UNVERSIONED_WARNING -->
|
|
|
|
# Spark example
|
|
|
|
Following this example, you will create a functional [Apache
|
|
Spark](http://spark.apache.org/) cluster using Kubernetes and
|
|
[Docker](http://docker.io).
|
|
|
|
You will setup a Spark master service and a set of
|
|
Spark workers using Spark's [standalone mode](http://spark.apache.org/docs/latest/spark-standalone.html).
|
|
|
|
For the impatient expert, jump straight to the [tl;dr](#tldr)
|
|
section.
|
|
|
|
### Sources
|
|
|
|
The Docker images are heavily based on https://github.com/mattf/docker-spark
|
|
|
|
## Step Zero: Prerequisites
|
|
|
|
This example assumes you have a Kubernetes cluster installed and
|
|
running, and that you have installed the ```kubectl``` command line
|
|
tool somewhere in your path. Please see the [getting
|
|
started](../../docs/getting-started-guides/) for installation
|
|
instructions for your platform.
|
|
|
|
## Step One: Start your Master service
|
|
|
|
The Master [service](../../docs/user-guide/services.md) is the master service
|
|
for a Spark cluster.
|
|
|
|
Use the
|
|
[`examples/spark/spark-master-controller.yaml`](spark-master-controller.yaml)
|
|
file to create a
|
|
[replication controller](../../docs/user-guide/replication-controller.md)
|
|
running the Spark Master service.
|
|
|
|
```console
|
|
$ kubectl create -f examples/spark/spark-master-controller.yaml
|
|
replicationcontrollers/spark-master-controller
|
|
```
|
|
|
|
Then, use the
|
|
[`examples/spark/spark-master-service.yaml`](spark-master-service.yaml) file to
|
|
create a logical service endpoint that Spark workers can use to access the
|
|
Master pod.
|
|
|
|
```console
|
|
$ kubectl create -f examples/spark/spark-master-service.yaml
|
|
services/spark-master
|
|
```
|
|
|
|
You can then create a service for the Spark Master WebUI:
|
|
|
|
```console
|
|
$ kubectl create -f examples/spark/spark-webui.yaml
|
|
services/spark-webui
|
|
```
|
|
|
|
### Check to see if Master is running and accessible
|
|
|
|
```console
|
|
$ kubectl get pods
|
|
NAME READY STATUS RESTARTS AGE
|
|
spark-master-controller-5u0q5 1/1 Running 0 8m
|
|
```
|
|
|
|
Check logs to see the status of the master. (Use the pod retrieved from the previous output.)
|
|
|
|
```sh
|
|
$ kubectl logs spark-master-controller-5u0q5
|
|
starting org.apache.spark.deploy.master.Master, logging to /opt/spark-1.5.1-bin-hadoop2.6/sbin/../logs/spark--org.apache.spark.deploy.master.Master-1-spark-master-controller-g0oao.out
|
|
Spark Command: /usr/lib/jvm/java-8-openjdk-amd64/jre/bin/java -cp /opt/spark-1.5.1-bin-hadoop2.6/sbin/../conf/:/opt/spark-1.5.1-bin-hadoop2.6/lib/spark-assembly-1.5.1-hadoop2.6.0.jar:/opt/spark-1.5.1-bin-hadoop2.6/lib/datanucleus-rdbms-3.2.9.jar:/opt/spark-1.5.1-bin-hadoop2.6/lib/datanucleus-core-3.2.10.jar:/opt/spark-1.5.1-bin-hadoop2.6/lib/datanucleus-api-jdo-3.2.6.jar -Xms1g -Xmx1g org.apache.spark.deploy.master.Master --ip spark-master --port 7077 --webui-port 8080
|
|
========================================
|
|
15/10/27 21:25:05 INFO Master: Registered signal handlers for [TERM, HUP, INT]
|
|
15/10/27 21:25:05 INFO SecurityManager: Changing view acls to: root
|
|
15/10/27 21:25:05 INFO SecurityManager: Changing modify acls to: root
|
|
15/10/27 21:25:05 INFO SecurityManager: SecurityManager: authentication disabled; ui acls disabled; users with view permissions: Set(root); users with modify permissions: Set(root)
|
|
15/10/27 21:25:06 INFO Slf4jLogger: Slf4jLogger started
|
|
15/10/27 21:25:06 INFO Remoting: Starting remoting
|
|
15/10/27 21:25:06 INFO Remoting: Remoting started; listening on addresses :[akka.tcp://sparkMaster@spark-master:7077]
|
|
15/10/27 21:25:06 INFO Utils: Successfully started service 'sparkMaster' on port 7077.
|
|
15/10/27 21:25:07 INFO Master: Starting Spark master at spark://spark-master:7077
|
|
15/10/27 21:25:07 INFO Master: Running Spark version 1.5.1
|
|
15/10/27 21:25:07 INFO Utils: Successfully started service 'MasterUI' on port 8080.
|
|
15/10/27 21:25:07 INFO MasterWebUI: Started MasterWebUI at http://spark-master:8080
|
|
15/10/27 21:25:07 INFO Utils: Successfully started service on port 6066.
|
|
15/10/27 21:25:07 INFO StandaloneRestServer: Started REST server for submitting applications on port 6066
|
|
15/10/27 21:25:07 INFO Master: I have been elected leader! New state: ALIVE
|
|
```
|
|
|
|
After you know the master is running, you can use the (cluster
|
|
proxy)[../../docs/user-guide/accessing-the-cluster.md#using-kubectl-proxy] to
|
|
connect to the Spark WebUI:
|
|
|
|
```console
|
|
kubectl proxy --port=8001
|
|
```
|
|
|
|
At which point the UI will be available at
|
|
http://localhost:8001/api/v1/proxy/namespaces/default/services/spark-webui/
|
|
|
|
## Step Two: Start your Spark workers
|
|
|
|
The Spark workers do the heavy lifting in a Spark cluster. They
|
|
provide execution resources and data cache capabilities for your
|
|
program.
|
|
|
|
The Spark workers need the Master service to be running.
|
|
|
|
Use the [`examples/spark/spark-worker-controller.yaml`](spark-worker-controller.yaml) file to create a
|
|
[replication controller](../../docs/user-guide/replication-controller.md) that manages the worker pods.
|
|
|
|
```console
|
|
$ kubectl create -f examples/spark/spark-worker-controller.yaml
|
|
```
|
|
|
|
### Check to see if the workers are running
|
|
|
|
If you launched the Spark WebUI, your workers should just appear in the UI when
|
|
they're ready. (It may take a little bit to pull the images and launch the
|
|
pods.) You can also interrogate the status in the following way:
|
|
|
|
```console
|
|
$ kubectl get pods
|
|
NAME READY STATUS RESTARTS AGE
|
|
spark-master-controller-5u0q5 1/1 Running 0 25m
|
|
spark-worker-controller-e8otp 1/1 Running 0 6m
|
|
spark-worker-controller-fiivl 1/1 Running 0 6m
|
|
spark-worker-controller-ytc7o 1/1 Running 0 6m
|
|
|
|
$ kubectl logs spark-master-controller-5u0q5
|
|
[...]
|
|
15/10/26 18:20:14 INFO Master: Registering worker 10.244.1.13:53567 with 2 cores, 6.3 GB RAM
|
|
15/10/26 18:20:14 INFO Master: Registering worker 10.244.2.7:46195 with 2 cores, 6.3 GB RAM
|
|
15/10/26 18:20:14 INFO Master: Registering worker 10.244.3.8:39926 with 2 cores, 6.3 GB RAM
|
|
```
|
|
|
|
Assuming you still have the `kubectl proxy` running from the previous section,
|
|
you should now see the workers in the UI as well. *Note:* The UI will have links
|
|
to worker Web UIs. The worker UI links do not work (the links will attempt to
|
|
connect to cluster IPs, which Kubernetes won't proxy automatically).
|
|
|
|
## Step Three: Start your Spark driver to launch jobs on your Spark cluster
|
|
|
|
The Spark driver is used to launch jobs into Spark cluster. You can read more about it in
|
|
[Spark architecture](https://spark.apache.org/docs/latest/cluster-overview.html).
|
|
|
|
```console
|
|
$ kubectl create -f examples/spark/spark-driver-controller.yaml
|
|
replicationcontrollers/spark-driver-controller
|
|
```
|
|
|
|
The Spark driver needs the Master service to be running.
|
|
|
|
### Check to see if the driver is running
|
|
|
|
```console
|
|
$ kubectl get pods -lcomponent=spark-driver
|
|
NAME READY STATUS RESTARTS AGE
|
|
spark-driver-controller-vwb9c 1/1 Running 0 1m
|
|
```
|
|
|
|
## Step Four: Do something with the cluster
|
|
|
|
Use the kubectl exec to connect to Spark driver and run a pipeline.
|
|
|
|
```console
|
|
$ kubectl exec spark-driver-controller-vwb9c -it pyspark
|
|
Python 2.7.9 (default, Mar 1 2015, 12:57:24)
|
|
[GCC 4.9.2] on linux2
|
|
Type "help", "copyright", "credits" or "license" for more information.
|
|
Welcome to
|
|
____ __
|
|
/ __/__ ___ _____/ /__
|
|
_\ \/ _ \/ _ `/ __/ '_/
|
|
/__ / .__/\_,_/_/ /_/\_\ version 1.5.1
|
|
/_/
|
|
|
|
Using Python version 2.7.9 (default, Mar 1 2015 12:57:24)
|
|
SparkContext available as sc, HiveContext available as sqlContext.
|
|
>>> sc.textFile("gs://dataflow-samples/shakespeare/*").map(lambda s: len(s.split())).sum()
|
|
939193
|
|
```
|
|
|
|
Congratulations, you just counted all of the words in all of the plays of
|
|
Shakespeare.
|
|
|
|
## Result
|
|
|
|
You now have services and replication controllers for the Spark master, Spark
|
|
workers and Spark driver. You can take this example to the next step and start
|
|
using the Apache Spark cluster you just created, see
|
|
[Spark documentation](https://spark.apache.org/documentation.html) for more
|
|
information.
|
|
|
|
## tl;dr
|
|
|
|
```console
|
|
kubectl create -f examples/spark
|
|
```
|
|
|
|
After it's setup:
|
|
|
|
```console
|
|
kubectl get pods # Make sure everything is running
|
|
kubectl proxy --port=8001 # Start an application proxy, if you want to see the Spark WebUI
|
|
kubectl get pods -lcomponent=spark-driver # Get the driver pod to interact with.
|
|
```
|
|
|
|
<!-- BEGIN MUNGE: GENERATED_ANALYTICS -->
|
|
[]()
|
|
<!-- END MUNGE: GENERATED_ANALYTICS -->
|