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NAME READY STATUS RESTARTS AGE
zeppelin-controller-ja09s 1/1 Running 0 53s
```
## Step Five: Do something with the cluster
Now you have two choices, depending on your predilections. You can do something
graphical with the Spark cluster, or you can stay in the CLI.
For both choices, we will be working with this Python snippet:
```python
from math import sqrt; from itertools import count, islice
def isprime(n):
return n > 1 and all(n%i for i in islice(count(2), int(sqrt(n)-1)))
nums = sc.parallelize(xrange(10000000))
print nums.filter(isprime).count()
```
### Do something fast with pyspark!
Simply copy and paste the python snippet into pyspark from within the zeppelin pod:
```console
$ kubectl exec zeppelin-controller-ja09s -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.
>>> from math import sqrt; from itertools import count, islice
>>>
>>> def isprime(n):
... return n > 1 and all(n%i for i in islice(count(2), int(sqrt(n)-1)))
...
>>> nums = sc.parallelize(xrange(10000000))
>>> print nums.filter(isprime).count()
664579
```
Congratulations, you now know how many prime numbers there are within the first 10 million numbers!
### Do something graphical and shiny!
Creating the Zeppelin service should have yielded you a Loadbalancer endpoint:
```console
$ kubectl get svc zeppelin -o wide
NAME CLUSTER-IP EXTERNAL-IP PORT(S) AGE SELECTOR
zeppelin 10.0.154.1 a596f143884da11e6839506c114532b5-121893930.us-east-1.elb.amazonaws.com 80/TCP 3m component=zeppelin
```
If your Kubernetes cluster does not have a Loadbalancer integration, then we will have to use port forwarding.
Take the Zeppelin pod from before and port-forward the WebUI port:
```console
kubectl port-forward zeppelin-controller-ja09s 8080:8080
```
This forwards `localhost` 8080 to container port 8080. You can then find
Zeppelin at [http://localhost:8080/](http://localhost:8080/).
Once you've loaded up the Zeppelin UI, create a "New Notebook". In there we will paste our python snippet, but we need to add a `%pyspark` hint for Zeppelin to understand it:
```
%pyspark
from math import sqrt; from itertools import count, islice
def isprime(n):
return n > 1 and all(n%i for i in islice(count(2), int(sqrt(n)-1)))
nums = sc.parallelize(xrange(10000000))
print nums.filter(isprime).count()
```
After pasting in our code, press shift+enter or click the play icon to the right of our snippet. The Spark job will run and once again we'll have our result!
## 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 ns spark-cluster