Hi,
thank you for your interest and welcome to Zeppelin community!
The simplest way to set these properties for Spark is thought Interpreter
properties.
In "Interpreters" menu pick one that is bided to you notebook (spark or
spark-local, or, create a new one) and set them w/ '+' sign. Interpreter
will be restarted automatically on 'save' of these settings.
This way the lazily auto-injected context `sc` will have all this
properties set for you on the first binded notebook run.
You are right, once configured SparkContext can not be changed, so for
different clusters the best way may be either to have different
interpreters (contexts) or if you are using awesome elasticsearch-hadoop
then something like this would do the job
```
import org.elasticsearch.spark._
import org.elasticsearch.hadoop.cfg.ConfigurationOptions
var esAddr = ""
out.saveToEs(Map(
ConfigurationOptions.ES_NODES -> esAddr,
ConfigurationOptions.ES_RESOURCE -> .... )
))
```
Alex.
On Sun, Sep 13, 2015 at 3:28 AM, Jeff Steinmetz <jeffrey.steinm...@gmail.com
> wrote:
> What is the approach to set custom properties dynamically for the conf
> within a notebook?
>
> I understand zeppelin already sets up a spark context for you. Once you
> have a SparkContext it can’t be changed.
>
> I may be missing something that the documentation doesn’t mention.
> Perhaps something to do with %spark
>
> Specifically, a native Scala elasticsearch spark source would look like:
>
> import org.apache.spark.SparkConf val conf = new
> SparkConf().setAppName(“sampleapp").setMaster(“local")
> conf.set("es.index.auto.create", "true”)
> conf.set("es.nodes", "192.168.51.50”)
> val sc = new SparkContext(conf)
>
> There may be times you may want to connect to a different IP for a
> different cluster.
>
