hi all,
got a vagrant image with spark notebook, spark, accumulo, and hadoop all
running. from notebook I can manually create a scanner and pull test data from
a table I created using one of the accumulo examples:
val instanceNameS = "accumulo"
val zooServersS = "localhost:2181"
val instance: Instance = new ZooKeeperInstance(instanceNameS, zooServersS)
val connector: Connector = instance.getConnector( "root", new
PasswordToken("password"))
val auths = new Authorizations("exampleVis")
val scanner = connector.createScanner("batchtest1", auths)
scanner.setRange(new Range("row_0000000000", "row_0000000010"))
for(entry: Entry[Key, Value] <- scanner) {
println(entry.getKey + " is " + entry.getValue)
}
will give the first ten rows of table data. when I try to create the RDD thusly:
val rdd2 =
sparkContext.newAPIHadoopRDD (
new Configuration(),
classOf[org.apache.accumulo.core.client.mapreduce.AccumuloInputFormat],
classOf[org.apache.accumulo.core.data.Key],
classOf[org.apache.accumulo.core.data.Value]
)
I get an RDD returned to me that I can't do much with due to the following
error:
java.io.IOException: Input info has not been set. at
org.apache.accumulo.core.client.mapreduce.lib.impl.InputConfigurator.validateOptions(InputConfigurator.java:630)
at
org.apache.accumulo.core.client.mapreduce.AbstractInputFormat.validateOptions(AbstractInputFormat.java:343)
at
org.apache.accumulo.core.client.mapreduce.AbstractInputFormat.getSplits(AbstractInputFormat.java:538)
at org.apache.spark.rdd.NewHadoopRDD.getPartitions(NewHadoopRDD.scala:98) at
org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:222) at
org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:220) at
scala.Option.getOrElse(Option.scala:120) at
org.apache.spark.rdd.RDD.partitions(RDD.scala:220) at
org.apache.spark.SparkContext.runJob(SparkContext.scala:1367) at
org.apache.spark.rdd.RDD.count(RDD.scala:927)
which totally makes sense in light of the fact that I haven't specified any
parameters as to which table to connect with, what the auths are, etc.
so my question is: what do I need to do from here to get those first ten rows
of table data into my RDD?
DAVID HOLIDAY
Software Engineer
760 607 3300 | Office
312 758 8385 | Mobile
dav...@annaisystems.com<mailto:broo...@annaisystems.com>
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On Mar 19, 2015, at 11:25 AM, David Holiday
<dav...@annaisystems.com<mailto:dav...@annaisystems.com>> wrote:
kk - I'll put something together and get back to you with more :-)
DAVID HOLIDAY
Software Engineer
760 607 3300 | Office
312 758 8385 | Mobile
dav...@annaisystems.com<mailto:broo...@annaisystems.com>
<GetFileAttachment.jpg>
www.AnnaiSystems.com<http://www.annaisystems.com/>
On Mar 19, 2015, at 10:59 AM, Irfan Ahmad
<ir...@cloudphysics.com<mailto:ir...@cloudphysics.com>> wrote:
Once you setup spark-notebook, it'll handle the submits for interactive work.
Non-interactive is not handled by it. For that spark-kernel could be used.
Give it a shot ... it only takes 5 minutes to get it running in local-mode.
Irfan Ahmad
CTO | Co-Founder | CloudPhysics<http://www.cloudphysics.com/>
Best of VMworld Finalist
Best Cloud Management Award
NetworkWorld 10 Startups to Watch
EMA Most Notable Vendor
On Thu, Mar 19, 2015 at 9:51 AM, David Holiday
<dav...@annaisystems.com<mailto:dav...@annaisystems.com>> wrote:
hi all - thx for the alacritous replies! so regarding how to get things from
notebook to spark and back, am I correct that spark-submit is the way to go?
DAVID HOLIDAY
Software Engineer
760 607 3300<tel:760%20607%203300> | Office
312 758 8385<tel:312%20758%208385> | Mobile
dav...@annaisystems.com<mailto:broo...@annaisystems.com>
<GetFileAttachment.jpg>
www.AnnaiSystems.com<http://www.annaisystems.com/>
On Mar 19, 2015, at 1:14 AM, Paolo Platter
<paolo.plat...@agilelab.it<mailto:paolo.plat...@agilelab.it>> wrote:
Yes, I would suggest spark-notebook too.
It's very simple to setup and it's growing pretty fast.
Paolo
Inviata dal mio Windows Phone
________________________________
Da: Irfan Ahmad<mailto:ir...@cloudphysics.com>
Inviato: 19/03/2015 04:05
A: davidh<mailto:dav...@annaisystems.com>
Cc: user@spark.apache.org<mailto:user@spark.apache.org>
Oggetto: Re: iPython Notebook + Spark + Accumulo -- best practice?
I forgot to mention that there is also Zeppelin and jove-notebook but I haven't
got any experience with those yet.
Irfan Ahmad
CTO | Co-Founder | CloudPhysics<http://www.cloudphysics.com/>
Best of VMworld Finalist
Best Cloud Management Award
NetworkWorld 10 Startups to Watch
EMA Most Notable Vendor
On Wed, Mar 18, 2015 at 8:01 PM, Irfan Ahmad
<ir...@cloudphysics.com<mailto:ir...@cloudphysics.com>> wrote:
Hi David,
W00t indeed and great questions. On the notebook front, there are two options
depending on what you are looking for. You can either go with iPython 3 with
Spark-kernel as a backend or you can use spark-notebook. Both have interesting
tradeoffs.
If you have looking for a single notebook platform for your data scientists
that has R, Python as well as a Spark Shell, you'll likely want to go with
iPython + Spark-kernel. Downsides with the spark-kernel project are that data
visualization isn't quite there yet, early days for documentation and
blogs/etc. Upside is that R and Python work beautifully and that the ipython
committers are super-helpful.
If you are OK with a primarily spark/scala experience, then I suggest you with
spark-notebook. Upsides are that the project is a little further along,
visualization support is better than spark-kernel (though not as good as
iPython with Python) and the committer is awesome with help. Downside is that
you won't get R and Python.
FWIW: I'm using both at the moment!
Hope that helps.
Irfan Ahmad
CTO | Co-Founder | CloudPhysics<http://www.cloudphysics.com/>
Best of VMworld Finalist
Best Cloud Management Award
NetworkWorld 10 Startups to Watch
EMA Most Notable Vendor
On Wed, Mar 18, 2015 at 5:45 PM, davidh
<dav...@annaisystems.com<mailto:dav...@annaisystems.com>> wrote:
hi all, I've been DDGing, Stack Overflowing, Twittering, RTFMing, and
scanning through this archive with only moderate success. in other words --
my way of saying sorry if this is answered somewhere obvious and I missed it
:-)
i've been tasked with figuring out how to connect Notebook, Spark, and
Accumulo together. The end user will do her work via notebook. thus far,
I've successfully setup a Vagrant image containing Spark, Accumulo, and
Hadoop. I was able to use some of the Accumulo example code to create a
table populated with data, create a simple program in scala that, when fired
off to Spark via spark-submit, connects to accumulo and prints the first ten
rows of data in the table. so w00t on that - but now I'm left with more
questions:
1) I'm still stuck on what's considered 'best practice' in terms of hooking
all this together. Let's say Sally, a user, wants to do some analytic work
on her data. She pecks the appropriate commands into notebook and fires them
off. how does this get wired together on the back end? Do I, from notebook,
use spark-submit to send a job to spark and let spark worry about hooking
into accumulo or is it preferable to create some kind of open stream between
the two?
2) if I want to extend spark's api, do I need to first submit an endless job
via spark-submit that does something like what this gentleman describes
<http://blog.madhukaraphatak.com/extending-spark-api> ? is there an
alternative (other than refactoring spark's source) that doesn't involve
extending the api via a job submission?
ultimately what I'm looking for help locating docs, blogs, etc that may shed
some light on this.
t/y in advance!
d
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