>From a quick look at this link - http://accumulo.apache.org/1.6/accumulo_user_manual.html#_mapreduce - it seems you need to call some static methods on AccumuloInputFormat in order to set the auth, table, and range settings. Try setting these config options first and then call newAPIHadoopRDD?
On Thu, Mar 26, 2015 at 2:34 AM, David Holiday <dav...@annaisystems.com> wrote: > hi Irfan, > > thanks for getting back to me - i'll try the accumulo list to be sure. > what is the normal use case for spark though? I'm surprised that hooking it > into something as common and popular as accumulo isn't more of an every-day > task. > > DAVID HOLIDAY > Software Engineer > 760 607 3300 | Office > 312 758 8385 | Mobile > dav...@annaisystems.com <broo...@annaisystems.com> > > > > www.AnnaiSystems.com > > On Mar 25, 2015, at 5:27 PM, Irfan Ahmad <ir...@cloudphysics.com> wrote: > > Hmmm.... this seems very accumulo-specific, doesn't it? Not sure how to > help with that. > > > *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 Tue, Mar 24, 2015 at 4:09 PM, David Holiday <dav...@annaisystems.com> > wrote: > >> 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 <broo...@annaisystems.com> >> >> >> <GetFileAttachment.jpg> >> www.AnnaiSystems.com <http://www.annaisystems.com/> >> >> On Mar 19, 2015, at 11:25 AM, David Holiday <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 <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> >> 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> >> 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 | Office >>> 312 758 8385 | Mobile >>> dav...@annaisystems.com <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> >>> 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 <ir...@cloudphysics.com> >>> Inviato: 19/03/2015 04:05 >>> A: davidh <dav...@annaisystems.com> >>> Cc: 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> >>> 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> >>>> 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 >>>>> >>>>> >>>>> >>>>> -- >>>>> View this message in context: >>>>> http://apache-spark-user-list.1001560.n3.nabble.com/iPython-Notebook-Spark-Accumulo-best-practice-tp22137.html >>>>> Sent from the Apache Spark User List mailing list archive at >>>>> Nabble.com <http://nabble.com/>. >>>>> >>>>> --------------------------------------------------------------------- >>>>> To unsubscribe, e-mail: user-unsubscr...@spark.apache.org >>>>> For additional commands, e-mail: user-h...@spark.apache.org >>>>> >>>>> >>>> >>> >>> >> >> >> > >
