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>
[cid:AE39C43E-3FF7-4C90-BCE4-9711C84C4CB8@cld.annailabs.com] 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 -- 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<mailto:user-unsubscr...@spark.apache.org> For additional commands, e-mail: user-h...@spark.apache.org<mailto:user-h...@spark.apache.org>