Re: Spark as a service
You're welcome. How did it go? *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 25, 2015 at 7:53 AM, Ashish Mukherjee ashish.mukher...@gmail.com wrote: Thank you On Tue, Mar 24, 2015 at 8:40 PM, Irfan Ahmad ir...@cloudphysics.com wrote: Also look at the spark-kernel and spark job server projects. Irfan On Mar 24, 2015 5:03 AM, Todd Nist tsind...@gmail.com wrote: Perhaps this project, https://github.com/calrissian/spark-jetty-server, could help with your requirements. On Tue, Mar 24, 2015 at 7:12 AM, Jeffrey Jedele jeffrey.jed...@gmail.com wrote: I don't think there's are general approach to that - the usecases are just to different. If you really need it, you probably will have to implement yourself in the driver of your application. PS: Make sure to use the reply to all button so that the mailing list is included in your reply. Otherwise only I will get your mail. Regards, Jeff 2015-03-24 12:01 GMT+01:00 Ashish Mukherjee ashish.mukher...@gmail.com : Hi Jeffrey, Thanks. Yes, this resolves the SQL problem. My bad - I was looking for something which would work for Spark Streaming and other Spark jobs too, not just SQL. Regards, Ashish On Tue, Mar 24, 2015 at 4:07 PM, Jeffrey Jedele jeffrey.jed...@gmail.com wrote: Hi Ashish, this might be what you're looking for: https://spark.apache.org/docs/latest/sql-programming-guide.html#running-the-thrift-jdbcodbc-server Regards, Jeff 2015-03-24 11:28 GMT+01:00 Ashish Mukherjee ashish.mukher...@gmail.com: Hello, As of now, if I have to execute a Spark job, I need to create a jar and deploy it. If I need to run a dynamically formed SQL from a Web application, is there any way of using SparkSQL in this manner? Perhaps, through a Web Service or something similar. Regards, Ashish
Re: iPython Notebook + Spark + Accumulo -- best practice?
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 = accumuloval zooServersS = localhost:2181val 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_00, row_10))
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
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
Re: Spark as a service
Also look at the spark-kernel and spark job server projects. Irfan On Mar 24, 2015 5:03 AM, Todd Nist tsind...@gmail.com wrote: Perhaps this project, https://github.com/calrissian/spark-jetty-server, could help with your requirements. On Tue, Mar 24, 2015 at 7:12 AM, Jeffrey Jedele jeffrey.jed...@gmail.com wrote: I don't think there's are general approach to that - the usecases are just to different. If you really need it, you probably will have to implement yourself in the driver of your application. PS: Make sure to use the reply to all button so that the mailing list is included in your reply. Otherwise only I will get your mail. Regards, Jeff 2015-03-24 12:01 GMT+01:00 Ashish Mukherjee ashish.mukher...@gmail.com: Hi Jeffrey, Thanks. Yes, this resolves the SQL problem. My bad - I was looking for something which would work for Spark Streaming and other Spark jobs too, not just SQL. Regards, Ashish On Tue, Mar 24, 2015 at 4:07 PM, Jeffrey Jedele jeffrey.jed...@gmail.com wrote: Hi Ashish, this might be what you're looking for: https://spark.apache.org/docs/latest/sql-programming-guide.html#running-the-thrift-jdbcodbc-server Regards, Jeff 2015-03-24 11:28 GMT+01:00 Ashish Mukherjee ashish.mukher...@gmail.com : Hello, As of now, if I have to execute a Spark job, I need to create a jar and deploy it. If I need to run a dynamically formed SQL from a Web application, is there any way of using SparkSQL in this manner? Perhaps, through a Web Service or something similar. Regards, Ashish
Re: Visualizing Spark Streaming data
Grafana allows pretty slick interactive use patterns, especially with graphite as the back-end. In a multi-user environment, why not have each user just build their own independent dashboards and name them under some simple naming convention? *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 Fri, Mar 20, 2015 at 1:06 AM, Harut Martirosyan harut.martiros...@gmail.com wrote: Hey Jeffrey. Thanks for reply. I already have something similar, I use Grafana and Graphite, and for simple metric streaming we've got all set-up right. My question is about interactive patterns. For instance, dynamically choose an event to monitor, dynamically choose group-by field or any sort of filter, then view results. This is easy when you have 1 user, but if you have team of analysts all specifying their own criteria, it becomes hard to manage them all. On 20 March 2015 at 12:02, Jeffrey Jedele jeffrey.jed...@gmail.com wrote: Hey Harut, I don't think there'll by any general practices as this part heavily depends on your environment, skills and what you want to achieve. If you don't have a general direction yet, I'd suggest you to have a look at Elasticsearch+Kibana. It's very easy to set up, powerful and therefore gets a lot of traction currently. Regards, Jeff 2015-03-20 8:43 GMT+01:00 Harut harut.martiros...@gmail.com: I'm trying to build a dashboard to visualize stream of events coming from mobile devices. For example, I have event called add_photo, from which I want to calculate trending tags for added photos for last x minutes. Then I'd like to aggregate that by country, etc. I've built the streaming part, which reads from Kafka, and calculates needed results and get appropriate RDDs, the question is now how to connect it to UI. Is there any general practices on how to pass parameters to spark from some custom built UI, how to organize data retrieval, what intermediate storages to use, etc. Thanks in advance. -- View this message in context: http://apache-spark-user-list.1001560.n3.nabble.com/Visualizing-Spark-Streaming-data-tp22160.html Sent from the Apache Spark User List mailing list archive at Nabble.com. - To unsubscribe, e-mail: user-unsubscr...@spark.apache.org For additional commands, e-mail: user-h...@spark.apache.org -- RGRDZ Harut
Re: iPython Notebook + Spark + Accumulo -- best practice?
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. - To unsubscribe, e-mail: user-unsubscr...@spark.apache.org For additional commands, e-mail: user-h...@spark.apache.org
Re: SQL with Spark Streaming
Got a 404 on that link: https://github.com/Intel-bigdata/spark-streamsql *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 11, 2015 at 6:41 AM, Jason Dai jason@gmail.com wrote: Yes, a previous prototype is available https://github.com/Intel-bigdata/spark-streamsql, and a talk is given at last year's Spark Summit ( http://spark-summit.org/2014/talk/streamsql-on-spark-manipulating-streams-by-sql-using-spark ) We are currently porting the prototype to use the latest DataFrame API, and will provide a stable version for people to try soon. Thabnks, -Jason On Wed, Mar 11, 2015 at 9:12 AM, Tobias Pfeiffer t...@preferred.jp wrote: Hi, On Wed, Mar 11, 2015 at 9:33 AM, Cheng, Hao hao.ch...@intel.com wrote: Intel has a prototype for doing this, SaiSai and Jason are the authors. Probably you can ask them for some materials. The github repository is here: https://github.com/intel-spark/stream-sql Also, what I did is writing a wrapper class SchemaDStream that internally holds a DStream[Row] and a DStream[StructType] (the latter having just one element in every RDD) and then allows to do - operations SchemaRDD = SchemaRDD using `rowStream.transformWith(schemaStream, ...)` - in particular you can register this stream's data as a table this way - and via a companion object with a method `fromSQL(sql: String): SchemaDStream` you can get a new stream from previously registered tables. However, you are limited to batch-internal operations, i.e., you can't aggregate across batches. I am not able to share the code at the moment, but will within the next months. It is not very advanced code, though, and should be easy to replicate. Also, I have no idea about the performance of transformWith Tobias
