I'm not very sure for CDH 5.3, but now Zeppelin works for Spark 1.2 as spark-repl has been published in Spark 1.2.1 Please try again!
On Fri Feb 13 2015 at 3:55:19 PM Su She <suhsheka...@gmail.com> wrote: > Thanks Kevin for the link, I have had issues trying to install zeppelin as > I believe it is not yet supported for CDH 5.3, and Spark 1.2. Please > correct me if I am mistaken. > > On Thu, Feb 12, 2015 at 7:33 PM, Kevin (Sangwoo) Kim <kevin...@apache.org> > wrote: > >> Apache Zeppelin also has a scheduler and then you can reload your chart >> periodically, >> Check it out: >> http://zeppelin.incubator.apache.org/docs/tutorial/tutorial.html >> >> >> >> >> On Fri Feb 13 2015 at 7:29:00 AM Silvio Fiorito < >> silvio.fior...@granturing.com> wrote: >> >>> One method I’ve used is to publish each batch to a message bus or >>> queue with a custom UI listening on the other end, displaying the results >>> in d3.js or some other app. As far as I’m aware there isn’t a tool that >>> will directly take a DStream. >>> >>> Spark Notebook seems to have some support for updating graphs >>> periodically. I haven’t used it myself yet so not sure how well it works. >>> See here: https://github.com/andypetrella/spark-notebook >>> >>> From: Su She >>> Date: Thursday, February 12, 2015 at 1:55 AM >>> To: Felix C >>> Cc: Kelvin Chu, "user@spark.apache.org" >>> >>> Subject: Re: Can spark job server be used to visualize streaming data? >>> >>> Hello Felix, >>> >>> I am already streaming in very simple data using Kafka (few messages / >>> second, each record only has 3 columns...really simple, but looking to >>> scale once I connect everything). I am processing it in Spark Streaming and >>> am currently writing word counts to hdfs. So the part where I am confused >>> is... >>> >>> Kafka Publishes Data -> Kafka Consumer/Spark Streaming Receives Data -> >>> Spark Word Count -> *How do I visualize?* >>> >>> is there a viz tool that I can set up to visualize JavaPairDStreams? >>> or do I have to write to hbase/hdfs first? >>> >>> Thanks! >>> >>> On Wed, Feb 11, 2015 at 10:39 PM, Felix C <felixcheun...@hotmail.com> >>> wrote: >>> >>>> What kind of data do you have? Kafka is a popular source to use with >>>> spark streaming. >>>> But, spark streaming also support reading from a file. Its called basic >>>> source >>>> >>>> https://spark.apache.org/docs/latest/streaming-programming-guide.html#input-dstreams-and-receivers >>>> >>>> --- Original Message --- >>>> >>>> From: "Su She" <suhsheka...@gmail.com> >>>> Sent: February 11, 2015 10:23 AM >>>> To: "Felix C" <felixcheun...@hotmail.com> >>>> Cc: "Kelvin Chu" <2dot7kel...@gmail.com>, user@spark.apache.org >>>> Subject: Re: Can spark job server be used to visualize streaming data? >>>> >>>> Thank you Felix and Kelvin. I think I'll def be using the k-means >>>> tools in mlib. >>>> >>>> It seems the best way to stream data is by storing in hbase and then >>>> using an api in my viz to extract data? Does anyone have any thoughts on >>>> this? >>>> >>>> Thanks! >>>> >>>> >>>> On Tue, Feb 10, 2015 at 11:45 PM, Felix C <felixcheun...@hotmail.com> >>>> wrote: >>>> >>>> Checkout >>>> >>>> https://databricks.com/blog/2015/01/28/introducing-streaming-k-means-in-spark-1-2.html >>>> >>>> In there are links to how that is done. >>>> >>>> >>>> --- Original Message --- >>>> >>>> From: "Kelvin Chu" <2dot7kel...@gmail.com> >>>> Sent: February 10, 2015 12:48 PM >>>> To: "Su She" <suhsheka...@gmail.com> >>>> Cc: user@spark.apache.org >>>> Subject: Re: Can spark job server be used to visualize streaming data? >>>> >>>> Hi Su, >>>> >>>> Out of the box, no. But, I know people integrate it with Spark >>>> Streaming to do real-time visualization. It will take some work though. >>>> >>>> Kelvin >>>> >>>> On Mon, Feb 9, 2015 at 5:04 PM, Su She <suhsheka...@gmail.com> wrote: >>>> >>>> Hello Everyone, >>>> >>>> I was reading this blog post: >>>> http://homes.esat.kuleuven.be/~bioiuser/blog/a-d3-visualisation-from-spark-as-a-service/ >>>> >>>> and was wondering if this approach can be taken to visualize >>>> streaming data...not just historical data? >>>> >>>> Thank you! >>>> >>>> -Suh >>>> >>>> >>>> >>>> >>> >
