So you are living the dream of using HDFS as a database? ;) On 15.09.2014, at 13:50, andy petrella <andy.petre...@gmail.com> wrote:
> I'm using Parquet in ADAM, and I can say that it works pretty fine! > Enjoy ;-) > > aℕdy ℙetrella > about.me/noootsab > > > > On Mon, Sep 15, 2014 at 1:41 PM, Marius Soutier <mps....@gmail.com> wrote: > Thank you guys, I’ll try Parquet and if that’s not quick enough I’ll go the > usual route with either read-only or normal database. > > On 13.09.2014, at 12:45, andy petrella <andy.petre...@gmail.com> wrote: > >> however, the cache is not guaranteed to remain, if other jobs are launched >> in the cluster and require more memory than what's left in the overall >> caching memory, previous RDDs will be discarded. >> >> Using an off heap cache like tachyon as a dump repo can help. >> >> In general, I'd say that using a persistent sink (like Cassandra for >> instance) is best. >> >> my .2¢ >> >> >> aℕdy ℙetrella >> about.me/noootsab >> >> >> >> On Sat, Sep 13, 2014 at 9:20 AM, Mayur Rustagi <mayur.rust...@gmail.com> >> wrote: >> You can cache data in memory & query it using Spark Job Server. >> Most folks dump data down to a queue/db for retrieval >> You can batch up data & store into parquet partitions as well. & query it >> using another SparkSQL shell, JDBC driver in SparkSQL is part 1.1 i >> believe. >> -- >> Regards, >> Mayur Rustagi >> Ph: +1 (760) 203 3257 >> http://www.sigmoidanalytics.com >> @mayur_rustagi >> >> >> On Fri, Sep 12, 2014 at 2:54 PM, Marius Soutier <mps....@gmail.com> wrote: >> >> Hi there, >> >> I’m pretty new to Spark, and so far I’ve written my jobs the same way I >> wrote Scalding jobs - one-off, read data from HDFS, count words, write >> counts back to HDFS. >> >> Now I want to display these counts in a dashboard. Since Spark allows to >> cache RDDs in-memory and you have to explicitly terminate your app (and >> there’s even a new JDBC server in 1.1), I’m assuming it’s possible to keep >> an app running indefinitely and query an in-memory RDD from the outside (via >> SparkSQL for example). >> >> Is this how others are using Spark? Or are you just dumping job results into >> message queues or databases? >> >> >> Thanks >> - Marius >> >> >> --------------------------------------------------------------------- >> To unsubscribe, e-mail: user-unsubscr...@spark.apache.org >> For additional commands, e-mail: user-h...@spark.apache.org >> >> >> >> > >
