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
