Just curious... Why would you not store the processed results in regular relational database? Not sure what you meant by persist the appropriate RDDs. Did you mean output of your job will be RDDs?
On 24 October 2014 13:35, ankits <ankitso...@gmail.com> wrote: > I want to set up spark SQL to allow ad hoc querying over the last X days of > processed data, where the data is processed through spark. This would also > have to cache data (in memory only), so the approach I was thinking of was > to build a layer that persists the appropriate RDDs and stores them in > memory. > > I see spark sql allows ad hoc querying through JDBC though I have never > used > that before. Will using JDBC offer any advantages (e.g does it have built > in > support for caching?) over rolling my own solution for this use case? > > Thanks! > > > > -- > View this message in context: > http://apache-spark-user-list.1001560.n3.nabble.com/Is-SparkSQL-JDBC-server-a-good-approach-for-caching-tp17196.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 > >
