Hi, I have just posted a Blog on this: https://www.linkedin.com/pulse/combining-druid-spark-interactive-flexible-analytics-scale-butani
regards, Harish Butani. On Tue, Sep 1, 2015 at 11:46 PM, Paolo Platter <paolo.plat...@agilelab.it> wrote: > Fantastic!!! I will look into that and I hope to contribute > > Paolo > > Inviata dal mio Windows Phone > ------------------------------ > Da: Harish Butani <rhbutani.sp...@gmail.com> > Inviato: 02/09/2015 06:04 > A: user <user@spark.apache.org> > Oggetto: Spark + Druid > > Hi, > > I am working on the Spark Druid Package: > https://github.com/SparklineData/spark-druid-olap. > For scenarios where a 'raw event' dataset is being indexed in Druid it > enables you to write your Logical Plans(queries/dataflows) against the 'raw > event' dataset and it rewrites parts of the plan to execute as a Druid > Query. In Spark the configuration of a Druid DataSource is somewhat like > configuring an OLAP index in a traditional DB. Early results show > significant speedup of pushing slice and dice queries to Druid. > > It comprises of a Druid DataSource that wraps the 'raw event' dataset and > has knowledge of the Druid Index; and a DruidPlanner which is a set of plan > rewrite strategies to convert Aggregation queries into a Plan having a > DruidRDD. > > Here > <https://github.com/SparklineData/spark-druid-olap/blob/master/docs/SparkDruid.pdf> > is > a detailed design document, which also describes a benchmark of > representative queries on the TPCH dataset. > > Looking for folks who would be willing to try this out and/or contribute. > > regards, > Harish Butani. >
