Hmm it will never be faster than SQL if you use SQL as an underlying storage. Spark is (currently) an in-memory batch engine for iterative machine learning workloads. It is not designed for interactive queries. Currently hive is going into the direction of interactive queries. Alternatives are Hbase on Phoenix or Impala.
> On 01 Dec 2015, at 21:58, Andrés Ivaldi <iaiva...@gmail.com> wrote: > > Yes, > The use case would be, > Have spark in a service (I didnt invertigate this yet), through api calls of > this service we perform some aggregations over data in SQL, We are already > doing this with an internal development > > Nothing complicated, for instance, a table with Product, Product Family, > cost, price, etc. Columns like Dimension and Measures, > > I want to Spark for query that table to perform a kind of rollup, with cost > as Measure and Prodcut, Product Family as Dimension > > Only 3 columns, it takes like 20s to perform that query and the aggregation, > the query directly to the database with a grouping at the columns takes like > 1s > > regards > > > >> On Tue, Dec 1, 2015 at 5:38 PM, Jörn Franke <jornfra...@gmail.com> wrote: >> can you elaborate more on the use case? >> >> > On 01 Dec 2015, at 20:51, Andrés Ivaldi <iaiva...@gmail.com> wrote: >> > >> > Hi, >> > >> > I'd like to use spark to perform some transformations over data stored >> > inSQL, but I need low Latency, I'm doing some test and I run into spark >> > context creation and data query over SQL takes too long time. >> > >> > Any idea for speed up the process? >> > >> > regards. >> > >> > -- >> > Ing. Ivaldi Andres > > > > -- > Ing. Ivaldi Andres
