Close. the mapPartitions call doesn't need to do anything at all to the
iter.
mapPartitions { iter =>
SomeDb.conn.init
iter
}
On Fri, Jun 12, 2015 at 3:55 PM, algermissen1971 <algermissen1...@icloud.com
> wrote:
> Cody,
>
> On 12 Jun 2015, at 17:26, Cody Koeninger <c...@koeninger.org> wrote:
>
> > There are several database apis that use a thread local or singleton
> reference to a connection pool (we use ScalikeJDBC currently, but there are
> others).
> >
> > You can use mapPartitions earlier in the chain to make sure the
> connection pool is set up on that executor, then use it inside
> updateStateByKey
> >
>
> Thanks. You are saying I should just make an arbitrary use of the
> ‘connection’ to invoke the ‘lazy’. E.g. like this:
>
> object SomeDB {
>
> lazy val conn = new SomeDB( “some serializable config")
>
> }
>
>
> Then somewhere else:
>
> theTrackingEvents.map(toPairs).mapPartitions(iter => iter.map( pair => {
> SomeDb.conn.init
> pair
> }
> )).updateStateByKey[Session](myUpdateFunction _)
>
>
> An in myUpdateFunction
>
> def myUpdateFunction( …) {
>
> SomeDb.conn.store( … )
>
> }
>
>
> Correct?
>
> Jan
>
>
>
>
> > On Fri, Jun 12, 2015 at 10:07 AM, algermissen1971 <
> algermissen1...@icloud.com> wrote:
> > Hi,
> >
> > I have a scenario with spark streaming, where I need to write to a
> database from within updateStateByKey[1].
> >
> > That means that inside my update function I need a connection.
> >
> > I have so far understood that I should create a new (lazy) connection
> for every partition. But since I am not working in foreachRDD I wonder
> where I can iterate over the partitions.
> >
> > Should I use mapPartitions() somewhere up the chain?
> >
> > Jan
> >
> >
> >
> > [1] The use case being saving ‘done' sessions during web tracking.
> >
> >
> > ---------------------------------------------------------------------
> > To unsubscribe, e-mail: user-unsubscr...@spark.apache.org
> > For additional commands, e-mail: user-h...@spark.apache.org
> >
> >
>
>
