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.
>
>
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