Re: using multiple dstreams together (spark streaming)
@TD: Doesn't transformWith need both of the DStreams to be of same slideDuration. [Spark Version: 1.3.1] -- View this message in context: http://apache-spark-user-list.1001560.n3.nabble.com/using-multiple-dstreams-together-spark-streaming-tp9947p24839.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
Re: using multiple dstreams together (spark streaming)
Thanks!
On Wed, Jul 16, 2014 at 6:34 PM, Tathagata Das tathagata.das1...@gmail.com
wrote:
Have you taken a look at DStream.transformWith( ... ) . That allows you
apply arbitrary transformation between RDDs (of the same timestamp) of two
different streams.
So you can do something like this.
2s-window-stream.transformWith(1s-window-stream, (rdd1: RDD[...], rdd2:
RDD[...]) = {
...
// return a new RDD
})
And streamingContext.transform() extends it to N DStreams. :)
Hope this helps!
TD
On Wed, Jul 16, 2014 at 10:42 AM, Walrus theCat walrusthe...@gmail.com
wrote:
hey at least it's something (thanks!) ... not sure what i'm going to do
if i can't find a solution (other than not use spark) as i really need
these capabilities. anyone got anything else?
On Wed, Jul 16, 2014 at 10:34 AM, Luis Ángel Vicente Sánchez
langel.gro...@gmail.com wrote:
hum... maybe consuming all streams at the same time with an actor that
would act as a new DStream source... but this is just a random idea... I
don't really know if that would be a good idea or even possible.
2014-07-16 18:30 GMT+01:00 Walrus theCat walrusthe...@gmail.com:
Yeah -- I tried the .union operation and it didn't work for that
reason. Surely there has to be a way to do this, as I imagine this is a
commonly desired goal in streaming applications?
On Wed, Jul 16, 2014 at 10:10 AM, Luis Ángel Vicente Sánchez
langel.gro...@gmail.com wrote:
I'm joining several kafka dstreams using the join operation but you
have the limitation that the duration of the batch has to be same,i.e. 1
second window for all dstreams... so it would not work for you.
2014-07-16 18:08 GMT+01:00 Walrus theCat walrusthe...@gmail.com:
Hi,
My application has multiple dstreams on the same inputstream:
dstream1 // 1 second window
dstream2 // 2 second window
dstream3 // 5 minute window
I want to write logic that deals with all three windows (e.g. when
the 1 second window differs from the 2 second window by some delta ...)
I've found some examples online (there's not much out there!), and I
can only see people transforming a single dstream. In conventional
spark,
we'd do this sort of thing with a cartesian on RDDs.
How can I deal with multiple Dstreams at once?
Thanks
using multiple dstreams together (spark streaming)
Hi, My application has multiple dstreams on the same inputstream: dstream1 // 1 second window dstream2 // 2 second window dstream3 // 5 minute window I want to write logic that deals with all three windows (e.g. when the 1 second window differs from the 2 second window by some delta ...) I've found some examples online (there's not much out there!), and I can only see people transforming a single dstream. In conventional spark, we'd do this sort of thing with a cartesian on RDDs. How can I deal with multiple Dstreams at once? Thanks
Re: using multiple dstreams together (spark streaming)
I'm joining several kafka dstreams using the join operation but you have the limitation that the duration of the batch has to be same,i.e. 1 second window for all dstreams... so it would not work for you. 2014-07-16 18:08 GMT+01:00 Walrus theCat walrusthe...@gmail.com: Hi, My application has multiple dstreams on the same inputstream: dstream1 // 1 second window dstream2 // 2 second window dstream3 // 5 minute window I want to write logic that deals with all three windows (e.g. when the 1 second window differs from the 2 second window by some delta ...) I've found some examples online (there's not much out there!), and I can only see people transforming a single dstream. In conventional spark, we'd do this sort of thing with a cartesian on RDDs. How can I deal with multiple Dstreams at once? Thanks
Re: using multiple dstreams together (spark streaming)
Yeah -- I tried the .union operation and it didn't work for that reason. Surely there has to be a way to do this, as I imagine this is a commonly desired goal in streaming applications? On Wed, Jul 16, 2014 at 10:10 AM, Luis Ángel Vicente Sánchez langel.gro...@gmail.com wrote: I'm joining several kafka dstreams using the join operation but you have the limitation that the duration of the batch has to be same,i.e. 1 second window for all dstreams... so it would not work for you. 2014-07-16 18:08 GMT+01:00 Walrus theCat walrusthe...@gmail.com: Hi, My application has multiple dstreams on the same inputstream: dstream1 // 1 second window dstream2 // 2 second window dstream3 // 5 minute window I want to write logic that deals with all three windows (e.g. when the 1 second window differs from the 2 second window by some delta ...) I've found some examples online (there's not much out there!), and I can only see people transforming a single dstream. In conventional spark, we'd do this sort of thing with a cartesian on RDDs. How can I deal with multiple Dstreams at once? Thanks
Re: using multiple dstreams together (spark streaming)
hum... maybe consuming all streams at the same time with an actor that would act as a new DStream source... but this is just a random idea... I don't really know if that would be a good idea or even possible. 2014-07-16 18:30 GMT+01:00 Walrus theCat walrusthe...@gmail.com: Yeah -- I tried the .union operation and it didn't work for that reason. Surely there has to be a way to do this, as I imagine this is a commonly desired goal in streaming applications? On Wed, Jul 16, 2014 at 10:10 AM, Luis Ángel Vicente Sánchez langel.gro...@gmail.com wrote: I'm joining several kafka dstreams using the join operation but you have the limitation that the duration of the batch has to be same,i.e. 1 second window for all dstreams... so it would not work for you. 2014-07-16 18:08 GMT+01:00 Walrus theCat walrusthe...@gmail.com: Hi, My application has multiple dstreams on the same inputstream: dstream1 // 1 second window dstream2 // 2 second window dstream3 // 5 minute window I want to write logic that deals with all three windows (e.g. when the 1 second window differs from the 2 second window by some delta ...) I've found some examples online (there's not much out there!), and I can only see people transforming a single dstream. In conventional spark, we'd do this sort of thing with a cartesian on RDDs. How can I deal with multiple Dstreams at once? Thanks
Re: using multiple dstreams together (spark streaming)
Or, if not, is there a way to do this in terms of a single dstream? Keep in mind that dstream1, dstream2, and dstream3 have already had transformations applied. I tried creating the dstreams by calling .window on the first one, but that ends up with me having ... 3 dstreams... which is the same problem. On Wed, Jul 16, 2014 at 10:30 AM, Walrus theCat walrusthe...@gmail.com wrote: Yeah -- I tried the .union operation and it didn't work for that reason. Surely there has to be a way to do this, as I imagine this is a commonly desired goal in streaming applications? On Wed, Jul 16, 2014 at 10:10 AM, Luis Ángel Vicente Sánchez langel.gro...@gmail.com wrote: I'm joining several kafka dstreams using the join operation but you have the limitation that the duration of the batch has to be same,i.e. 1 second window for all dstreams... so it would not work for you. 2014-07-16 18:08 GMT+01:00 Walrus theCat walrusthe...@gmail.com: Hi, My application has multiple dstreams on the same inputstream: dstream1 // 1 second window dstream2 // 2 second window dstream3 // 5 minute window I want to write logic that deals with all three windows (e.g. when the 1 second window differs from the 2 second window by some delta ...) I've found some examples online (there's not much out there!), and I can only see people transforming a single dstream. In conventional spark, we'd do this sort of thing with a cartesian on RDDs. How can I deal with multiple Dstreams at once? Thanks
Re: using multiple dstreams together (spark streaming)
hey at least it's something (thanks!) ... not sure what i'm going to do if i can't find a solution (other than not use spark) as i really need these capabilities. anyone got anything else? On Wed, Jul 16, 2014 at 10:34 AM, Luis Ángel Vicente Sánchez langel.gro...@gmail.com wrote: hum... maybe consuming all streams at the same time with an actor that would act as a new DStream source... but this is just a random idea... I don't really know if that would be a good idea or even possible. 2014-07-16 18:30 GMT+01:00 Walrus theCat walrusthe...@gmail.com: Yeah -- I tried the .union operation and it didn't work for that reason. Surely there has to be a way to do this, as I imagine this is a commonly desired goal in streaming applications? On Wed, Jul 16, 2014 at 10:10 AM, Luis Ángel Vicente Sánchez langel.gro...@gmail.com wrote: I'm joining several kafka dstreams using the join operation but you have the limitation that the duration of the batch has to be same,i.e. 1 second window for all dstreams... so it would not work for you. 2014-07-16 18:08 GMT+01:00 Walrus theCat walrusthe...@gmail.com: Hi, My application has multiple dstreams on the same inputstream: dstream1 // 1 second window dstream2 // 2 second window dstream3 // 5 minute window I want to write logic that deals with all three windows (e.g. when the 1 second window differs from the 2 second window by some delta ...) I've found some examples online (there's not much out there!), and I can only see people transforming a single dstream. In conventional spark, we'd do this sort of thing with a cartesian on RDDs. How can I deal with multiple Dstreams at once? Thanks
Re: using multiple dstreams together (spark streaming)
Have you taken a look at DStream.transformWith( ... ) . That allows you
apply arbitrary transformation between RDDs (of the same timestamp) of two
different streams.
So you can do something like this.
2s-window-stream.transformWith(1s-window-stream, (rdd1: RDD[...], rdd2:
RDD[...]) = {
...
// return a new RDD
})
And streamingContext.transform() extends it to N DStreams. :)
Hope this helps!
TD
On Wed, Jul 16, 2014 at 10:42 AM, Walrus theCat walrusthe...@gmail.com
wrote:
hey at least it's something (thanks!) ... not sure what i'm going to do if
i can't find a solution (other than not use spark) as i really need these
capabilities. anyone got anything else?
On Wed, Jul 16, 2014 at 10:34 AM, Luis Ángel Vicente Sánchez
langel.gro...@gmail.com wrote:
hum... maybe consuming all streams at the same time with an actor that
would act as a new DStream source... but this is just a random idea... I
don't really know if that would be a good idea or even possible.
2014-07-16 18:30 GMT+01:00 Walrus theCat walrusthe...@gmail.com:
Yeah -- I tried the .union operation and it didn't work for that reason.
Surely there has to be a way to do this, as I imagine this is a commonly
desired goal in streaming applications?
On Wed, Jul 16, 2014 at 10:10 AM, Luis Ángel Vicente Sánchez
langel.gro...@gmail.com wrote:
I'm joining several kafka dstreams using the join operation but you
have the limitation that the duration of the batch has to be same,i.e. 1
second window for all dstreams... so it would not work for you.
2014-07-16 18:08 GMT+01:00 Walrus theCat walrusthe...@gmail.com:
Hi,
My application has multiple dstreams on the same inputstream:
dstream1 // 1 second window
dstream2 // 2 second window
dstream3 // 5 minute window
I want to write logic that deals with all three windows (e.g. when the
1 second window differs from the 2 second window by some delta ...)
I've found some examples online (there's not much out there!), and I
can only see people transforming a single dstream. In conventional spark,
we'd do this sort of thing with a cartesian on RDDs.
How can I deal with multiple Dstreams at once?
Thanks
