Idiomatic way to use akka stream Source within Spark

[Kyrylo Stokoz]

Hi All,

I`m trying to figure out how one should use Sources within Spark Jobs keeping all benefits of Spark.

Consider following snippet:

val items: Seq[String] = Seq("a", "b", "c")
sparkSession.sparkContext.parallelize(items, 10).flatMap { item =>
  val subItems: Source[String, _] = f(item)
  // (1)
  ???
}.map { subItem =>
  f1(subItem)
}.reduce(_ + _)

There is this project https://github.com/lloydmeta/sparkka-streams which tries to bridge akka streams and Spark Streaming.

I also created an IteratorSinkStage which materialized into Iterator similar as InputStreamSinkStage which is materialized into InputStream, but i`m not sure if this is best solution for this problem.

What would be the best way to work with akka Source within Spark environment?

Regards,

Kyrylo

 

[Akka Team]

I think this question has a higher chance of getting an answer if asked in the Spark community/mailing list. 

The linked project seems to be more about feeding data from Akka Streams into spark than running Akka Streams inside of Spark.

-- 

Johan

Akka Team

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