Hi guys, In my recent blog post (http://mandubian.com/2014/03/08/zpark-ml-nio-1/), I needed to have an InputDStream helper looking like NetworkInputDStream to be able to push my data into DStream in an async way. But I didn't want the remoting aspect as my data source runs locally and nowhere else. I didn't want my InputDStream to be considered as a NetworkInputDStream as they have a special management in DStream scheduler to be potentially remoted.
So I've implemented this LocalInputDStream that provides simple push with an receiver based on an actor, creating BlockRDD but ensures it won't be remoted: https://github.com/mandubian/zpark-ztream/blob/master/src/main/scala/LocalInputDStream.scala (the code is just a hack of NetworkInputDStream) and a instance of it: https://github.com/mandubian/zpark-ztream/blob/master/src/main/scala/ZparkInputDStream.scala Is it something useful for the spark-streaming project that I could contribute to the project (in a PR) or have I totally missed something that would do the same in current project code? Best regards Pascal
