I am afraid not. The whole point of Spark Streaming is to make it easy to
do complicated processing on streaming data while interoperating with core
Spark, MLlib, SQL without the operational overheads of maintain 4 different
systems. As a slight cost of achieving that unification, there maybe some
Hi guys.
Is there a more lightweight way of stream processing with Spark? What we
want is a simpler way, preferably with no scheduling, which just streams
the data to destinations multiple.
We extensively use Spark Core, SQL, Streaming, GraphX, so it's our main
tool and don't want to add new
