Hi, In the spark docs <http://spark.apache.org/docs/latest/streaming-programming-guide.html#failure-of-a-worker-node> it mentions "However, output operations (like foreachRDD) have *at-least once* semantics, that is, the transformed data may get written to an external entity more than once in the event of a worker failure. "
I would like to setup a Kafka pipeline whereby I write my data to a single topic 1, then I continue to process using spark streaming and write the transformed results to topic2, and finally I read the results from topic 2. How do I configure the spark streaming so that I can maintain exactly once semantics when writing to topic 2? Thanks, Josh
