Looking @ [1], it seems to recommend pull from multiple Kafka topics in order to parallelize data received from Kafka over multiple nodes. I notice in [2], however, that one of the createConsumer() functions takes a groupId. So am I understanding correctly that creating multiple DStreams with the same groupId allow data to be partitioned across many nodes on a single topic?

[1] http://spark.apache.org/docs/1.2.0/streaming-programming-guide.html#level-of-parallelism-in-data-receiving
[2] https://spark.apache.org/docs/1.2.0/api/scala/index.html#org.apache.spark.streaming.kafka.KafkaUtils$