Hi Experts, We are trying to get a kafka stream ingested in Spark and expose the registered table over JDBC for querying. Here are some questions: 1. Spark Streaming supports single context per application right? If I have multiple customers and would like to create a kafka topic for each of them and 1 streaming context for every topic is this doable? As per the current spark documentation, http://spark.apache.org/docs/latest/streaming-programming-guide.html#initializing-streamingcontext I can have only 1 active streaming context at a time. Is there no way around that? The use case here is, if I am looking at a 5 min window, the window should have records for that customer only, which is possible only by having customer specific streaming context.
2. If I am able to create multiple contexts in this fashion, can I register them as temp tables in my application and expose them over JDBC. Going by https://forums.databricks.com/questions/1464/how-to-configure-thrift-server-to-use-a-custom-spa.html, looks like I can connect the thrift server to a single sparkSQL Context. Having multiple streaming contexts means I automatically have multiple SQL contexts? 3. Can I use SQLContext or do I need to have HiveContext in order to see the tables registered via Spark application through the JDBC? regards Sunita
