I'd like to analyze a continuous stream of data (accessed over HTTP) using a MapReduce approach, so I've been looking into Apache Hadoop. Unfortunately, it appears that Hadoop expects to start a job with an input file of fixed size, rather than being able to hand off new data to consumers as it arrives. Is this actually the case, or am I missing something? Is there a different MapReduce tool that works with data being read in from an open socket? Scalability is an issue here, so I'd prefer to let the MapReducer handle the messy parallelization stuff.
I've played around with Cascading and was able to run a job on a static file accessed via HTTP, but this doesn't actually solve my problem. I could use curl as an intermediate step to dump the data somewhere on a Hadoop filesystem and write a watchdog to fire off a new job every time a new chunk of data is ready, but that's a dirty hack; there has to be some more elegant way to do this.