 <p>The plus: it's a super easy way to distribute the work that needs to be done.</p> <p>The minus: due to the way that Hadoop recovers from failures, you need to be very careful about managing what is and isn't run (which you can definitely do, it's just something to watch out for). If a reduce fails, for example, then all of the map jobs that feed that partition must also be rerun. Obviously this would most likely be a no-reducer job, but this is still true of mappers...what happens if half of the calls run, then the job fails, so it is rescheduled?</p> <p>You could use some sort of high-throughput system to manage the calls that are actually made or somesuch. But it definitely can be appropriately used for this.</p>