We’ve been making use of both. Fine-grain mode makes sense for more ad-hoc work loads, and coarse-grained for more job like loads on a common data set. My preference is the fine-grain mode in all cases, but the overhead associated with its startup and the possibility that an overloaded cluster would be starved for resources makes coarse grain mode a reality at the moment.
On Wednesday, 4 November 2015 5:24 AM, Reynold Xin <r...@databricks.com<mailto:r...@databricks.com>> wrote: If you are using Spark with Mesos fine grained mode, can you please respond to this email explaining why you use it over the coarse grained mode? Thanks.
