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 <rxin@databricks.com<mailto:rxin@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.
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