I'm doing a performance analysis for Spark on Mesos and I can see that the
Coarse-grained backend simply launches tasks in wave size of the amount of
cores available. But it seems Fine-grained mode the Mesos executor takes 1
core for itself (so -1 core per mesos slave). Shouldn't fine- and
coarse-g
I'm running a query from the BigDataBenchmark, query 1B to be precise.
When running this with Spark (1.3.1)+ mesos(0.21) in coarse grained mode
with 5 mesos slave, through a spark shell, all is well.
However rerunning the query a few times:
scala> sqlContext.sql("SELECT pageURL, pageRank FROM
Hi,
In the Spark UI, under “Show additional metrics”, there are two extra
metrics you can show
.1 Scheduler delay
.2 and Getting result time
When hovering “Scheduler Delay" it says (among other things):
…time to send task result from executor…
When hovering “Getting result time”:
Time that the
Hi,
Does anyone know of a Java/Scala library (not simply a HTTP library) for
interacting with Spark through its REST/HTTP API? My “problem” is that
interacting through REST induces a lot of work mapping the JSON to sensible
Spark/Scala objects.
So a simple example, I hope there is a library whi
I'm having the same problem, did you solve this?
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Hi all,
For my master thesis I will be characterising performance of two-level
schedulers like Mesos and after reading the paper:
https://www.cs.berkeley.edu/~alig/papers/mesos.pdf
where Spark is also introduced I am wondering how some experiments and
results came about.
If this is not the plac
Hi,
What do the mesos slave logs say? Usually this gives a clearcut error, they
are probably local on a slave node.
I'm not sure about your config, so I can;t pinpoint you to a specific path.
might look something like:
/???/mesos/slaves/20150213-092641-84118794-5050-14978-S0/frameworks/2015032
Well that are only the logs of the slaves on mesos level, I'm not sure from
your reply if you can ssh into a specific slave or not, if you can, you
should look at actual output of the application (spark in this case) on a
slave in e.g.
/tmp/mesos/slaves/20150322-040336-606645514-5050-2744-S1/fr