Has anyone used Spark Job Server on a "kerberized" cluster in YARN-Client
mode? When Job Server contacts the YARN resource manager, we see a "Cannot
impersonate root" error and am not sure what we have misconfigured.
Thanks.
_______
*Mike Wright*
Principal
Kerberos seems to be working otherwise ... for example, we're using it
successfully to control access to HDFS and it's linked to AD ... we're
using Ranger if that helps. I'm not a systems admin guy so this is really
not my area of expertise.
_______
*Mike Wright*
Thanks for the insight!
___
*Mike Wright*
Principal Architect, Software Engineering
S&P Capital IQ and SNL
434-951-7816 *p*
434-244-4466 *f*
540-470-0119 *m*
mwri...@snl.com
On Fri, Dec 11, 2015 at 2:38 PM, Michael Armbrust
wrote:
> The way that we do this is to have a
Somewhat related - What's the correct implementation when you have a single
cluster to support multiple jobs that are unrelated and NOT sharing data? I
was directed to figure out, via job server, to support "multiple contexts"
and explained that multiple contexts per JVM is not really supported. So
As part of our implementation, we are utilizing a full "Kerberized" cluster
built on the Hortonworks suite. We're using Job Server as the front end to
initiate short-run jobs directly from our client-facing product suite.
1) We believe we have configured the job server to start with the
appropriat
all at the end and writing them all at once.
I am using a groupBy against the filtered RDD the get the grouping I want,
but apparently this may not be the most efficient way, and it seems that
everything is always in a single partition under this scenario.
___
*Mike Wright*
Principal
