Erik Krogen created SPARK-33185:
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Summary: YARN: Print direct links to driver logs alongside
application report in cluster mode
Key: SPARK-33185
URL: https://issues.apache.org/jira/browse/SPARK-33185
Project: Spark
Issue Type: Improvement
Components: YARN
Affects Versions: 3.0.1
Reporter: Erik Krogen
Currently when run in {{cluster}} mode on YARN, the Spark {{yarn.Client}} will
print out the application report into the logs, to be easily viewed by users.
For example:
{code}
INFO yarn.Client:
client token: Token { kind: YARN_CLIENT_TOKEN, service: }
diagnostics: N/A
ApplicationMaster host: X.X.X.X
ApplicationMaster RPC port: 0
queue: default
start time: 1602782566027
final status: UNDEFINED
tracking URL: http://hostname:8888/proxy/application_<id>/
user: xkrogen
{code}
Typically, the tracking URL can be used to find the logs of the
ApplicationMaster/driver while the application is running. Later, the Spark
History Server can be used to track this information down, using the
stdout/stderr links on the Executors page.
However, in the situation when the driver crashed _before_ writing out a
history file, the SHS may not be aware of this application, and thus does not
contain links to the driver logs. When this situation arises, it can be
difficult for users to debug further, since they can't easily find their driver
logs.
It is possible to reach the logs by using the {{yarn logs}} commands, but the
average Spark user isn't aware of this and shouldn't have to be.
I propose adding, alongside the application report, some additional lines like:
{code}
Driver Logs (stdout):
http://hostname:8042/node/containerlogs/container_<id>/xkrogen/stdout?start=-4096
Driver Logs (stderr):
http://hostname:8042/node/containerlogs/container_<id>/ekrogen/stderr?start=-4096
{code}
With this information available, users can quickly jump to their driver logs,
even if it crashed before the SHS became aware of the application. This has the
additional benefit of providing a quick way to access driver logs, which often
contain useful information, in a single click (instead of navigating through
the Spark UI).
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