Well, for future reference, this helped in the case of ABFS:
logger.abfs.name = org.apache.hadoop.fs.azurebfs.services.AbfsClient
logger.abfs.level = DEBUG
logger.abfs.filter.failures.type = RegexFilter
logger.abfs.filter.failures.regex = ^.*([Ff]ail|[Rr]etry|: [45][0-9]{2},).*$
logger.abfs.filte
I must ask again if anyone at least knows if Flink's file system can expose
more detailed exceptions when things go wrong, Azure support is asking for
specific exception messages to decide how to troubleshoot.
Regards,
Alexis.
Am Di., 23. Juli 2024 um 13:39 Uhr schrieb Alexis Sarda-Espinosa <
sar
Hi again,
I found a Hadoop class that can log latency information [1], but since I
don't see any exceptions in the logs when a checkpoint expires due to
timeout, I'm still wondering if I can change other log levels to get more
insights, maybe somewhere in Flink's file system abstractions?
[1]
htt
Hello,
We have a Flink job that uses ABFSS for checkpoints and related state.
Lately we see a lot of exceptions due to expiration of checkpoints, and I'm
guessing that's an issue in the infrastructure or on Azure's side, but I
was wondering if there are Flink/Hadoop Java packages that log potentia
