Hi Cody, Our job is our failsafe as we don't have Control over Kafka Stream as of now. Can setting rebalance max retries help? We do not have any monitors setup as of now. We need to setup the monitors.
My idea is to to have some kind of Cron job that queries the Streaming API for monitoring like every 5 minutes and then send an email alert and automatically restart the Streaming job by deleting the Checkpoint directory. Would that help? Thanks! On Mon, Nov 9, 2015 at 11:09 AM, Cody Koeninger <[email protected]> wrote: > The direct stream will fail the task if there is a problem with the kafka > broker. Spark will retry failed tasks automatically, which should handle > broker rebalances that happen in a timely fashion. spark.tax.maxFailures > controls the maximum number of retries before failing the job. Direct > stream isn't any different from any other spark task in that regard. > > The question of what kind of monitoring you need is more a question for > your particular infrastructure and what you're already using for > monitoring. We put all metrics (application level or system level) into > graphite and alert from there. > > I will say that if you've regularly got problems with kafka falling over > for half an hour, I'd look at fixing that before worrying about spark > monitoring... > > > On Mon, Nov 9, 2015 at 12:26 PM, swetha <[email protected]> wrote: > >> Hi, >> >> How to recover Kafka Direct automatically when the there is a problem with >> Kafka brokers? Sometimes our Kafka Brokers gets messed up and the entire >> Streaming job blows up unlike some other consumers which do recover >> automatically. How can I make sure that Kafka Direct recovers >> automatically >> when the broker fails for sometime say 30 minutes? What kind of monitors >> should be in place to recover the job? >> >> Thanks, >> Swetha >> >> >> >> -- >> View this message in context: >> http://apache-spark-user-list.1001560.n3.nabble.com/Kafka-Direct-does-not-recover-automatically-when-the-Kafka-Stream-gets-messed-up-tp25331.html >> Sent from the Apache Spark User List mailing list archive at Nabble.com. >> >> --------------------------------------------------------------------- >> To unsubscribe, e-mail: [email protected] >> For additional commands, e-mail: [email protected] >> >> >
