As i seen, once i kill my receiver on one machine, it will automatically spawn another receiver on another machine or on the same machine.
Thanks Best Regards On Mon, Mar 16, 2015 at 1:08 PM, Jun Yang <yangjun...@gmail.com> wrote: > Dibyendu, > > Thanks for the reply. > > I am reading your project homepage now. > > One quick question I care about is: > > If the receivers failed for some reasons(for example, killed brutally by > someone else), is there any mechanism for the receiver to fail over > automatically? > > On Mon, Mar 16, 2015 at 3:25 PM, Dibyendu Bhattacharya < > dibyendu.bhattach...@gmail.com> wrote: > >> Which version of Spark you are running ? >> >> You can try this Low Level Consumer : >> http://spark-packages.org/package/dibbhatt/kafka-spark-consumer >> >> This is designed to recover from various failures and have very good >> fault recovery mechanism built in. This is being used by many users and at >> present we at Pearson running this Receiver in Production for almost 3 >> months without any issue. >> >> You can give this a try. >> >> Regards, >> Dibyendu >> >> On Mon, Mar 16, 2015 at 12:47 PM, Akhil Das <ak...@sigmoidanalytics.com> >> wrote: >> >>> You need to figure out why the receivers failed in the first place. Look >>> in your worker logs and see what really happened. When you run a streaming >>> job continuously for longer period mostly there'll be a lot of logs (you >>> can enable log rotation etc.) and if you are doing a groupBy, join, etc >>> type of operations, then there will be a lot of shuffle data. So You need >>> to check in the worker logs and see what happened (whether DISK full etc.), >>> We have streaming pipelines running for weeks without having any issues. >>> >>> Thanks >>> Best Regards >>> >>> On Mon, Mar 16, 2015 at 12:40 PM, Jun Yang <yangjun...@gmail.com> wrote: >>> >>>> Guys, >>>> >>>> We have a project which builds upon Spark streaming. >>>> >>>> We use Kafka as the input stream, and create 5 receivers. >>>> >>>> When this application runs for around 90 hour, all the 5 receivers >>>> failed for some unknown reasons. >>>> >>>> In my understanding, it is not guaranteed that Spark streaming receiver >>>> will do fault recovery automatically. >>>> >>>> So I just want to figure out a way for doing fault-recovery to deal >>>> with receiver failure. >>>> >>>> There is a JIRA post mentioned using StreamingLister for monitoring the >>>> status of receiver: >>>> >>>> >>>> https://issues.apache.org/jira/browse/SPARK-2381?focusedCommentId=14056836&page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel#comment-14056836 >>>> >>>> However I haven't found any open doc about how to do this stuff. >>>> >>>> Any guys have met the same issue and deal with it? >>>> >>>> Our environment: >>>> Spark 1.3.0 >>>> Dual Master Configuration >>>> Kafka 0.8.2 >>>> >>>> Thanks >>>> >>>> -- >>>> yangjun...@gmail.com >>>> http://hi.baidu.com/yjpro >>>> >>> >>> >> > > > -- > yangjun...@gmail.com > http://hi.baidu.com/yjpro >
