Bug in Message Timeout implementation

Hi I have opened a ticket https://issues.apache.org/jira/browse/STORM-3693. To me, it seems to be a conceptual bug. Am I missing something? Regards Chandan

Re: [DISCUSS] Release Storm 1.0.5 / 1.1.2

Stig, I saw lots of changes in storm-kafka-client 1.x when compared to 1.1.1. Should I assume that storm-kafka-client from 1.x will work fine with storm release 1.1.1? Thanks Chandan On Sun, Jan 14, 2018 at 7:29 PM, chandan singh <cks07...@gmail.com> wrote: > Thanks Stig. > > I

Re: [DISCUSS] Release Storm 1.0.5 / 1.1.2

m code > and build storm-kafka-client yourself. Check out the 1.x-branch and do "mvn > clean install -DskipTests" from the project root. The storm-kafka-client > jar will be in external/storm-kafka-client/target. > > 2018-01-14 9:01 GMT+01:00 chandan singh <cks07...@gmail.com

Re: [DISCUSS] Release Storm 1.0.5 / 1.1.2

+1 Any idea when is 1.1.2v coming out. Under tremendous pressure to upgrade storm-kafka-client due to STORM-2549 . Is there any help needed towards that goal? On Tue, Jan 9, 2018 at 5:59 PM, Satish Duggana wrote: > +1

Re: KafkaSpout v1.1.1 : ManualPartitionNamedSubcription fails to initilialize spout

t; > 2017-09-19 14:23 GMT+02:00 chandan singh <cks07...@gmail.com>: > > > Hi > > > > I am not sure if it is an existing bug but ManualParitionNamedSubcription > > fails to initialize the spout because > > listener.onPartitionsAssigned(newAssignment) is nev

KafkaSpout v1.1.1 : ManualPartitionNamedSubcription fails to initilialize spout

Hi I am not sure if it is an existing bug but ManualParitionNamedSubcription fails to initialize the spout because listener.onPartitionsAssigned(newAssignment) is never invoked. It requires a simple change which I have done locally. If this has already been fixed, please let me know. Regards

KafkaSpout v1.1.1 : FetchOffset vs CommitOffset

Hi I wanted to get my understanding about CommitOffset/FetchOffset in KafkaSout (v1.1.1) confirmed. For Kafka consumer, commitOffset and fetchOffset are same. In other words, Kafka consumer reads from last committedOffset and hence their official documentation (

Re: Few observations related to KafkaSpout implementation (1.1.0)

essarily polling the messages next to the > committed offset when we didn't need to. We've changed it so we seek to the > offset we want to retry instead, which avoids these issues. See > https://github.com/apache/storm/pull/1924/files#diff- > 7d7cbc8f5444fa7ada7962033fc31c5eR302 > for

Re: Few observations related to KafkaSpout implementation (1.1.0)

for optimization. Thanks Chandan On Tue, Jul 11, 2017 at 1:37 AM, chandan singh <cks07...@gmail.com> wrote: > 1) Agreed that short duration blocks are less likely to cause an issue but > it will be much better to avoid them. Anyway, a conclusion is not easy > without some benchmark. I will le

Re: Few observations related to KafkaSpout implementation (1.1.0)

for the amazing work. Chandan On Tue, Jul 11, 2017 at 12:56 AM, chandan singh <cks07...@gmail.com> wrote: > Sorry about being cryptic there. What I meant is that it will be much > better if we don't make assumptions about frequency of failure rates in > topologies. I know it is more o

Re: Few observations related to KafkaSpout implementation (1.1.0)

t to make that this is preventing, or > why they would be helpful. > > - Bobby > > > On Monday, July 10, 2017, 12:14:53 PM CDT, chandan singh < > cks07...@gmail.com> wrote: > > Hi Stig & Bobby > > Thanks for confirming my understanding. > > 1) Ensuring that calls to

Re: Few observations related to KafkaSpout implementation (1.1.0)

Hi Stig & Bobby Thanks for confirming my understanding. 1) Ensuring that calls to nexTuple(), ack() and fail() are non-blocking has been a guideline on http://storm.apache.org/releases/1.1.0/Concepts.html for long. Copying verbatim here : "The main method on spouts is nextTuple. nextTuple

Few observations related to KafkaSpout implementation (1.1.0)

Hi I hope I am using the right mailing list. Please advice if I am wrong. I have few observations about the KafkaSpout and feel that some of these lead to inefficiencies. It will be of great help if someone can throw some light on the rationale behind the implementation. 1) Kafka polling and