Eric Huang created KAFKA-3572:
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Summary: Metrics of topics still exist when they have been deleted
Key: KAFKA-3572
URL: https://issues.apache.org/jira/browse/KAFKA-3572
Project: Kafka
Issue Type:
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https://issues.apache.org/jira/browse/KAFKA-3421?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Liquan Pei updated KAFKA-3421:
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Status: Patch Available (was: In Progress)
> Update docs with new connector features
>
I guess the simplest way would be to use a constructor parameter:
> public static class CampaignProcessor implements
> ProcessorSupplier, List>
> {
> private final String jedis_server;
>
> public CampaignProcessor(String jedisServer) {
> this.jedis_server = jedisServ
Ok... Is it really perform distribution of the field to several instances
of a cluster? I expected to see some way via ProcessorContext...
But may be this is result of the Flink's experience...
Thanks
2016-04-17 12:38 GMT+02:00 Matthias J. Sax :
> I guess the simplest way would be to use a const
Igor Stepanov created KAFKA-3573:
Summary: JSON (de)serialization for kafka-client
Key: KAFKA-3573
URL: https://issues.apache.org/jira/browse/KAFKA-3573
Project: Kafka
Issue Type: New Feature
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ASF GitHub Bot commented on KAFKA-3337:
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GitHub user mjsax opened a pull request:
GitHub user mjsax opened a pull request:
https://github.com/apache/kafka/pull/1231
KAFKA-3337: [WIP] Extract selector as a separate groupBy operator for
KTable aggregations
You can merge this pull request into a Git repository by running:
$ git pull https://github.com/mjsax/k
KafkaStreams works quite different than other systems like Flink/Storm.
It is not a system but a library.
If you start a KafkaStreams application, it runs locally.
Scaling/Parallelism comes into place if you start the same application
on multiple nodes. For this, Kafka's parallelization model is u
Matthias J. Sax created KAFKA-3574:
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Summary: Add missing @returns tags for JavaDoc
Key: KAFKA-3574
URL: https://issues.apache.org/jira/browse/KAFKA-3574
Project: Kafka
Issue Type: Improveme
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Matthias J. Sax updated KAFKA-3574:
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Issue Type: Sub-task (was: Improvement)
Parent: KAFKA-2590
> Add missing @returns tag
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Matthias J. Sax reassigned KAFKA-3429:
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Assignee: Matthias J. Sax
> Remove Serdes needed for repartitioning in KTable stateful
Hi,
I'm slightly confused by KTable.count(..). The javadoc says:
Count number of records of this stream by the selected key into a new
instance of {@link KTable}.
So.. if i send 5 records with the same key to the input topic, as per below
final KafkaProducer producer = new
KafkaProducer<>(prod
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https://issues.apache.org/jira/browse/KAFKA-3101?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Bill Bejeck reassigned KAFKA-3101:
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Assignee: Bill Bejeck
> Optimize Aggregation Outputs
>
>
>
+1
On Sat, Apr 16, 2016 at 10:25 PM, Gwen Shapira wrote:
> +1
>
> On Fri, Apr 15, 2016 at 9:37 AM, Guozhang Wang wrote:
> > +1 from me. Thanks.
> >
> > On Fri, Apr 15, 2016 at 9:16 AM, Jun Rao wrote:
> >
> >> Hi, Jiangjie,
> >>
> >> Thanks for the latest update. +1 on the KIP.
> >>
> >> Jun
>
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Liquan Pei commented on KAFKA-3573:
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Thanks for working on this. Currently, there is a J
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Matthias J. Sax commented on KAFKA-3429:
[~guozhang] I am a little confused here:
Hi Damin,
I am new to KStreams as well, so my answer might not be 100% precise. In
KTable, the same key is treated as updates instead of events. Thus
aggregation on the same key will do some de-dup. The docs for the tech
preview contains some explanation on this behavior:
http://docs.confluent.io
Thanks for the answer. But is it correct in this case to use yahoo
streaming benchmark to compare Kafka, Flink and Storm? Or Kafka streaming
processor is for other category of customers?
Best regards
2016-04-17 16:48 GMT+02:00 Matthias J. Sax :
> KafkaStreams works quite different than other sys
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Igor Stepanov commented on KAFKA-3573:
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Good point, found your code here:
https://git
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Jiangjie Qin commented on KAFKA-3565:
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[~ijuma] A few comments:
1. The performance im
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https://issues.apache.org/jira/browse/KAFKA-3554?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Jiangjie Qin updated KAFKA-3554:
Summary: Generate actual data with specific compression ratio and add
multi-thread support in the Pr
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Jiangjie Qin updated KAFKA-3554:
Description:
Currently the ProducerPerformance always generate the payload with same bytes.
This do
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Ismael Juma commented on KAFKA-3565:
Becket,
1. Yes, the non-compressed throughput c
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Ismael Juma edited comment on KAFKA-3565 at 4/18/16 12:30 AM:
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Ismael Juma edited comment on KAFKA-3565 at 4/18/16 12:29 AM:
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Ismael Juma edited comment on KAFKA-3565 at 4/18/16 12:29 AM:
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Guozhang Wang commented on KAFKA-3429:
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The {{originalSerde}} is used to materialize
Hello,
I think Kafka Streams is better treated as one approach in streaming
processing systems for a variety of customers. For example, say if you
already have a YARN cluster, and you have a dedicated team operating it and
many teams wants to use this for their various streaming jobs, then
submitt
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Guozhang Wang commented on KAFKA-3573:
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We were working on moving the serdes from con
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https://issues.apache.org/jira/browse/KAFKA-119?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Manikumar Reddy resolved KAFKA-119.
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Resolution: Won't Fix
ProducerPerformance.scala is deprecated. New ProducerPerformance tool is
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https://issues.apache.org/jira/browse/KAFKA-1058?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Manikumar Reddy resolved KAFKA-1058.
Resolution: Won't Fix
Kafka code contribution process is moved to Github PR process.
> Cha
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https://issues.apache.org/jira/browse/KAFKA-3005?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Manikumar Reddy resolved KAFKA-3005.
Resolution: Not A Problem
Your approach is error prone. Use rolling restart to set delete.t
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https://issues.apache.org/jira/browse/KAFKA-3050?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Manikumar Reddy resolved KAFKA-3050.
Resolution: Fixed
Fix Version/s: 0.9.0.0
This got fixed in 0.9.0.0 release
> Space i
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