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About auto-topic creation: If your broker configuration allows for
this, yes it would work. However, keep in mind, that the topic will be
created with default values (according to broker config) with regard
to number of partitions and replication fac
I could successfully get the total (not average). As far as I see, there is
no need to create a topic manually before I run the app. Topic is created
if there is data and topic name not exists. Here is my code:
KStreamBuilder builder = new KStreamBuilder();
KStream longs = builder.stream(
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You should create input/intermediate and output topic manually before
you start you Kafka Streams application.
- -Matthias
On 10/18/16 3:34 PM, Furkan KAMACI wrote:
> Sorry about concurrent questions. Tried below code, didn't get any
> error but c
Sorry about concurrent questions. Tried below code, didn't get any error
but couldn't get created output topic:
Properties props = new Properties();
props.put("bootstrap.servers", "localhost:9092");
props.put("acks", "all");
props.put("retries", 0);
props.pu
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Two things:
1) you should not apply the window to the first count, but to the base
stream to get correct results.
2) your windowed aggregation, doew not just return String type, but
Window type. Thus, you need to either insert a .map() to transform
Hi Matthias,
I've tried this code:
*final Properties streamsConfiguration = new Properties();*
*streamsConfiguration.put(StreamsConfig.APPLICATION_ID_CONFIG,
"myapp");*
*streamsConfiguration.put(StreamsConfig.BOOTSTRAP_SERVERS_CONFIG,
"localhost:9092");*
*streamsCo
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I see. KGroupedStream will be part of 0.10.1.0 (should be release the
next weeks).
So, instead of
> .groupByKey().count()
you need to do
> .countByKey()
- -Matthias
On 10/18/16 12:05 PM, Furkan KAMACI wrote:
> Hi Matthias,
>
> Thanks for you
Hi Matthias,
Thanks for your detailed answer. By the way I couldn't find "KGroupedStream"
at version of 0.10.0.1?
Kind Regards,
Furkan KAMACI
On Tue, Oct 18, 2016 at 8:41 PM, Matthias J. Sax
wrote:
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> Hi,
>
> You just need to read you stream
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Hi,
You just need to read you stream and apply an (windowed) aggregation
on it.
If you use non-windowed aggregation you will get "since the
beginning". If you use windowed aggregation you can specify the window
size as 1 hour and get those results.
