parallel operations), for which they may also need
to revise their scheduling model.
[1]
https://ci.apache.org/projects/flink/flink-docs-release-1.11/concepts/flink-architecture.html
On Fri, Oct 30, 2020 at 10:05 AM Yuta Morisawa
mailto:yu-moris...@kddi-research.jp>> wrote:
Hello,
Hello,
I am wondering whether Flink operators synchronize their execution
states like Apache Spark. In Apache Spark, the master decides
everything, for example, it schedules jobs and assigns tasks to
Executors so that each job is executed in a synchronized way. But Flink
looks different. It a
essed element.
Best,
Victor
On 2019/8/7, 10:56 AM, "Yuta Morisawa" wrote:
Hi Yun
Thank you for replying.
>Have you set a default value for the state ?
Actually, the constructor of the ValueStateDescriptor with default value
is deprecated
Hi Yun
Thank you for replying.
>Have you set a default value for the state ?
Actually, the constructor of the ValueStateDescriptor with default value
is deprecated so I don't set it.
The problem occurs when the stream1 comes first.
I made sure the 'ValueState data' has data from stream
Hi
I am trying to use low-level joins.
According to the doc, the way is creating a state and access it from
both streams, but I can't.
https://ci.apache.org/projects/flink/flink-docs-release-1.8/dev/stream/operators/process_function.html
This is a snippet of my code.
It seems that the process
different machines.
On Mon, Jul 29, 2019 at 11:12 AM Yuta Morisawa
mailto:yu-moris...@kddi-research.jp>> wrote:
Hi all
I want to use the same state for multiple times.
stream
.keyBy(0)
.map(new MyRichMapfunction)
...
.keyBy(0)
.map(new MyRichMapfunction
Hi all
I want to use the same state for multiple times.
stream
.keyBy(0)
.map(new MyRichMapfunction)
...
.keyBy(0)
.map(new MyRichMapfunction2)
In this snippet, I want access the same state in MyRichMapfunction and
MyRichMapfunction2, but I failed in spite of keying the same key.
Is there any
Motavalli
*From:* Yuta Morisawa
*Sent:* Tuesday, December 18, 2018 6:30:09 AM
*To:* user@flink.apache.org
*Subject:* How to update Flink applications gracefully
Hi all
Now I'm trying to update my streaming application.
Hi all
Now I'm trying to update my streaming application.
But I have no idea how to update it gracefully.
Should I stop it, replace a jar file then restart it?
In my understanding, in that case, all the state will be recovered if I
use checkpoints in a persistent storage.
Is this correct?
Tha
in flink's documentation is in
terms of the types flink supported. But for all the other arbitrary
types kryo is the first choice.
2018-07-12 9:55 GMT+08:00 Yuta Morisawa <mailto:yu-moris...@kddi-research.jp>>:
Thank you for your answer.
> For POJOs Flink has a custo
se Avro as a fallback.
On 11.07.2018 09:24, Yuta Morisawa wrote:
Hi all
Now, I'm reading Flink document and I have some points to feel
difficult to get an idea.
I'd appreciate if you tell it me.
1,TypeInformation
I understand TypeInformation is used for selecting relevant
serializer
Hi all
Now, I'm reading Flink document and I have some points to feel difficult
to get an idea.
I'd appreciate if you tell it me.
1,TypeInformation
I understand TypeInformation is used for selecting relevant serializer
and comparator.
But, the ducument doesn't specify if it has another way
at 12:11 AM, Yuta Morisawa
mailto:yu-moris...@kddi-research.jp>> wrote:
Hi
I want to apply a window function simply on data from each
kafka-partition(I mean I don't need any grouping and just want to
process data parallely).
I think the best way to do so is drawing
Hi
I want to apply a window function simply on data from each
kafka-partition(I mean I don't need any grouping and just want to
process data parallely).
I think the best way to do so is drawing kafka partition id and use it
for keyBy function.
For example,
val data = stream.keyBy(kafka-parti
ght that be
an issue?
On Wed, Dec 6, 2017 at 9:50 AM, Yuta Morisawa
mailto:yu-moris...@kddi-research.jp>>
wrote:
> Which version of Fllink are you using?
I'm using Flink 1.3.0.
> Is the high CPU usage caused by the browser or the JVM?
The CPU usage of browse
JobManager,
but I don't know of a good way to do that without modifying the source.
On 06.12.2017 01:20, Yuta Morisawa wrote:
Hi Timo
I execute streaming job without checkpointing and I don't configure
any state backend, so it may be "MemoryStateBackend".
Actually, my stre
o
much CPU resources?
Regards,
Timo
Am 12/5/17 um 5:13 AM schrieb Yuta Morisawa:
Hi
Now I am looking for the way to increase the number of allocated CPU
cores because my JobManagaer WEBUI is very heavy and sometimes freeze.
I think this is caused by the resource shortage of JobManager.
H
ources?
Regards,
Timo
Am 12/5/17 um 5:13 AM schrieb Yuta Morisawa:
Hi
Now I am looking for the way to increase the number of allocated CPU
cores because my JobManagaer WEBUI is very heavy and sometimes freeze.
I think this is caused by the resource shortage of JobManager.
How can I increase the
Hi
Now I am looking for the way to increase the number of allocated CPU
cores because my JobManagaer WEBUI is very heavy and sometimes freeze.
I think this is caused by the resource shortage of JobManager.
How can I increase the number of CPU for JobManager in YARN mode?
Thanks
Yuta
--
re never GC'd (unless a job was cancelled), so the
setup cost is a one time thing that only happens when the job is started.
Best, Fabian
2017-09-15 12:43 GMT+02:00 Yuta Morisawa <mailto:yu-moris...@kddi-research.jp>>:
Hi Fabian,
Thank you for your description.
This is
Kafka before subsequent tasks have been started.
So, there is quite a lot happening when you call execute() including
network communication and task deployment.
Hope this helps,
Fabian
2017-09-15 4:25 GMT+02:00 Yuta Morisawa <mailto:yu-moris...@kddi-research.jp>>:
Hi, Fabian
>
ycle of tasks.
Best, Fabian
2017-09-12 11:02 GMT+02:00 Yuta Morisawa <mailto:yu-moris...@kddi-research.jp>>:
Hi,
I am worrying about the delay of the Streaming API.
My application is that it gets data from kafka-connectors and
process them, then push data to kafka-pro
Hi,
I am worrying about the delay of the Streaming API.
My application is that it gets data from kafka-connectors and process
them, then push data to kafka-producers.
The problem is that the app suffers a long delay when the first data
come in the cluster.
It takes about 1000ms to process data
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