Hi,
Is there a way to specify an exponential backoff strategy for when
async function calls fail?
I have an async function that does web requests to a rate-limited API.
Can you handle that with settings on the async function call?
Thanks,
William
Trying to build a new Docker image by replacing 1.6.3 with 1.6.4 in
the Dockerfile found here (
https://github.com/docker-flink/docker-flink ), but seems to require a
new signing key, Is it available somewhere?
Getting
+ wget -nv -O flink.tgz.asc
https://www.apache.org/dist/flink/flink-1.6.4/fli
essing I'm not the
only one doing async functions in Scala so figured I'd ask :)
Thanks,
William Saar
: "Lasse Nedergaard"
To:"William Saar"
Cc:"Fabian Hueske" , "user"
Sent:Tue, 5 Feb 2019 10:41:41 +0100
Subject:Re: How to add caching to async function?
Hi William
No iterations isn’t the solution as you can (will) end up in a
deadlock. We conclude
Thanks! Looks like iterations is indeed the way to go for now then...
- Original Message -
From: "Lasse Nedergaard"
To:"Fabian Hueske"
Cc:"William Saar" , "user"
Sent:Mon, 4 Feb 2019 20:20:30 +0100
Subject:Re: How to add caching to async f
Hi,
I am trying to implement an async function that looks up a value in a
cache or, if the value doesn't exist in the cache, queries a web
service, but I'm having trouble creating the cache. I've tried to
create a RichAsyncFunction and add a map state as cache, but I'm
getting: State is not suppor
How can I easiest use s3 from a Flink job deployed in a session
cluster on kubernetes?
I've tried including the flink-s3-fs-hadoop dependency in the sbt file
for my job, can I programmatically set the properties to point to it?
Is there a ready-made docker image for a flink with s3 dependencies
I'm running Flink 1.7 in ECS, is this a known issue or should I create
a jira?
The web console doesn't show anything when trying to list logs or
stdout for task managers and the job manager log have stack traces for
the errors
2018-12-19 15:35:53,498 ERROR
org.apache.flink.runtime.rest.handler.
Thanks, works great! This should be very useful for real-time
dashboard that want to compute in event time, especially for
multi-tenant systems or other specialized kafka topics that can have
gaps in the traffic.
- Original Message -
From: "Aljoscha Krettek"
To:"Wi
Any standardized components to generate watermarks based on processing
time in an event time stream when there is no data from a source?
The docs for event time [1] indicate that people are doing this, but
the only suggestion on Stack Overflow [2] is to make every window
operator in stream have a
data used to come from two
different topics).
William
- Original Message -
From:
"Gary Yao"
To:
"William Saar"
Cc:
"user"
Sent:
Thu, 18 Jan 2018 11:11:17 +0100
Subject:
Re: Far too few watermarks getting generated with Kafka source
Hi William,
How often
Hi,
I have a job where we read data from either Kafka or a file (for
testing), decode the entries and flat map them into events, and then
add a timestamp and watermark assigner to the events in a later
operation. This seems to generate periodic watermarks when running
from a file, but when Kafka is
Hi,
I have added the code below to the start of processElement2 in
CoProcessFunction. It prints timestamps and watermarks for the first 3
elements for each new watermark. Shouldn't the timestamp always be
lower than the next watermark? The 3 timestamps before the last
watermark are all larger than
pending on the details.
Nico
[1] https://ci.apache.org/projects/flink/flink-docs-release-1.3/dev/
windows.html#triggers
[2]
https://ci.apache.org/projects/flink/flink-docs-release-1.3/dev/stream/
process_function.html
On Tuesday, 20 June 2017 12:52:38 CEST William Saar wrote:
> Hi,
> I am
Hi,
I am looking to implement a window that sends out updates for each new
event it receives and also when an expiration timer fires and purges
the window (the expiration time can be determined from a timestamp in
the first event).
I can't figure out a way to do this that does not require preserv
Flink.
- Original Message -
From:
"Gyula Fóra"
To:
"William Saar" ,
Cc:
Sent:
Tue, 30 May 2017 13:56:08 +
Subject:
Re: Porting batch percentile computation to streaming window
I think you could actually do a window operation to get the
tDigestStre
ark information or something on
metrics objects in line 1 and emit T digests more often in line 2?
Finally, how do I access the watermark/window information in my fold
operation in line 1?
Thanks!
- Original Message -
From: "Gyula Fóra"
To:"William Saar" ,
Cc:
Sent:Tue, 30
I am porting a calculation from Spark batches that uses broadcast
variables to compute percentiles from metrics and curious for tips on
doing this with Flink streaming.
I have a windowed computation where I am compute metrics for
IP-addresses (a windowed stream of metrics objects grouped by
IP-add
the end of the window + allowedLateness you have set.
On Tue, Nov 22, 2016 at 11:08 PM, William Saar
wrote:
> Thanks!
> One difference is that my topology had 2 sources. I have updated
your
> example to also use 2 sources and that breaks the co-group
operation in the
> e
6849f405
Gyula is right, the ContinuousEventTimeTrigger never purges the
window
but that you can circumvent that by extending this trigger and
purging
at the end of the window, similarly as done in the EventTimeTrigger.
-Max
On Mon, Nov 21, 2016 at 6:52 PM, William Saar
wr
d windowed
streams?
Hi William,
I am wondering whether the ContinuousEventTimeTrigger is the best
choice here (it never cleans up the state as far as I know).
Have you tried the simple SlidingEventTimeWindows as your window
function?
Cheers,
Gyula
William Saar ezt írta (időpont: 2016. nov.
19.,
Hi!
My topology below seems to work when I comment out all the lines with
ContinuousEventTimeTrigger, but prints nothing when the line is in
there. Can I coGroup two large time windows that use a different
trigger time than the window size? (even if the
ContinuousEventTimeTrigger doesn't
Hi,
How can I maintain a local state, for instance a ConcurrentHashMap, across
different steps in a streaming chain on a single machine/process?
Static variable? (This doesn't seem to work well when running locally as it
gets shared across multiple instances, a common "pipeline" store would be
h
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