Hi,
Can the enriching data be keyed? Or is it something that has to be broadcasted
to each operator?
Either way, I think Side Inputs (an upcoming feature in the future) is the best
fit for this. You can take a look at
https://issues.apache.org/jira/browse/FLINK-6131.
Regarding the 3 options yo
Dear Flink Users,
I’m getting started with Flink and I’ve bumped into a small problem. I have a
keyed stream like this:
val stream = env.addSource(consumer)
.flatMap(new ValidationMap()).name("ValidationMap")
.keyBy(x => (x.getObj.foo(), x.getObj.bar(), x.getObj.baz()))
.flatMap(new Calcul
Hi. Say I have a few reference data sets need to be used for a
streaming job. The sizes range between 10M-10GB. The data is not
static, will be refreshed at minutes and/or day intervals.
With the new advancements in Flink, it seems there are quite a few options.
A. Store all the data in an exte
Hi,
I'm not aware of a performance report for this feature. I don't think it is
well known or used a lot.
The classes to check out for prepartitioned / presorted data are
SplitDataProperties [1], DataSource [2], and as an example
PropertyDataSourceTest [3].
[1]
https://github.com/apache/flink/blo
thanks for tip @Stephan.
To [1] , there's a description about "I’ve got sooo much data to join, do
I really need to ship it?" . How to configure Flink to touch that target?
Is there a performance report ?
[1] :
https://flink.apache.org/news/2015/03/13/peeking-into-Apache-Flinks-Engine-Room.html
Hi,
Flink does not apply join order optimization (neither in the DataSet nor in
the Table API). Joins are executed in the same order as they are specified.
You can build bushy join plans for SQL by nesting queries:
SELECT *
FROM (SELECT * FROM X, Y WHERE x = y) AS t1, (SELECT * FROM U, V WHERE u
Hi Kostas,
As suggested I switched to version 1.3-SNAPSHOT and the project run
without any problem. I will keep you informed if any other issue occurs.
Thanks again for the help.
Cheers,
Simone.
On 16/05/2017 16:36, Kostas Kloudas wrote:
Hi Simone,
Glad I could help ;)
Actually it would b
Minor update: I have executed the flink-runtime tests on XFS, Lustre and
DVS (Cray DataWarp), and I observe divergences on XFS and Lustre, but not
on DVS. It turns out that cached reads are reported by the file systems as
well, so I don't think caching is an issue here. There might still be some
th
Hi Valentin!
Your understanding is correct, the Kafka connectors do not use the consumer
group functionality to distribute messages across multiple instances of a
FlinkKafkaConsumer source. It’s basically determining which instances should be
assigned which Kafka partitions based on a simple ro
Hi Bruno,
Thanks for reporting this! And sorry for the stale response here, this one
slipped out of my notice.
As far as I can tell, this seems to have been fixed indirectly by
https://issues.apache.org/jira/browse/FLINK-5949.
Cheers,
Gordon
On 18 May 2017 at 3:15:18 PM, Bruno Michelin Rakot
Hi all,
FYI, this issue seems to be fixed in flink 1.2.1.
Regards,
From: Bruno Michelin Rakotondranaivo
[mailto:bruno.michelin.rakotondrana...@ericsson.com]
Sent: vendredi 21 avril 2017 12:47
To: user@flink.apache.org
Subject: Failed checkpointing on HDFS : Flink don't use the right authentica
11 matches
Mail list logo