Hi,everyone:
Is there Any api that let the DataStream join a DataSet ? I have read all the
document But I can't find .
If Flink now does not have the api, will Flink support it in the future ?
thanks a lot!
Glad to hear. I read "flink-storm-compatibility-core" and was alarmed. ;)
On 06/27/2015 07:50 PM, Aljoscha Krettek wrote:
> Nevermind, removal of my local maven repository solved the problem. Sorry
> for the inconvenience.
>
> On Sat, 27 Jun 2015 at 19:22 Márton Balassi
> wrote:
>
>> Interestin
Yes. But as I said, you can get the same behavior with a
GroupedDataStream using a tumbling 1-tuple-size window. Thus, there is
no conceptual advantage in using KeyedDataStream and no disadvantage in
binding stateful operations to GroupedDataStreams.
On 06/27/2015 06:54 PM, Márton Balassi wrote:
>
Nevermind, removal of my local maven repository solved the problem. Sorry
for the inconvenience.
On Sat, 27 Jun 2015 at 19:22 Márton Balassi
wrote:
> Interesting, it does not appear on travis or my local machine, but both run
> linux. (Ubuntu 14.10, Java 8, mvn 3.0.5 in the latter case)
>
> On p
Gyula Fora created FLINK-2283:
-
Summary: Make grouped reduce/fold/aggregations stateful using
Partitioned state
Key: FLINK-2283
URL: https://issues.apache.org/jira/browse/FLINK-2283
Project: Flink
Gyula Fora created FLINK-2282:
-
Summary: Deprecate non-grouped stream reduce/fold/aggregations for
0.9.1
Key: FLINK-2282
URL: https://issues.apache.org/jira/browse/FLINK-2282
Project: Flink
Issu
Interesting, it does not appear on travis or my local machine, but both run
linux. (Ubuntu 14.10, Java 8, mvn 3.0.5 in the latter case)
On paper the remote-resources plugin is only used for the Eclipse
integration and should not even effect the maven build itself, at least
that the comment says in
@Matthias: Your point of working with a minimal number of clear concepts is
desirable to say the least. :)
The reasoning behind the KeyedDatastream is to associate Flink persisted
operator state with the keys of the data that produced it, so that stateful
computation becomes scalabe in the future.
Hi,
anyone else seeing this:
[ERROR] Failed to execute goal
org.apache.maven.plugins:maven-remote-resources-plugin:1.5:process
(default) on project flink-storm-compatibility-core: Execution default of
goal org.apache.maven.plugins:maven-remote-resources-plugin:1.5:process
failed: For artifact {nul
Hi, You can choose any unassigned issue about Flink Machine Learning Library
(flink-ml) in JIRA. [1]
There are some issues for starter in flink-ml such as FLINK-1737 [2],
FLINK-1748 [3], FLINK-1994 [4].
First, It would be better to read some articles about contributing to Flink.
[5][6]
And if y
Hello everyone,
I came across Stratosphere while looking for GSOC organisations working in
Machine Learning. I got to know that it had become Apache Flink.
I am interested in this project:
https://github.com/stratosphere/stratosphere/wiki/Google-Summer-of-Code-2014#implement-one-or-multiple-machi
Hey guys,
Me again :) So now that my wonderful job finishes, I would like to monitor
it a bit (i.e. build some charts on the number of messages per vertex,
compute the total amount of time elapsed per computation per vertex, etc).
The main computational-intensive operation is a coGroup. There, wi
This was more a conceptual point-of-view argument. From an
implementation point of view, skipping the window building step is a
good idea if a tumbling 1-tuple-size window is detected.
I prefer to work with a minimum number of concepts (and apply internal
optimization if possible) instead of using
What do you mean by Comment 2? Using the whole window apparatus if you just
want to have, for example, a simple partitioned filter with partitioned
state seems a bit extravagant.
On Sat, 27 Jun 2015 at 15:19 Matthias J. Sax
wrote:
> Nice starting point.
>
> Comment 1:
> "Each individual stream p
Nice starting point.
Comment 1:
"Each individual stream partition delivers elements strictly in order."
(in 'Parallel Streams, Partitions, Time, and Ordering')
I would say "FIFO" and not "strictly in order". If data is not emitted
in-order, the stream partition will not be in-order either.
Comme
+1
- tested local-mode and cluster-mode for hadoop 2.7 with
https://github.com/aljoscha/FliRTT (by the way, this runs with built-in
data and external data)
On Fri, 26 Jun 2015 at 12:45 Robert Metzger wrote:
> +1
>
> - Ran a 100 GB wordcount on a Hadoop/YARN 2.4.0 installation. So both YARN
> an
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