That depends on your requirements.
A common interface is usually less feature rich than the abstracted
processing engines. For example, Cascading does not support iterations or
streaming.
If you are fine with the features (and limitations) of the common
interface, your approach might make sense.
C
Hi Kostas,
my question is related to the fact that now Flink is available as Cascading
engine.
So, if I had to write a general purpose dataflow UI I think I'd use
Cascading or Dataflow,
so that I could draw my pipeline with the UI and write the execution code
using just one API.
Obviously this int
I had a discussion with Joe from the NiFi community, and they are
interested in contributing a connector between NiFi and Flink. I created a
JIRA issue for that: https://issues.apache.org/jira/browse/FLINK-2740
I believe that this is the easiest and most useful integration point to
begin with, as
I saw that now cascading supports Flink..so maybe you could think in
programming a cascading abstraction to have also spark and tez
compatibility for free!what do you think?
On 22 Sep 2015 11:17, "Christian Kreutzfeldt" wrote:
> Hi Slim,
>
> thanks for sharing the presentation. Like Flavio I see
Hi Slim,
thanks for sharing the presentation. Like Flavio I see the (UI)
capabilities provided by Apache NiFi as very helpful for (enterprise)
customers.
At the Otto Group we are currently think about how to track data through a
stream based system like we do in the batch world using staging laye
As a user that would be very helpful!
On 19 Sep 2015 12:34, "Slim Baltagi" wrote:
> Hi Flink experts!
>
> I came across Apache Nifi https://nifi.apache.org
> https://www.youtube.com/watch?v=sQCgtCoZyFQ
> In the Nifi project, there is an open JIRA
> issue:https://issues.apache.org/jira/browse/NIFI
