Hi Mihail,
Thanks for the code. I'm trying to reproduce the problem now.
On Wed, Jul 1, 2015 at 8:30 PM, Mihail Vieru vi...@informatik.hu-berlin.de
wrote:
Hi Max,
thank you for your reply. I wanted to revise and dismiss all other factors
before writing back. I've attached you my code and
Hi Stephan,
I think that clean shutdown is a major feature to build a complex persistent
service that use Flink Streaming for a data-quality critical task, and I’ll
mark my code with a // FIXME comment waiting for this feature to be available !
Greetings,
Arnaud
De : ewenstep...@gmail.com
Hi!
If there is a CassandraSource for Hadoop, you can also use that with the
HadoopInputFormatWrapper.
If you want to implement a Flink-specific source, extending InputFormat is
the right thing to do. A user has started to implement a cassandra sink in
this fork (may be able to reuse some code
Hi Stephan,
Thanks a lot !
I will give it a look.
Cheers
On Thu, Jul 2, 2015 at 6:05 PM, Stephan Ewen se...@apache.org wrote:
Hi!
If there is a CassandraSource for Hadoop, you can also use that with the
HadoopInputFormatWrapper.
If you want to implement a Flink-specific source,
@Alexander I’m happy to hear that you want to help me. If you help me, I really
appreciate. :)
Regards,
Chiwan Park
On Jul 2, 2015, at 2:57 PM, Alexander Alexandrov
alexander.s.alexand...@gmail.com wrote:
@Chiwan: let me know if you need hands-on support. I'll be more then happy to
The problem is that your input and output path are the same. Because Flink
executes in a pipelined fashion, all the operators will come up at once.
When you set WriteMode.OVERWRITE for the sink, it will delete the path
before writing anything. That means that when your DataSource reads the
input,
Thanks Stephan,
That's clear !
Cheers
On Thu, Jul 2, 2015 at 6:13 PM, Stephan Ewen se...@apache.org wrote:
Hi!
I am actually working to get some more docs out there, there is a lack
right now, agreed.
Concerning your questions:
(1) Batch programs basically recover from the data sources
Hi to all,
I'd like to join 2 datasets of POJO, let's say for example:
Person:
- name
- birthPlaceId
Place:
- id
- name
I'd like to do
people.coCoGroup(places).where(birthPlaceId).equalTo(id).with(...)
However, not all people have a birthPlaceId value in my use case..so I get
a
Hi Flavio!
Keys cannot be null in Flink, that is a contract deep in the system.
Filter out the null valued elements, or, if you want them in the result, I
would try to use a special value for null. That should do it.
BTW: In SQL, joining on null usually filters out elements, as key
operations
ok, thanks for the help Stephan!
On 2 Jul 2015 20:05, Stephan Ewen se...@apache.org wrote:
Hi Flavio!
Keys cannot be null in Flink, that is a contract deep in the system.
Filter out the null valued elements, or, if you want them in the result, I
would try to use a special value for null.
Hello,
I'd like to share my code for TeraSort on Flink and Spark which uses
the same range partitioner as Hadoop TeraSort:
https://github.com/eastcirclek/terasort
I also write a short report on it:
http://eastcirclek.blogspot.kr/2015/06/terasort-for-spark-and-flink-with-range.html
In the blog
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