Thanks Felix,
Thanks fir the response!
I'm looking forward to use it!
On Apr 24, 2015 9:01 PM, "Felix Neutatz" wrote:
> Hi Flavio,
>
> in Thrift you can try:
>
> struct FlavioTuple {
> 1: optional string f1;
> 2: optional string f2;
> 3: optional list f3;
> }
>
> See: http://diwakergu
Hi Flavio,
in Thrift you can try:
struct FlavioTuple {
1: optional string f1;
2: optional string f2;
3: optional list f3;
}
See: http://diwakergupta.github.io/thrift-missing-guide/
I like Thrift the most, because the API for Thrift in Parquet is the
easiest.
Have fun with Parquet :
Hi
I have a small problem with doing a custom join, that I would need some help
with. Maybe I'm also approaching the problem wrong.
So basically I have two dataset.
The simplified example: The first one has a start and end value. The second
dataset is just a list of ordered numbers and some value
Hi!
I think this refers only to the classes in the previous "compiler", now
"optimizer" project. That happened during a refactoring.
Sorry about that. I'll try to get to some time in the next days...
Greetings,
Stephan
On Fri, Apr 24, 2015 at 5:00 PM, Andra Lungu wrote:
> Hey everyone,
>
> I
Hey everyone,
I was following the documentation on how to create a new runtime operator
and I noticed that all the links to the classes on Github return 404.
http://ci.apache.org/projects/flink/flink-docs-master/internals/add_operator.html
Eventually, I started to check the code out directly fro
Vikhyat Korrapati created FLINK-1938:
Summary: Add Grunt for building the front-end
Key: FLINK-1938
URL: https://issues.apache.org/jira/browse/FLINK-1938
Project: Flink
Issue Type: Improv
There is a simple reason for that: They don't support joins. :D
They support n-ary co-group, however. This is implemented using
tagging and a group-by-key operation. So only elements in the same
window can end up in the same co-grouped result.
On Fri, Apr 24, 2015 at 3:51 PM, Matthias J. Sax
wro
Interesting read. Thanks for the pointer.
Take home message (in my understanding):
- they support wall-clock, attribute-ts, and count windows
-> default is attribute-ts (and not wall-clock as in Flink)
-> it is not specified, if a global order is applied to windows, but I
doubt it, because o
Did anyone read these:
https://cloud.google.com/dataflow/model/windowing,
https://cloud.google.com/dataflow/model/triggers ?
The semantics seem very straightforward and I'm sure the google guys
spent some time thinking this through. :D
On Mon, Apr 20, 2015 at 3:43 PM, Stephan Ewen wrote:
> Perfe
I was looking at this great example and I'd like to ask you which
serialization framework is the best if I have to serialize
Tuple3 with Parquet.
The syntax I like the most is the Thrift one but I can't see all the pros
and cons of using it and I'd like to hear your opinion here.
Thanks in advance
Flink's programming model and APIs are based on the concept of data flows.
>From what I get by looking at the website, Ignite rather follows a grid
computing approach. I don't think that these concepts go very well
together.
I think using Ignite as a data source / sink or distributed hash table is
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