Hi,
I'm trying to read Parquet/Hive data using parquet's ParquetInputFormat and
hive's DataWritableReadSupport.
I have an error when the TupleSerializer tries to create an instance of
ArrayWritable, using reflection because ArrayWritable has no no-args
constructor.
I've been able to make it w
Opps, sorry
I was supposed to email this one to hive mailiing list.
On Fri, Dec 18, 2015 at 2:19 AM, Philip Lee wrote:
> I think It is from Hive Bug about something related to metastore.
>
> Here is the thing.
>
> After I generated scale factor 300 named bigbench300 and bigbench100,
> which al
> On 18 Dec 2015, at 11:07, Philip Lee wrote:
>
> Opps, sorry
>
> I was supposed to email this one to hive mailiing list.
No problem. Can happen easily with auto completion ;)
– Ufuk
I'll answer to myself :)
I think i've managed to make it work by creating my "WrappingReadSupport" that
wraps the DataWritableReadSupport but I also insert my "WrappingMaterializer"
that converts the ArrayWritable produced by the original Materializer to
String[]. Then later on, the String[] po
Hi Nirmalya,
sorry for the delayed answer.
First of all, Flink does not take care that our windows fit into memory.
The default trigger depends on the way in which you define a window. Given
a KeyedStream you can define a window in the following ways:
KeyedStream s = ...
s.timeWindow() // this w
If I understand you correctly, you want to write something like:
--
[cassandra]
^
|
V
(even
Hi Till,
Many thanks for your quick response.
I have modified the WordCountExample to re-reproduce my problem in a simple
example.
I run the code below with the following command:
./bin/flink run -m yarn-cluster -yn 1 -ys 4 -yjm 1024 -ytm 1024 -c
mypackage.WordCountExample ../flinklink.jar
An
In which log file are you exactly looking for the logging statements? And
on what machine? You have to look on the machines on which the yarn
container were started. Alternatively if you have log aggregation
activated, then you can simply retrieve the log files via yarn logs.
Cheers,
Till
On Fri,
I was thinking to something more like
http://www.infoq.com/articles/key-lessons-learned-from-transition-to-nosql
that basically implement what you call Out-of-core state at
https://cwiki.apache.org/confluence/display/FLINK/Stateful+Stream+Processing.
Riak provide
some feature to handle the eventual
