gt; >
> > [1]
> >
> https://ci.apache.org/projects/flink/flink-docs-master/api/java/org/apache/flink/streaming/connectors/fs/RollingSink.html
>
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https://issues.apache.org/jira/browse/FLINK-3961
>> <https://issues.apache.org/jira/browse/FLINK-3961>
>>
>>
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Yeah, created this one https://issues.apache.org/jira/browse/FLINK-3961
<https://issues.apache.org/jira/browse/FLINK-3961>
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he near future?
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Is there any plans to implement this kind of feature (possibility to write to
data specified partitions) in the near future?
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Yes, you're right. I did not understand your question correctly.
Right now, Flink does not feature an output format that writes records to
output files depending on a key attribute.
You would need to implement such an output format yourself and append it as
follows:
val data = ...
data.partitionB
Fabian,
Not sure if we are on the same page. If I do something like below code, it
will groupby field 0 and each task will write a separate part file in
parallel.
val sink = data1.join(data2)
.where(1).equalTo(0) { ((l,r) => ( l._3, r._3) ) }
.partitionByHash(0)
.writeAsCsv(pathBa
Hi Srikanth,
DataSet.partitionBy() will partition the data on the declared partition
fields.
If you append a DataSink with the same parallelism as the partition
operator, the data will be written out with the defined partitioning.
It should be possible to achieve the behavior you described using
D
Hello,
Is there a Hive(or Spark dataframe) partitionBy equivalent in Flink?
I'm looking to save output as CSV files partitioned by two columns(date and
hour).
The partitionBy dataset API is more to partition the data based on a column
for further processing.
I'm thinking there is no direct
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