to specify partitioning for joins. Flink's SQL planner
> does this for you. If you look into the web UI you'll see an arrow marked
> with HASH pointing from sources to join operators. It means that records
> flowing through this arrow will be distributed to the corresponding
>
Hi,
I'd like to understand a little more how joins work. I have a fairly simple
LEFT JOIN query, and I'm seeing spotty results on the joins. I know there
is a record on the right side, but sometimes it produces a result, and
sometimes it doesn't.
Sample query:
SELECT a.id, b.val1, c.val2
FROM tabl
he OS logs for OOM killer
> > messages or process status?
> >
> > Regards,
> > Roman
> >
> > On Wed, Sep 22, 2021 at 6:30 PM Curt Buechter
> wrote:
> >>
> >> Hi,
> >> I'm getting an error after enabling checkp
gt; > Is it possible that the python process crashed or hung up? (probably
> > performing a snapshot)
> > Could you validate this by checking the OS logs for OOM killer
> > messages or process status?
> >
> > Regards,
> > Roman
> >
> > On Wed, Sep 2
, Sep 22, 2021 at 11:46 AM Curt Buechter
wrote:
> Hi,
> I'm getting an error that happens randomly when starting a flink
> application.
>
> For context, this is running in YARN on AWS. This application is one that
> converts from the Table API to the Stream API, so two flink
Hi,
I'm getting an error that happens randomly when starting a flink
application.
For context, this is running in YARN on AWS. This application is one that
converts from the Table API to the Stream API, so two flink
applications/jobmanagers are trying to start up. I think what happens is
that the
Hi,
I'm getting an error after enabling checkpointing in my pyflink application
that uses a keyed stream and rocksdb state.
Here is the error message:
2021-09-22 16:18:14,408 INFO
org.apache.flink.contrib.streaming.state.RocksDBKeyedStateBackend [] -
Closed RocksDB State Backend. Cleaning up Rock
I have a question about how the conversion from Table API to Datastream API
actually works under the covers.
If I have a Table API operation that creates a random id, like:
SELECT id, CAST(UUID() AS VARCHAR) as random_id FROM table
...then I convert this table to a datastream with
t_env.to_retr
I have a pyflink job that starts using the Datastream api and converts to
the Table API. In the datastream portion, there is a MapFunction. I am
getting the following error:
flink run -py sample.py
java.lang.IllegalArgumentException: The configured managed memory fraction
for Python worker proces
This feels like the simplest error, but I'm struggling to get past it. I
can run pyflink jobs locally just fine by submitting them either via
`python sample.py` or `flink run --target local -py sample.py`. But, when I
try to execute on a remote worker node, it always fails with this error:
table_e
k/blob/master/flink-connectors/flink-connector-kafka/src/main/java/org/apache/flink/streaming/connectors/kafka/KafkaContextAware.java#L48
>>
>> Regards,
>> Dian
>>
>> 2021年6月24日 上午11:45，Curt Buechter 写道：
>>
>> Hi Dian,
>> Thanks for the reply.
>> I
ht that split is still not supported. Does it make sense for
you to split the stream using a filter function? There is some overhead
compared the built-in stream.split as you need to provide a filter function
for each sub-stream and so a record will evaluated multiple times.>
>
> &g
Hi,
New PyFlink user here. Loving it so far. The first major problem I've run
into is that I cannot create a Kafka Producer with dynamic topics. I see
that this has been available for quite some time in Java with Keyed
Serialization using the getTargetTopic method. Another way to do this in
Java ma
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