Hi Sjoerd,

We've added kafka.group.id config to Spark 3.0...

kafka.group.id string none streaming and batch The Kafka group id to use in
Kafka consumer while reading from Kafka. Use this with caution. By default,
each query generates a unique group id for reading data. This ensures that
each Kafka source has its own consumer group that does not face
interference from any other consumer, and therefore can read all of the
partitions of its subscribed topics. In some scenarios (for example, Kafka
group-based authorization), you may want to use a specific authorized group
id to read data. You can optionally set the group id. However, do this with
extreme caution as it can cause unexpected behavior. Concurrently running
queries (both, batch and streaming) or sources with the same group id are
likely interfere with each other causing each query to read only part of
the data. This may also occur when queries are started/restarted in quick
succession. To minimize such issues, set the Kafka consumer session timeout
(by setting option "kafka.session.timeout.ms") to be very small. When this
is set, option "groupIdPrefix" will be ignored.
BR,
G


On Tue, Mar 17, 2020 at 3:34 PM Sjoerd van Leent <
sjoerd.van.le...@alliander.com> wrote:

> Dear reader,
>
>
>
> I must force the group.id of Kafka, as Kafka is under ACL control,
> however, doing so gives me the error:
>
>
>
> Kafka option 'group.id' is not supported as user-specified consumer
> groups are not used to track offsets.
>
>
>
> This won’t work, as not being able to set it, basically disqualifies using
> Spark within our organization. How can I force (Py)Spark to respect the
> group.id used?
>
>
>
> Met vriendelijke groet,
>
>
>
> *Sjoerd van Leent*
>
> Systeem Engineer | IT AST-B&R CSC
>
>
>
> *M   *+31 6 11 24 52 27
> *E *   sjoerd.van.le...@alliander.com
>
>
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