HeartSaVioR edited a comment on pull request #34089:
URL: https://github.com/apache/spark/pull/34089#issuecomment-1034277243


   > Right, so if you build your app by including Spark via a Maven/Gradle 
dependency, you can specify a kafka-clients dependency on your project to 
override the version used. Is there a reason why this is not possible with 
Spark?
   
   It is possible, but that is not something we will test hard before 
releasing. Choosing the default must be done like we ourselves have a 
production directly affected by this, because that is what end users are 
facing. If we can do opposite, like compiling Spark with Kafka 2.8.1 and using 
it with kafka-clients 3.1.x at runtime, I would feel safer. For sure, I 
wouldn't recommend unless they really need it, and say "it's your own risk".
   
   >> Could you please elaborating more on this? Does this mean Kafka 3.0 has 
different default values on functionality related configurations? If then it 
sounds like end users using Kafka 3.0 should understand what is going on before 
moving on, and the end users of Spark will have to do this in technically 
"minor version upgrade".
   
   > Yes.
   
   OK this backs up my concern. This is something we missed. I don't see any 
effort in this PR about thinking hard on the possible impacts we will get.
   
   That is why I concern more on major releases; everyone struggling with 
semver knows that bumping major version is one of chance in years to make 
breaking changes, so we break minors to majors in major release. Spark 
community is not aiming to release the major version, so end users tend to not 
expect any breaking changes. And we technically do.


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