twalthr opened a new pull request #16080:
URL: https://github.com/apache/flink/pull/16080


   ## What is the purpose of the change
   
   Since Flink 1.9 we have supported two SQL planners. Most of the original 
plan of 
[FLIP-32](https://cwiki.apache.org/confluence/display/FLINK/FLIP-32%3A+Restructure+flink-table+for+future+contributions)
 has been implemented. The Blink code merge has been completed and many 
additional features have been added exclusively to the new planner. The new 
planner is now in a much better shape than the legacy one.
   
   In order to avoid user confusion, reduce duplicate code, and improve 
maintainability and testing times of the Flink project as a whole this PR 
removes the legacy planner module. 
   
   This means that both the BatchTableEnvironment and DataSet API interop with 
Table API are reaching end of life. Use the unified TableEnvironment for batch 
and stream processing with the new planner or the DataStream API in batch 
execution mode.
   
   Users are encouraged to update their pipelines. Otherwise Flink 1.13 is the 
last version that offers the old functionality.
   
   Other "legacy batch"-specific interfaces and API will be removed in the next 
PR.
   
   ## Brief change log
   
   - Remove `flink-table-planner` module
   - Remove `flink-table-uber` module
   
   ## Verifying this change
   
   This change is a trivial rework / code cleanup without any test coverage.
   
   ## Does this pull request potentially affect one of the following parts:
   
     - Dependencies (does it add or upgrade a dependency): yes
     - The public API, i.e., is any changed class annotated with 
`@Public(Evolving)`: yes
     - The serializers: no
     - The runtime per-record code paths (performance sensitive): no
     - Anything that affects deployment or recovery: JobManager (and its 
components), Checkpointing, Kubernetes/Yarn/Mesos, ZooKeeper: no
     - The S3 file system connector: no
   
   ## Documentation
   
     - Does this pull request introduce a new feature? no
     - If yes, how is the feature documented? not applicable
   


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