vikramahuja1001 commented on PR #5890:
URL: https://github.com/apache/hive/pull/5890#issuecomment-3000316790

   @Aggarwal-Raghav , thanks for testing out the patch HIVE-28956 with along 
with HIVE-28909 and HIVE-28972. When i was working on the fix and tested the 
same, the 2 patches were not merged.
   From the above tests, post HIVE-28972 it seems that the JDO performance is 
much better than the current DirectSql Implementation. 
   
   
   
   > @Aggarwal-Raghav, do we know what change in 
[HIVE-28956](https://issues.apache.org/jira/browse/HIVE-28956) introduced a 
perf degradation: batching or `alterPartitions` API? cc 
[vikramahuja1001](https://github.com/vikramahuja1001)
   
   @deniskuzZ , in HIVE-28956, i had moved from alterPartition API to 
alterPartitions API with batching. As is the case currently, alterPartition 
does not support DirectSql. 
   
   
   
   
   
   > @Aggarwal-Raghav, @dengzhhu653, do we have an agreement on 
[HIVE-28956](https://issues.apache.org/jira/browse/HIVE-28956) revert? If yes, 
I can do that.
   > 
   > Also, do we have a benchmark in metastore-tools for `alter table add 
column cascade`? Or how do you find the regression post DataNucleus upgrade, 
private setup ?
   
   Though reverting the patch HIVE-28956 would definitely improve the 
performance of alter table add column cascade operation, but it would still not 
fix the issue of DirectSql being slower than JDO in the alterPartitions API 
which currently is being used in other flows as well, for instance: alter table 
rename operation. 
   This use case of rename table should also potentially suffer from the same 
issue, based on the analysis in the above comments. HIVE-17969 is doing the 
similar change of moving from alterPartition API to alterPartitions API in the 
alter table rename flow. We should also perhaps look and compare the 
performance of the rename operation as well in JDO vs DirectSql and then take a 
call.


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