rickyma commented on PR #1759:
URL: 
https://github.com/apache/incubator-uniffle/pull/1759#issuecomment-2146959428

   We can do a math here. According to 
https://github.com/apache/incubator-uniffle/pull/1759#issuecomment-2139067679, 
the heap memory usage is 4000 * 200Bytes. If a Spark job has 20,000 reduce 
partitions, it will occupy 14.9GB of heap memory. Assuming the actual size of 
these blocks is very small, so they will never trigger a flush operation. This 
is just the case with one Spark job. If more extreme Spark jobs pile up, I 
think the Uniffle server will face increasingly severe GC pauses, or even OOM. 
Even more extreme, if a Spark job has 200,000 reduce partitions, it will occupy 
149GB of heap memory. Maybe more reduce partitions, like 2,000,000 reduce 
partitions?


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