VladRodionov commented on PR #7291:
URL: https://github.com/apache/hbase/pull/7291#issuecomment-3746782600

   While reading through the issue and thinking about possible design 
trade-offs, a few questions came to mind that may be worth considering as the 
implementation evolves:
   + Heap pressure: using Java-heap–resident structures (or reusing BucketCache 
metadata paths) may increase GC pressure under some workloads. ZGC certainly 
helps here, but I’m curious how this is expected to behave for row-sized 
objects with high churn.
   + Metadata overhead: for cache entries on the order of a single row, the 
relative metadata overhead can become significant compared to the payload. It 
would be interesting to understand how this is being evaluated or measured in 
the current approach.
   + Sparse row access: some applications primarily care about a subset of row 
data (for example, only the latest versions of selected cells). Google 
Bigtable’s row cache supports sparse rows — are similar access patterns in 
scope here, or is the focus on full-row caching?
   + In-place mutation: supporting sparse rows often implies updating cached 
entries in place so the cache always reflects the most recent version of the 
row. I’m curious whether this is within the intended scope or something to 
consider later.
   
   These aren’t meant as blockers — just questions around the design space and 
trade-offs. Looking forward to following the progress on this issue.
   


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