EungsopYoo commented on PR #7291:
URL: https://github.com/apache/hbase/pull/7291#issuecomment-3787316067

   @VladRodionov 
   Thank you for your comments. I’d like to respond to the questions you raised.
   
   > * 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.
   
   Although it will be clearer once we run some tests, under high-churn 
workloads I expect RowCache, like BlockCache, to experience significant GC 
pressure. In such cases, it would likely be more appropriate not to use 
RowCache.
   
   > * 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.
   
   That’s correct. Because the overhead is large, I plan to set the default 
size of RowCache to 2% of the heap, which is relatively much smaller than the 
40% heap size typically allocated to BlockCache.
   
   > * 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.
   
   In this PR, I am not considering caching for sparse rows and am focusing 
only on caching full rows. Support for sparse row caching can be considered 
later.


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