durgaprasadml commented on issue #56331:
URL: https://github.com/apache/spark/issues/56331#issuecomment-4625403478

   Thanks for raising this — the concern makes sense.
   
   The current approx_top_k naming strongly implies approximate ranking 
semantics, while the underlying implementation is actually based on the Apache 
DataSketches Frequent Items / Heavy Hitters sketch family, which provides 
threshold-based guarantees rather than true top-k guarantees.
   
   As demonstrated in the example above, the sketch can legitimately return:
   
   * fewer than k items
   * or even zero items
   
   depending on the stream distribution and configured sketch size, while still 
behaving correctly according to the sketch guarantees.
   
   Using terminology aligned with the DataSketches documentation (frequent 
items / heavy hitters) would make the behavior much clearer to users and reduce 
incorrect expectations around strict top-k semantics.
   
   I’d like to work on this issue by:
   
   * introducing clearer canonical naming
   * preserving backward compatibility through aliases/deprecation paths
   * improving user/developer documentation around sketch guarantees and query 
modes
   * adding regression tests for edge cases like empty results


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