viirya commented on PR #57104:
URL: https://github.com/apache/spark/pull/57104#issuecomment-4928769189

   Closing this PR. Rationale:
   
   During review of the sibling PRs, concerns were raised about the 
maintainability of routing data values through NumPy (behavior across the 
supported arrow/numpy version matrix, and keeping the "no type coercion" 
invariant guarded by tests over time). While the conversions here are 
exactness-tested — the object-dtype conversion for strings/binary can only 
produce `str`/`bytes`/`None`, and nullable numerics are filled and restored 
from the validity bitmap rather than going through a float representation — 
this is also precisely the layer that apache/arrow#50327 implements properly in 
C, planned for PyArrow 25.0.1 per the Arrow dev-list discussion.
   
   With the version gate added in SPARK-58019 (#57099), Spark automatically 
uses PyArrow's native conversion once the installed PyArrow contains that fix — 
so the leaf-level speedup reaches users through a PyArrow upgrade rather than 
through NumPy-based code maintained here. The remaining Spark-side PRs are 
scoped to what Arrow cannot do for Spark: SPARK-58019/SPARK-58024 (bulk 
offsets/validity slicing; no data values through NumPy) and SPARK-58050 (bulk 
result assembly; no NumPy at all).
   
   For the record: this PR gave flat string 196ms→20ms and int64 99ms→28ms per 
1M rows, and its removal lowers the struct/map gains in SPARK-58024 from 
5.2x/6.8x to 2.0x/2.7x until the PyArrow fix ships. We accept that interim gap 
in exchange for the smaller maintenance surface.


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