XiaoHongbo-Hope opened a new pull request, #8738:
URL: https://github.com/apache/paimon/pull/8738

   ## Purpose
   
   `ray.data.join` shuffles both sides. When two tables are sorted/clustered by 
the join key, that shuffle is avoidable: cut the key space into ranges from 
per-file min/max stats in the manifest, then read and join each range in its 
own Ray task — no global shuffle. Complements `bucket_join` (which needs 
co-bucketed tables) for the sorted-but-not-co-bucketed case.
   
   Half-open ranges plus an in-memory clip keep every matching pair produced 
exactly once regardless of range count; splits with no usable stats fall back 
to joining every range. Supports `on=` or `left_on`/`right_on`, inner join. 
Shared driver/worker helpers are factored into `join_common` and reused by 
`bucket_join`.
   
   ## Tests
   
   `ray_range_join_test.py`; flake8 clean. The exactly-once planning invariant 
was additionally verified over randomized range/skew/null trials.
   


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