[core][common]support row range read of a DataSplit - #9705

Why not just use IndexedSplit?

The critical RowRange use case is slicing the stream after a filter — e.g. "give me the 1000th–2000th matching rows for training." Even composed with a filter, IndexedSplit only ANDs two physical-position bitmaps; it never renumbers rows into a
post-filter effective sequence, so it cannot express "the N-th row after filtering."

This is exactly what AbstractDataTableRead.outerWrap encodes:

• RowRange + filter (executeFilter): outerWrap=true — RowRange wraps outside the filter, slicing the filtered effective stream.
• IndexedSplit + filter: both reduce to physical-position bitmaps ANDed together — no "post-filter renumbering" step.

The AI training-shard use case (why RowRange exists)

In AI / ML data loading, a common pattern is sharding a dataset by effective sample position:

• A training job with worldSize=W, rank=R wants its local shard — the rows at effective positions [R*N, (R+1)*N - 1] of the dataset.
• With filters active (e.g. quality filters, column predicates) or deletion vectors, the "effective row order" is the filtered/compacted sequence. Each worker must receive a deterministic, contiguous slice of that sequence, not of the raw file layout.
• RowRange models exactly this: a single contiguous [start, end] in the 0-based effective-row space of a split. The reader either pushes it down as a selection bitmap (parquet, full-scan — no extra rows decoded) or wraps a single RangeSkipReader over
  the filtered output (filter/DV/ORC/merge-tree) to skip start and take count.

IndexedSplit cannot express this:

• It cuts physical row-ids, which have no relation to the post-filter effective order — worker rank=R wouldn't get a contiguous slice of matching rows.
• It requires firstRowId (so plain append tables are out) or a pre-built global index.
• For merge-tree primary-key tables, physical position ≠ output order, so the shard would be scrambled.

Conclusion

IndexedSplit and RowRange are complementary, not interchangeable:

• IndexedSplit: read a discrete set of physical row-ids (vector search / global-index hits), AND-composed with filters in the physical-position space, requires row-ids or a pre-built index, excludes append tables / post-filter slicing / merge-output
  slicing.
• RowRange: read a contiguous slice in effective-row space (AI training shards / pagination / range queries), applied as skip+limit over the filtered effective stream, works across append / primary-key / DE tables, no pre-built index needed.

RowRange was introduced precisely to cover IndexedSplit's blind spots — append tables, post-filter effective-row slicing, and merge-output slicing — all validated by tests in this PR (testAppendOrcRowRange..., testRowRangeWithFilterWrapsOutsideFilter,
testPrimaryKeyRowRangeOverMergeRead). They cover behavior IndexedSplit cannot express, so RowRange cannot be replaced by it.