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Rationale for this change
run_end_decodelacks a kernel for run-end encoded arrays whose physical values are dictionary-encoded. Such arrays are valid Arrow IPC data, but bothrun_end_decodeandto_pandas()fail with a missing-kernel error.Fixes #55489.
What changes are included in this PR?
Register dictionary-valued REE decoding. Expand only the dictionary indices using the existing primitive decoder, then reconstruct the result with the unchanged dictionary and dictionary type. This retains dictionary ordering and index width without re-encoding values.
Add regression cases covering all three run-end widths, multiple dictionary index widths, nulls, slices, chunks, empty arrays, and Python/pandas conversion.
Are these changes tested?
Regression tests are included but not executed yet: the environment used to prepare this change does not have a built Arrow C++/PyArrow checkout. The patch was structurally reviewed and compared against the upstream source; compile and runtime test results remain pending.
Are there any user-facing changes?
Yes. Valid run-end encoded dictionary arrays can be decoded and converted to pandas.
Was AI used for this PR?
PR code and description written by:
Reviewed before submission by:
The code and tests were prepared with AI assistance and inspected for the missing kernel, expected output type, null handling and slice behavior. They still require compilation and targeted test execution.