xinrong-databricks opened a new pull request, #36076:
URL: https://github.com/apache/spark/pull/36076

   ### What changes were proposed in this pull request?
   Support `return_indexer` parameter of `Index/MultiIndex.sort_values`.
   
   Note that this method returns indexer as a pandas-on-Spark index while 
pandas returns it as a list. That's because indexer in pandas-on-Spark may not 
fit in memory.
   
   ### Why are the changes needed?
   To reach parity with pandas.
   
   
   ### Does this PR introduce _any_ user-facing change?
   Yes.  `return_indexer` parameter of `Index/MultiIndex.sort_values` is 
supported as below.
   
   Index
   ```py
           >>> idx = ps.Index([10, 100, 1, 1000])
           >>> idx
           Int64Index([10, 100, 1, 1000], dtype='int64')
   
           >>> idx.sort_values(ascending=False, return_indexer=True)
           (Int64Index([1000, 100, 10, 1], dtype='int64'), Int64Index([3, 1, 0, 
2], dtype='int64'))
   ```
   MultiIndex
   ```py
           >>> psidx = ps.MultiIndex.from_tuples([('a', 'x', 1), ('c', 'y', 2), 
('b', 'z', 3)])
           >>> psidx
           MultiIndex([('a', 'x', 1),
                       ('c', 'y', 2),
                       ('b', 'z', 3)],
                      )
   
           >>> psidx.sort_values(ascending=False, return_indexer=True)
           (MultiIndex([('c', 'y', 2),
                       ('b', 'z', 3),
                       ('a', 'x', 1)],
                      ), Int64Index([1, 2, 0], dtype='int64'))
   ```
   
   ### How was this patch tested?
   Unit test.
   


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