[jira] [Created] (ARROW-8799) [C++][Dataset] Reading list column as nested dictionary segfaults

[Joris Van den Bossche (Jira)]

Joris Van den Bossche created ARROW-8799:
--------------------------------------------

             Summary: [C++][Dataset] Reading list column as nested dictionary 
segfaults
                 Key: ARROW-8799
                 URL: https://issues.apache.org/jira/browse/ARROW-8799
             Project: Apache Arrow
          Issue Type: Bug
          Components: C++
            Reporter: Joris Van den Bossche


Python example:

{code}
import pyarrow as pa
import pyarrow.parquet as pq  
from pyarrow.tests import util                                                  
                                                                                
                                           
                                                                                
                                                                                
      
repeats = 10 
nunique = 5 

data = [ 
    [[util.rands(10)] for i in range(nunique)] * repeats, 
] 
table = pa.table(data, names=['f0'])                                            
                                                                                
                                       

pq.write_table(table, "test_dictionary.parquet")
{code}

Reading with the parquet code works:

{code}
>>> pq.read_table("test_dictionary.parquet", read_dictionary=['f0.list.item'])  
>>>                                                                             
>>>                                                     
pyarrow.Table
f0: list<item: dictionary<values=string, indices=int32, ordered=0>>
  child 0, item: dictionary<values=string, indices=int32, ordered=0>
{code}

but doing the same with the datasets API segfaults:

{code}
>>> fmt = 
>>> ds.ParquetFileFormat(read_options=dict(dictionary_columns=["f0.list.item"]))
>>> dataset = ds.dataset("test_dictionary.parquet", format=fmt)                 
>>>                                                       
>>> dataset.to_table()      
Segmentation fault (core dumped)
{code}



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