[jira] [Created] (ARROW-17828) Large strings cause ArrowInvalid: offset overflow while concatenating arrays

["Ben Epstein (Jira)" <ji...@apache.org>]

Ben Epstein created ARROW-17828:
-----------------------------------

             Summary: Large strings cause ArrowInvalid: offset overflow while concatenating arrays
                 Key: ARROW-17828
                 URL: https://issues.apache.org/jira/browse/ARROW-17828
             Project: Apache Arrow
          Issue Type: Bug
          Components: Python
    Affects Versions: 9.0.0
            Reporter: Ben Epstein


When working with medium-sized datasets that have very long strings, arrow fails when trying to operate on the strings. The root is the `combine_chunks` function.

Here is a minimally reproducible example

 
{code:java}
import numpy as np
import pyarrow as pa

# Create a large string
x = str(np.random.randint(low=0,high=1000, size=(30000,)).tolist())
t = pa.chunked_array([x]*20_000)
# Combine the chunks into large string array - fails
combined = t.combine_chunks(){code}
 

 

I get the following error
{code:java}
--------------------------------------------------------------------------- ArrowInvalid Traceback (most recent call last) /var/folders/x6/00594j4s2yv3swcn98bn8gxr0000gn/T/ipykernel_95780/4128956270.py in <module> ----> 1 z=t.combine_chunks()
~/.venv/lib/python3.7/site-packages/pyarrow/table.pxi in pyarrow.lib.ChunkedArray.combine_chunks() 
~/.venv/lib/python3.7/site-packages/pyarrow/array.pxi in pyarrow.lib.concat_arrays() ~/Documents/Github/dataquality/.venv/lib/python3.7/site-packages/pyarrow/error.pxi in pyarrow.lib.pyarrow_internal_check_status() ~.venv/lib/python3.7/site-packages/pyarrow/error.pxi in pyarrow.lib.check_status() 
ArrowInvalid: offset overflow while concatenating arrays {code}
 

 

With smaller strings or smaller arrays this works fine.

 
{code:java}
x = str(np.random.randint(low=0,high=1000, size=(10,)).tolist())
t = pa.chunked_array([x]*1000)
combined = t.combine_chunks(){code}

The first example that fails takes a few minutes to run. If you'd like a faster example for experimentation, you can use `vaex` to generate the chunked array much faster. This will throw the identical error and will run about 1 second.
{code:java}
import vaex
import numpy as np

n = 50_000
x = str(np.random.randint(low=0,high=1000, size=(30_000,)).tolist())
df = vaex.from_arrays(
    id=list(range(n)),
    y=np.random.randint(low=0,high=1000,size=n)
)
df["text"] = vaex.vconstant(x, len(df))
# text_chunk_array is now a pyarrow.lib.ChunkedArray
text_chunk_array = df.text.values
x = text_chunk_array.combine_chunks() {code}
 

 

 



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