kolfild26 commented on issue #44513:
URL: https://github.com/apache/arrow/issues/44513#issuecomment-2544141432
@zanmato1984
Stacktrace:
```bash
Dec 16 01:07:44 kernel: python[37938]: segfault at 7f3004626050 ip
00007f3fc25441cd sp 00007f3f10b09018 error 4 in
libarrow.so.1801[7f3fc1670000+2269000]
Dec 16 01:07:44 kernel: python[37971]: segfault at 7f3004626050 ip
00007f3fc25441db sp 00007f3f002b0018 error 4
Dec 16 01:07:44 kernel: python[37961]: segfault at 7f3004626050 ip
00007f3fc25441cd sp 00007f3f052d0018 error 4 in
libarrow.so.1801[7f3fc1670000+2269000]
Dec 16 01:07:44 kernel: in libarrow.so.1801[7f3fc1670000+2269000]
Dec 16 01:07:44 kernel: python[37957]: segfault at 7f3004626050 ip
00007f3fc25441db sp 00007f3f072d8018 error 4
Dec 16 01:07:44 kernel: python[37940]: segfault at 7f3004626050 ip
00007f3fc25441cd sp 00007f3f0fb07018 error 4
Dec 16 01:07:44 kernel: in libarrow.so.1801[7f3fc1670000+2269000]
Dec 16 01:07:44 kernel: in libarrow.so.1801[7f3fc1670000+2269000]
Dec 16 01:07:44 kernel: python[37974]: segfault at 7f3004626050 ip
00007f3fc25441cd sp 00007f3d18f6d018 error 4 in
libarrow.so.1801[7f3fc1670000+2269000]
Dec 16 01:07:44 kernel: python[37966]: segfault at 7f3004626050 ip
00007f3fc25441db sp 00007f3f02abf018 error 4
Dec 16 01:07:44 kernel: python[37951]: segfault at 7f3004626050 ip
00007f3fc25441db sp 00007f3f0a2ec018 error 4
Dec 16 01:07:44 kernel: python[37973]: segfault at 7f3004626050 ip
00007f3fc25441cd sp 00007f3efb7fe018 error 4
Dec 16 01:07:44 kernel: in libarrow.so.1801[7f3fc1670000+2269000]
Dec 16 01:07:44 kernel: in libarrow.so.1801[7f3fc1670000+2269000]
Dec 16 01:07:44 kernel: python[37953]: segfault at 7f3004626050 ip
00007f3fc25441db sp 00007f3f092e6018 error 4
Dec 16 01:07:44 kernel: in libarrow.so.1801[7f3fc1670000+2269000]
Dec 16 01:07:44 kernel: in libarrow.so.1801[7f3fc1670000+2269000]
Dec 16 01:07:44 abrt-hook-ccpp: Process 35963 (python3.10) of user 1000
killed by SIGSEGV - dumping core
```
Here is the tables's statistics:
<details>
<summary>Script to get stats</summary>
```python
import pyarrow as pa
import pyarrow.compute as pc
import pandas as pd
import pyarrow.types as patypes
def get_column_distributions(table):
distributions = {}
total_rows = table.num_rows
for column in table.schema.names:
col_data = table[column]
null_count = pc.sum(pc.is_null(col_data)).as_py()
null_percentage = (null_count / total_rows) * 100 if total_rows > 0
else 0
# Compute the cardinality (unique count / total count)
unique_count =
pc.count_distinct(col_data.filter(pc.is_valid(col_data))).as_py()
cardinality_percentage = round((unique_count / total_rows)*100,3) if
total_rows > 0 else 0
if patypes.is_integer(col_data.type) or
patypes.is_floating(col_data.type):
stats = {
"count": pc.count(col_data).as_py(),
"nulls": null_count,
"null_percentage": null_percentage,
"cardinality_percentage": cardinality_percentage,
"min": pc.min(col_data).as_py(),
"max": pc.max(col_data).as_py(),
}
elif patypes.is_string(col_data.type) or
patypes.is_binary(col_data.type):
value_counts =
pc.value_counts(col_data.filter(pc.is_valid(col_data)))
stats = {
"nulls": null_count,
"null_percentage": null_percentage,
"cardinality_percentage": cardinality_percentage,
"value_counts": value_counts.to_pandas().to_dict("records"),
}
else:
stats = {
"nulls": null_count,
"null_percentage": null_percentage,
"cardinality_percentage": cardinality_percentage,
"message": f"Statistics not supported for type:
{col_data.type}"
}
distributions[column] = stats
return distributions
```
</details>
<details>
<summary>small</summary>
</details>
<details>
<summary>large</summary>
</details>
Would it be easier if I attached the tables here?
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