Cabeda opened a new issue, #1804:
URL: https://github.com/apache/iceberg-python/issues/1804
### Apache Iceberg version
0.9.0 (latest release)
### Please describe the bug 🐞
Hi,
Not sure if this is a bug but worst case scenario this might be something
for other to look up into in the future.
I've created a table like follows using pyiceberg
```python
schema = Schema(
NestedField(field_id=1, name="bk_id",
field_type=StringType(), required=False),
NestedField(field_id=2, name="possnr",
field_type=StringType(), required=False),
NestedField(field_id=3, name="posg",
field_type=StringType(), required=False),
NestedField(field_id=4, name="posp",
field_type=StringType(), required=False),
NestedField(field_id=5, name="aendnr_hinzu",
field_type=StringType(), required=False),
NestedField(field_id=6, name="bk_prod",
field_type=StringType(), required=False),
NestedField(field_id=7, name="bend",
field_type=StringType(), required=False),
NestedField(field_id=8, name="prod_ort",
field_type=StringType(), required=False),
NestedField(field_id=9, name="erzvgr",
field_type=StringType(), required=False),
NestedField(field_id=10, name="vkgr_art",
field_type=StringType(), required=False),
NestedField(field_id=11, name="sachnummernart",
field_type=StringType(), required=False),
NestedField(field_id=19, name="bza_log",
field_type=StringType(), required=False),
NestedField(field_id=20, name="eins_key",
field_type=StringType(), required=False),
NestedField(field_id=21, name="akkz",
field_type=StringType(), required=False),
NestedField(field_id=22, name="werk_zust",
field_type=StringType(), required=False),
NestedField(field_id=23, name="aendnr_entf",
field_type=StringType(), required=False),
NestedField(field_id=24, name="bearb_kz",
field_type=StringType(), required=False),
NestedField(field_id=25, name="pruefkz",
field_type=StringType(), required=False),
NestedField(field_id=26, name="drukz",
field_type=StringType(), required=False),
NestedField(field_id=27, name="kswkz",
field_type=StringType(), required=False),
NestedField(field_id=28, name="erskz",
field_type=StringType(), required=False),
NestedField(field_id=29, name="wdat",
field_type=TimestampType(), required=False),
NestedField(field_id=30, name="aedat",
field_type=TimestampType(), required=False),
NestedField(field_id=31, name="aeuser",
field_type=StringType(), required=False),
NestedField(field_id=32, name="pgm_name",
field_type=StringType(), required=False),
NestedField(field_id=33, name="kast_kz",
field_type=StringType(), required=False),
NestedField(field_id=34, name="rnum",
field_type=StringType(), required=False),
NestedField(field_id=35, name="mbma",
field_type=StringType(), required=False),
NestedField(field_id=36, name="mbma_confidence",
field_type=DoubleType(), required=False),
NestedField(field_id=37, name="kost",
field_type=StringType(), required=False),
NestedField(field_id=38, name="kost_confidence",
field_type=DoubleType(), required=False),
NestedField(field_id=39, name="stand",
field_type=StringType(), required=False),
NestedField(field_id=40, name="stand_confidence",
field_type=DoubleType(), required=False),
NestedField(field_id=41, name="inference_date",
field_type=TimestampType(), required=False),
NestedField(field_id=42, name="verified",
field_type=BooleanType(), required=False),
NestedField(field_id=43, name="id", field_type=StringType(),
required=True),
)
```
I've been able to do multiple appends to the table using pyiceberg with no
issues.
Now, to run some tests and prepare to use the new upsert operation, I
decided do append a row with id = 'dummy_id', and then run a scan filtering by
it. When I do the scan through AWS Athena I see the row, however, when doing
the scan with `dummy = table.scan(row_filter=EqualTo("id", 'dummy_id'))` I get
`list index out of range`. This seems to be because pyiceberg isn't able to
retrieve the row.
Here is the code I have setup to replicate the issue:
```python
from pyiceberg.expressions import EqualTo
import pyarrow as pa
df = pa.Table.from_pydict(
{
"bk_id": ["BK123456"],
"possnr": ["POS789"],
"posp": ["777"],
"posg": ["888"],
"bk_prod": ["PROD456"],
"bend": ["B789"],
"prod_ort": ["C"],
"erzvgr": ["E001"],
"vkgr_art": ["VA123"],
"sachnummernart": ["S456"],
"bza_log": ["BL789"],
"akkz": ["AK123"],
"werk_zust": ["WZ456"],
"aendnr_entf": ["AE789"],
"bearb_kz": ["BK001"],
"pruefkz": ["PK002"],
"drukz": ["D003"],
"kswkz": ["K004"],
"eins_key": [1],
"erskz": ["E005"],
"aeuser": ["user123"],
"pgm_name": ["program456"],
"kast_kz": ["KK789"],
"rnum": ["R001"],
"mbma": ["M123"],
"mbma_confidence": [0.85],
"kost": ["K456"],
"kost_confidence": [0.92],
"stand": ["S789"],
"stand_confidence": [0.78],
"inference_date": [pd.Timestamp.now()],
"verified": [False],
"id": ["dummy_id"],
}
)
catalog = load_catalog(
"glue",
**{
"type": "glue",
"warehouse": warehouse_path,
"downcast-ns-timestamp-to-us-on-write": True,
},
)
table_identifier = "database_name.table_name"
table = catalog.load_table(table_identifier)
table.append(df)
dummy = table.scan(row_filter=EqualTo("id", 'dummy_id'))
dummy.to_arrow()
```
Is there something I'm doing wrong?
### Willingness to contribute
- [ ] I can contribute a fix for this bug independently
- [x] I would be willing to contribute a fix for this bug with guidance from
the Iceberg community
- [ ] I cannot contribute a fix for this bug at this time
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