apache / apache/iceberg-python
ArrowScan to_table fails if the data is mixed between dict-encoded strings and plain strings.
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描述
### Apache Iceberg version
0.11.0 (latest release)
### Please describe the bug 🐞
We have recently updated our functions to call the pyiceberg table.append() function with dict encoded arrow tables. Now we have in our iceberg tables mixed data from before this change, (where our data still is stored as string) and after the change, where the data is stored as dict-encoded strings.
If we now call to_arrow() of a DataScan class, on this table we get this error:
```
pyarrow.lib.ArrowTypeError: Unable to merge: Field col has incompatible types: string vs dictionary
```
Here is a minimal example that reproduces this error:
```python
from pyiceberg.io.pyarrow import ArrowScan
from pyiceberg.table import ALWAYS_TRUE
from pyiceberg.schema import Schema
from pyiceberg.types import NestedField
from pyiceberg.types import StringType
import pyarrow as pa
def create_scan_with_mixed_dict_encode_not_encode() -> ArrowScan:
schema = Schema(
NestedField(field_id=1, name="col", field_type=StringType(), required=False)
)
class FakeTableMetadata:
def schema(self) -> Schema:
return schema
scan = ArrowScan(table_metadata=FakeTableMetadata(),
io=object(),
projected_schema=schema,
row_filter=ALWAYS_TRUE)
def _batches_for_repro(self, _tasks):
str_values = pa.array(["a"], type=pa.string())
yield pa.record_batch([str_values], names=["col"])
yield pa.record_batch([str_values.dictionary_encode()], names=["col"])
ArrowScan.to_record_batches = _batches_for_repro
return scan
if __name__ == "__main__":
scan = create_scan_with_mixed_dict_encode_not_encode()
arrow_table = ArrowScan.to_table(scan, tasks=[])
```
I am happy to provide a bugfix PR, but I need a small guidance on the best approach.
One idea is to cast each batch in to_table to the arrow_schema. The more performant way is to check for each batch, if the schema is different. If they are different, then find the dict_encoded col and only cast that one to string.
### Willingness to contribute
- [x] 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
貢獻指南
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研究方向
從最小重現開始,檢查 ArrowScan.to_table 以及 issue 中所示的 to_record_batches 入口點。驗證如何合併混合了一般字串和字典編碼值的批次。完成標準是:重現過程在沒有 ArrowTypeError 的情況下完成,並回傳包含預期字串欄位的 Arrow 表格。
由索引模型根據 Issue 內容生成。
評估
- 技術堆疊
- python
- 領域
- databases
- Issue 類型
- 缺陷
- 難度
- 3/5
- 預估耗時
- 1-2 天
- 活躍度
- 冷清
- 描述清晰度
- 基本清楚
- 新手友好度
- 55/100