Avro EnumReader.skip() does not advance the decoder
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Assessment
- Difficulty
- 1/5
- Estimated time
- Under an hour
- Newbie friendliness
- 92/100
Research direction
Start in pyiceberg/avro/resolver.py at EnumReader.skip() and trace the Avro projection path for omitted enum fields. Reproduce the manifest read with status projected out, then verify that the following snapshot_id is decoded correctly rather than as the enum value. Done means the decoder advances past the omitted enum field.
Written by the indexing model from the issue text.
Description
Apache Iceberg version
main (development)
Please describe the bug 🐞
Description
EnumReader.skip() in pyiceberg/avro/resolver.py currently does nothing:
def skip(self, decoder: BinaryDecoder) -> None:
pass
When an enum field is omitted from the requested read schema, the Avro reader calls skip() for that field. Because the decoder is not advanced, the next field is read from the enum field's bytes.
This causes incorrect values when reading selected Avro records, including Iceberg manifest files.
Reproduction
Create an Iceberg table, append one row, and read its manifest with the status enum field projected out:
from tempfile import TemporaryDirectory
import pyarrow as pa
from pyiceberg.avro.file import AvroFile
from pyiceberg.catalog.memory import InMemoryCatalog
from pyiceberg.manifest import MANIFEST_ENTRY_SCHEMAS, ManifestEntryStatus
from pyiceberg.schema import Schema
from pyiceberg.types import IntegerType, NestedField
with TemporaryDirectory() as warehouse:
# Use a temporary local warehouse so the example does not modify external data.
catalog = InMemoryCatalog("bug-simulation", warehouse=warehouse)
catalog.create_namespace("demo")
# Create a simple Iceberg table with two required integer columns.
table = catalog.create_table(
"demo.events",
schema=Schema(
NestedField(1, "id", IntegerType(), required=True),
NestedField(2, "value", IntegerType(), required=True),
),
)
# Build a PyArrow table whose types and nullability match the Iceberg schema.
data = pa.Table.from_pylist(
[{"id": 1, "value": 123}],
schema=pa.schema(
[
pa.field("id", pa.int32(), nullable=False),
pa.field("value", pa.int32(), nullable=False),
]
),
)
# Write the data file and commit a snapshot containing a manifest.
table.append(data)
# Find the manifest generated by the append operation.
snapshot = table.current_snapshot()
manifest = snapshot.manifests(table.io)[0]
# The manifest schema starts with field ID 0, the status enum.
file_schema = MANIFEST_ENTRY_SCHEMAS[2]
# Build a projected schema that omits status but keeps the later fields.
# This makes the Avro reader skip status before reading snapshot_id.
projected_fields = []
for field in file_schema.fields:
if field.field_id != 0:
projected_fields.append(field)
projected_schema = Schema(*projected_fields)
with AvroFile(
table.io.new_input(manifest.manifest_path),
read_schema=projected_schema,
# Tell the resolver that field ID 0 should be converted to an enum.
# The field is projected out, so EnumReader.skip() handles it.
read_enums={0: ManifestEntryStatus},
) as reader:
entries = list(reader)
# Because status was projected out, the first returned field is snapshot_id.
decoded_snapshot_id = entries[0][0]
# the decoder is still positioned at status and returns 1.
if decoded_snapshot_id != snapshot.snapshot_id:
raise RuntimeError(
f"Expected snapshot_id {snapshot.snapshot_id}, "
f"got {decoded_snapshot_id}"
)
Actual behavior
The decoded snapshot_id is incorrectly read as 1.
1 is the encoded manifest status value. This shows that the decoder did not skip the enum value before reading snapshot_id.
Expected behavior
The decoder should skip the enum value and decode the following snapshot_id correctly.
Proposed fix
Delegate skipping to the wrapped reader:
def skip(self, decoder: BinaryDecoder) -> None:
self.reader.skip(decoder)
Willingness to contribute
- I can contribute a fix for this bug independently
- 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
- Dominant language
- Python
- Stars
- 1.1k
- Forks
- 589
- Avg merge
- 2d 2h
- Merged PRs (30d)
- 70
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