kevinjqliu commented on issue #1229:
URL:
https://github.com/apache/iceberg-python/issues/1229#issuecomment-2414939042
> Most of the time is spent processing the manifests record-by-record and
converting each record to a dict
Heres a snippet using threads to parallelize both reading the manifest files
and conversion to records.
This is generated by Claude, so please double-check.
```
def get_message_table_files(
table: pyiceberg.table.Table,
) -> pa.Table:
schema = table.metadata.schema()
snapshot = table.current_snapshot()
if not snapshot:
return pa.Table.from_pylist([], schema=_FILES_SCHEMA)
with ThreadPoolExecutor() as pool:
return pa.Table.from_batches(
pool.map(
partial(_process_manifest, schema, table.io),
snapshot.manifests(table.io),
),
schema=_FILES_SCHEMA,
)
def _process_manifest(
table_schema: Schema,
io: FileIO,
manifest: ManifestFile,
) -> pa.RecordBatch:
ts_field = table_schema.find_field('ts')
entries = list(manifest.fetch_manifest_entry(io))
valid_entries = [
entry for entry in entries
if entry.data_file.file_format == FileFormat.PARQUET
and entry.status != ManifestEntryStatus.DELETED
]
with ThreadPoolExecutor() as pool:
rows = list(pool.map(
partial(_process_entry, ts_field),
valid_entries
))
return pa.RecordBatch.from_pylist(rows, schema=_FILES_SCHEMA)
def _process_entry(ts_field: Schema.Field, entry: ManifestEntry) -> Dict:
return {
'path': entry.data_file.file_path,
'event_id': entry.data_file.partition.event_id,
'ts_min': from_bytes(
ts_field.field_type,
entry.data_file.lower_bounds.get(ts_field.field_id),
),
'ts_max': from_bytes(
ts_field.field_type,
entry.data_file.upper_bounds.get(ts_field.field_id),
),
}
```
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