Fokko commented on code in PR #1799:
URL: https://github.com/apache/iceberg-python/pull/1799#discussion_r2000526902
##########
pyiceberg/io/pyarrow.py:
##########
@@ -2335,9 +2340,18 @@ def data_file_statistics_from_parquet_metadata(
col_aggs[field_id] = StatsAggregator(
stats_col.iceberg_type, statistics.physical_type,
stats_col.mode.length
)
-
- col_aggs[field_id].update_min(statistics.min)
- col_aggs[field_id].update_max(statistics.max)
+ matches=DECIMAL_REGEX.search(str(stats_col.iceberg_type))
+ if matches and statistics.physical_type !=
"FIXED_LEN_BYTE_ARRAY":
+ precision=int(matches.group(1))
+ scale=int(matches.group(2))
+ local_context = Context(prec=precision)
+ decoded_min =
local_context.create_decimal(Decimal(statistics.min_raw)/ (10 ** scale))
+ decoded_max =
local_context.create_decimal(Decimal(statistics.max_raw)/ (10 ** scale))
+ col_aggs[field_id].update_min(decoded_min)
+ col_aggs[field_id].update_max(decoded_max)
+ else:
+ col_aggs[field_id].update_min(statistics.min)
+ col_aggs[field_id].update_max(statistics.max)
Review Comment:
When we `isinstanceof` the `stats_col.iceberg_Type` as a `DecimalType`, then
we have access to the `scale` and `precision`.
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