Github user liancheng commented on a diff in the pull request: https://github.com/apache/spark/pull/6796#discussion_r33132365 --- Diff: sql/core/src/main/scala/org/apache/spark/sql/parquet/ParquetTypes.scala --- @@ -229,11 +231,15 @@ private[parquet] object ParquetTypesConverter extends Logging { case LongType => Some(ParquetTypeInfo(ParquetPrimitiveTypeName.INT64)) case TimestampType => Some(ParquetTypeInfo(ParquetPrimitiveTypeName.INT96)) case DecimalType.Fixed(precision, scale) if precision <= 18 => - // TODO: for now, our writer only supports decimals that fit in a Long Some(ParquetTypeInfo(ParquetPrimitiveTypeName.FIXED_LEN_BYTE_ARRAY, Some(ParquetOriginalType.DECIMAL), Some(new DecimalMetadata(precision, scale)), Some(BYTES_FOR_PRECISION(precision)))) + case DecimalType.Fixed(precision, scale) => + Some(ParquetTypeInfo(ParquetPrimitiveTypeName.BINARY, --- End diff -- Using `BINARY` here conforms to Parquet format spec. But according to the spec, `FIXED_LENGTH_BYTE_ARRAY` with different length can also be used to store decimals with different precisions. From the perspective of storage efficiency, `FIXED_LENGTH_BYTE_ARRAY` is probably more preferable, since `BINARY` has variable length and needs 4 extra bytes to encode the length (before being encoded and compressed). Another benefit here is that we can just unify cases for precision <= 18 and precision > 18.
--- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- --------------------------------------------------------------------- To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org