Github user rtreffer commented on a diff in the pull request:
https://github.com/apache/spark/pull/6796#discussion_r33133591
--- 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 --
Under the assumption that all values will use the full length, yes.
But at some point the overhead of the length is low compared to the
overhead if someone specifies just the upper bound of values.
I have to check if it really uses 4 bytes for BINARY. I'd then raise the
threshold to ~40 bytes length. (meaning <=10% worst case overhead before
compression)
It won't simplify the decoding/writing though, because the <=18 case is
used for long decoding.
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