MaxGekk commented on code in PR #55923:
URL: https://github.com/apache/spark/pull/55923#discussion_r3387841073
##########
sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetVectorUpdaterBenchmark.scala:
##########
@@ -264,6 +264,10 @@ object ParquetVectorUpdaterBenchmark extends BenchmarkBase
{
TimestampNTZType,
descriptor(PrimitiveTypeName.INT32, LogicalTypeAnnotation.dateType()),
longVec, intBytes)
+ addReadValuesCase(benchmark, "LongAsNanosUpdater (TimeType)",
Review Comment:
The class-level Scaladoc for Group B (`IntegerToLong, IntegerToDouble,
FloatToDouble, DateToTimestampNTZ, DowncastLong` on lines 47–48) doesn't
include `LongAsNanosUpdater`. Please add it to the Group B listing.
##########
sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetVectorUpdaterBenchmark.scala:
##########
@@ -264,6 +264,10 @@ object ParquetVectorUpdaterBenchmark extends BenchmarkBase
{
TimestampNTZType,
descriptor(PrimitiveTypeName.INT32, LogicalTypeAnnotation.dateType()),
longVec, intBytes)
+ addReadValuesCase(benchmark, "LongAsNanosUpdater (TimeType)",
+ TimeType(),
+ descriptor(PrimitiveTypeName.INT64),
Review Comment:
In production, `TimeType` columns are written as `INT64` with
`timeType(false, TimeUnit.MICROS)` (`ParquetSchemaConverter.scala:695–697`).
The class doc says the benchmark exercises "the full configuration matrix
(logical-type annotation, rebase mode, timezone) the production decoder uses".
Suggest using the production annotation:
```suggestion
descriptor(PrimitiveTypeName.INT64,
LogicalTypeAnnotation.timeType(false, LogicalTypeAnnotation.TimeUnit.MICROS)),
```
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