cloud-fan commented on a change in pull request #26102: [SPARK-29448][SQL]
Support the `INTERVAL` type by Parquet datasource
URL: https://github.com/apache/spark/pull/26102#discussion_r334474170
##########
File path:
sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetRowConverter.scala
##########
@@ -325,6 +325,26 @@ private[parquet] class ParquetRowConverter(
override def set(value: Any): Unit =
updater.set(value.asInstanceOf[InternalRow].copy())
})
+ case CalendarIntervalType
+ if parquetType.asPrimitiveType().getPrimitiveTypeName ==
FIXED_LEN_BYTE_ARRAY =>
+ new ParquetPrimitiveConverter(updater) {
+ override def addBinary(value: Binary): Unit = {
+ assert(
+ value.length() == 12,
+ "Intervals are expected to be stored in 12-byte fixed len byte
array, " +
+ s"but got a ${value.length()}-byte array.")
+
+ val buf = value.toByteBuffer.order(ByteOrder.LITTLE_ENDIAN)
+ val milliseconds = buf.getInt
+ var microseconds = milliseconds * DateTimeUtils.MICROS_PER_MILLIS
+ val days = buf.getInt
+ val daysInUs = Math.multiplyExact(days,
DateTimeUtils.MICROS_PER_DAY)
Review comment:
Parquet stores # of days as a separated field because one logical day
interval can be 23 or 24 or 25 hours in case of daylight saving. If we convert
parquet interval to Spark interval, it's not a truncation but losing
information.
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