srowen 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_r335170728
##########
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:
If we don't change CalendarInterval, hm, how can we handle the different
structure of a Parquet interval without getting it wrong in some cases?
As in the other PR, another option is to refuse to read/write intervals that
are longer than a day, I guess?
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