MaxGekk commented on code in PR #56825:
URL: https://github.com/apache/spark/pull/56825#discussion_r3485963424
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sql/core/src/main/scala/org/apache/spark/sql/avro/AvroDeserializer.scala:
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@@ -213,6 +213,28 @@ private[sql] class AvroDeserializer(
s"Avro logical type $other cannot be converted to SQL type
${TimeType().sql}.")
}
+ case (LONG, t: TimestampLTZNanosType) => avroType.getLogicalType match {
+ // The timestamp-nanos logical type stores epoch-nanoseconds (Long),
while the value is
+ // represented internally as (epochMicros, nanosWithinMicro). Floor
semantics keep
+ // nanosWithinMicro in [0, 999] for pre-epoch values. Nanos timestamps
are always proleptic
+ // Gregorian, so they are exempt from datetime rebasing.
+ case _: TimestampNanos => (updater, ordinal, value) =>
+ updater.set(ordinal,
+ DateTimeUtils.epochNanosToTimestampNanos(value.asInstanceOf[Long],
t.precision))
+ case other => throw new IncompatibleSchemaException(errorPrefix +
+ s"Avro logical type $other cannot be converted to SQL type " +
+ s"${TimestampLTZNanosType().sql}.")
+ }
+
+ case (LONG, t: TimestampNTZNanosType) => avroType.getLogicalType match {
+ case _: LocalTimestampNanos => (updater, ordinal, value) =>
+ updater.set(ordinal,
+ DateTimeUtils.epochNanosToTimestampNanos(value.asInstanceOf[Long],
t.precision))
Review Comment:
Added in `725770c` - new test "SPARK-57459: reading a foreign nanos Avro
file with an explicit lower-precision schema": writes a full-precision
(`...567890123`) foreign `timestamp-nanos` / `local-timestamp-nanos` file with
no catalyst-type prop, reads it with an explicit `TIMESTAMP_LTZ(7)` /
`TIMESTAMP_NTZ(7)` schema, and asserts the sub-microsecond digits are truncated
(`...123` -> `...100`), mirroring `ParquetTimestampNanosSuite`.
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