matthias-Q commented on code in PR #2173:
URL: https://github.com/apache/iceberg-python/pull/2173#discussion_r2216665172
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pyiceberg/utils/schema_conversion.py:
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@@ -69,8 +69,10 @@
LOGICAL_FIELD_TYPE_MAPPING: Dict[Tuple[str, str], PrimitiveType] = {
("date", "int"): DateType(),
("time-micros", "long"): TimeType(),
+ ("timestamp-millis", "int"): TimestampType(),
Review Comment:
Thanks for the response. I was preparing a PR that would add
`TimestampMilli` similar to `TimestampNano`. I understand that is not in the
spec.
My initial use case was, that I want to use the Schema conversion functions
to create an Iceberg table based of an Avro Schema. At the moment I use
`AvroSchemaConversion.avro_to_iceberg().as_arrow()` to create the Arrow table
that goes eventually into Iceberg. Maybe it would suffice to add some
functionality here. Since my data is actually a python timestamp and that has
microsecond precision anyways. As some context: I want to consume a Kafka topic
and upsert that into an iceberg table.
EDIT:
Here is a gist
https://gist.github.com/matthias-Q/87632a18301324e4bc3d02dd2c396210
That also my explains my initial confidence that we do not need conversion.
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