Hi Everyone,
As part of our discussions on the Materialized View (MV) spec, the topic of
"SQL table identifiers" has been a constant source of complexity. After
several iterations, the community has agreed not to use SQL table
identifiers in the table-side representation of MVs. However, that stil
Thanks for confirming!
To close the loop on this issue, we have added more documentation about the
`result_type` function in PyIceberg. This clarifies the physical and
display representations of partition transforms. For DayTransform, the
physical representation is `int`, while the display represe
Yes. When we return the Spark type, it shows up as date and Spark correctly
displays the value.
On Mon, Sep 30, 2024 at 9:56 AM Kevin Liu wrote:
> Thank you both for the insights and context.
>
> As Russell pointed out, the "day partition transform" result is true of
> int type. The Types.DateTy
Hi, I would like to discuss the property
write.metadata.metrics.max-inferred-column-defaults
issue created here https://github.com/apache/iceberg/issues/11253
The fundamental issue is that this doesn't work for all kinds of wide
schemas. I need to support
many arbitrary schemas so having per sche
