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
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
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
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
