Jay Chia

We will not be taking this on: it's too difficult to come up with a reasonable number here because it's so dependent on the workload.

``` --------------------------------------------------------------------------- ArrowNotImplementedError Traceback (most recent call last) Cell In[3], line 6 4 df = daft.from_pydict({"x": [np.array([1, 2, 3]), None, np.array([1, 2, 3])]}) 5 df = df.with_column("y", df["x"].cast(daft.DataType.fixed_size_list(daft.DataType.int64(), 3))) ---->...

Closing in favor of #3002

We're happy to provide support and discuss integrations. It should hopefully not be too difficult, but would require a Python API for Paimon - is that something that is available?

It'd have to be done as a PhysicalPlan optimization which I think would be a departure from how we currently perform optimization passes (we only optimize LogicalPlans I think?). Not...

Any thoughts also on partitioning? They could contain the same data (and same order) globally, but partitioning might differ. I feel like perhaps the safest option might just be to...

Hey @rkunnamp! We realized that `deltalake` made a backward incompatible change in the 0.17 version.... If you pip install `deltalake

Hi @ritchie46, apologies for the late reply! Going by the Parquet spec, decimals are actually able to be encoded as `int32`, `int64`, `fixed_len_byte_array` and `binary`. See: https://github.com/apache/parquet-format/blob/master/LogicalTypes.md#decimal > `binary`: precision...

Thanks @apostolos-geyer .... Good catch! This definitely seems like a bug. Would LOVE to take a contribution ❤️ Here are some quick tips: * Getting set up with Daft locally...

Feel free to shoot us any questions about contributing :)