daft.read_iceberg

daft.read_iceberg(pyiceberg_table: PyIcebergTable, io_config: Optional[IOConfig] = None) → DataFrame

Create a DataFrame from an Iceberg table

Example

>>> import pyiceberg
>>>
>>> pyiceberg_table = pyiceberg.Table(...)
>>> df = daft.read_iceberg(pyiceberg_table)
>>>
>>> # Filters on this dataframe can now be pushed into
>>> # the read operation from Iceberg
>>> df = df.where(df["foo"] > 5)
>>> df.show()

Note

This function requires the use of PyIceberg, which is the Apache Iceberg’s official project for Python.

Parameters:

• pyiceberg_table – Iceberg table created using the PyIceberg library

• io_config – A custom IOConfig to use when accessing Iceberg object storage data. Defaults to None.

Returns:

a DataFrame with the schema converted from the specified Iceberg table

Return type:

DataFrame

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