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