DataFusion

https://datafusion.apache.org/

Install

Install Ibis and dependencies for the Apache DataFusion backend:

pip

Install with the Apache datafusion extra:

pip install 'ibis-framework[datafusion]'

And connect:

import ibis

con = ibis.datafusion.connect()

1

Adjust connection parameters as needed.

conda

Install for Apache DataFusion:

conda install -c conda-forge ibis-datafusion

And connect:

import ibis

con = ibis.datafusion.connect()

1

Adjust connection parameters as needed.

mamba

Install for Apache DataFusion:

mamba install -c conda-forge ibis-datafusion

And connect:

import ibis

con = ibis.datafusion.connect()

1

Adjust connection parameters as needed.

Connect

ibis.datafusion.connect

con = ibis.datafusion.connect()

con = ibis.datafusion.connect(
    config={"table1": "path/to/file.parquet", "table2": "path/to/file.csv"}
)

Note

ibis.datafusion.connect is a thin wrapper around ibis.backends.datafusion.Backend.do_connect.

Connection Parameters

do_connect

do_connect(['self', 'config=None'])

Create a DataFusion Backend for use with Ibis.

Parameters

Name	Type	Description	Default
config	Mapping[str, str | Path] | SessionContext | None	Mapping of table names to files or a SessionContext instance.	None

Examples

>>> import ibis
>>> config = {
...     "astronauts": "ci/ibis-testing-data/parquet/astronauts.parquet",
...     "diamonds": "ci/ibis-testing-data/csv/diamonds.csv",
... }
>>> con = ibis.datafusion.connect(config)
>>> con.list_tables()
['astronauts', 'diamonds']
>>> con.table("diamonds")
DatabaseTable: diamonds
  carat   float64
  cut     string
  color   string
  clarity string
  depth   float64
  table   float64
  price   int64
  x       float64
  y       float64
  z       float64

datafusion.Backend

compile

compile(['self', 'expr', 'limit=None', 'params=None', 'pretty=False'])

Compile an Ibis expression to a SQL string.

connect

connect(['self', '*args', '**kwargs'])

Connect to the database.

Parameters

Name	Type	Description	Default
*args		Mandatory connection parameters, see the docstring of do_connect for details.	()
**kwargs		Extra connection parameters, see the docstring of do_connect for details.	{}

Notes

This creates a new backend instance with saved args and kwargs, then calls reconnect and finally returns the newly created and connected backend instance.

Returns

Name	Type	Description
	BaseBackend	An instance of the backend

create_catalog

create_catalog(['self', 'name', 'force=False'])

Create a new catalog.

Ibis does not use the word schema to refer to database hierarchy.

A collection of table is referred to as a database. A collection of database is referred to as a catalog.

These terms are mapped onto the corresponding features in each backend (where available), regardless of whether the backend itself uses the same terminology.

Parameters

Name	Type	Description	Default
name	str	Name of the new catalog.	required
force	bool	If False, an exception is raised if the catalog already exists.	False

create_database

create_database(['self', 'name', 'catalog=None', 'force=False'])

Create a database named name in catalog.

Parameters

Name	Type	Description	Default
name	str	Name of the database to create.	required
catalog	str | None	Name of the catalog in which to create the database. If None, the current catalog is used.	None
force	bool	If False, an exception is raised if the database exists.	False

create_table

create_table(['self', 'name', 'obj=None', '*', 'schema=None', 'database=None', 'temp=False', 'overwrite=False'])

Create a table in DataFusion.

Parameters

Name	Type	Description	Default
name	str	Name of the table to create	required
obj	ir.Table | pd.DataFrame | pa.Table | pa.RecordBatchReader | pa.RecordBatch | pl.DataFrame | pl.LazyFrame | None	The data with which to populate the table; optional, but at least one of obj or schema must be specified	None
schema	sch.SchemaLike | None	The schema of the table to create; optional, but at least one of obj or schema must be specified	None
database	str | None	The name of the database in which to create the table; if not passed, the current database is used.	None
temp	bool	Create a temporary table	False
overwrite	bool	If True, replace the table if it already exists, otherwise fail if the table exists	False

create_view

create_view(['self', 'name', 'obj', '*', 'database=None', 'overwrite=False'])

Create a new view from an expression.

Parameters

Name	Type	Description	Default
name	str	Name of the new view.	required
obj	ir.Table	An Ibis table expression that will be used to create the view.	required
database	str | None	Name of the database where the view will be created, if not provided the database’s default is used.	None
overwrite	bool	Whether to clobber an existing view with the same name	False

Returns

Name	Type	Description
	Table	The view that was created.

disconnect

disconnect(['self'])

Close the connection to the backend.

drop_catalog

drop_catalog(['self', 'name', 'force=False'])

Drop a catalog with name name.

Ibis does not use the word schema to refer to database hierarchy.

A collection of table is referred to as a database. A collection of database is referred to as a catalog.

These terms are mapped onto the corresponding features in each backend (where available), regardless of whether the backend itself uses the same terminology.

Parameters

Name	Type	Description	Default
name	str	Catalog to drop.	required
force	bool	If False, an exception is raised if the catalog does not exist.	False

drop_database

drop_database(['self', 'name', 'catalog=None', 'force=False'])

Drop the database with name in catalog.

Parameters

Name	Type	Description	Default
name	str	Name of the schema to drop.	required
catalog	str | None	Name of the catalog to drop the database from. If None, the current catalog is used.	None
force	bool	If False, an exception is raised if the database does not exist.	False

drop_table

drop_table(['self', 'name', 'database=None', 'force=False'])

Drop a table.

Parameters

Name	Type	Description	Default
name	str	Name of the table to drop.	required
database	str | None	Name of the database where the table exists, if not the default.	None
force	bool	If False, an exception is raised if the table does not exist.	False

drop_view

drop_view(['self', 'name', '*', 'database=None', 'force=False'])

Drop a view.

Parameters

Name	Type	Description	Default
name	str	Name of the view to drop.	required
database	str | None	Name of the database where the view exists, if not the default.	None
force	bool	If False, an exception is raised if the view does not exist.	False

execute

execute(['self', 'expr', '**kwargs'])

Execute an expression.

from_connection

from_connection(['cls', 'con'])

Create a DataFusion Backend from an existing SessionContext instance.

Parameters

Name	Type	Description	Default
con	SessionContext	A SessionContext instance.	required

get_schema

get_schema(['self', 'table_name', '*', 'catalog=None', 'database=None'])

has_operation

has_operation(['cls', 'operation'])

Return whether the backend implements support for operation.

Parameters

Name	Type	Description	Default
operation	type[ops.Value]	A class corresponding to an operation.	required

Returns

Name	Type	Description
	bool	Whether the backend implements the operation.

Examples

>>> import ibis
>>> import ibis.expr.operations as ops
>>> ibis.sqlite.has_operation(ops.ArrayIndex)
False
>>> ibis.postgres.has_operation(ops.ArrayIndex)
True

insert

insert(['self', 'table_name', 'obj', 'database=None', 'overwrite=False'])

Insert data into a table.

Ibis does not use the word schema to refer to database hierarchy.

A collection of table is referred to as a database. A collection of database is referred to as a catalog.

These terms are mapped onto the corresponding features in each backend (where available), regardless of whether the backend itself uses the same terminology.

Parameters

Name	Type	Description	Default
table_name	str	The name of the table to which data needs will be inserted	required
obj	pd.DataFrame | ir.Table | list | dict	The source data or expression to insert	required
database	str | None	Name of the attached database that the table is located in. For backends that support multi-level table hierarchies, you can pass in a dotted string path like "catalog.database" or a tuple of strings like ("catalog", "database").	None
overwrite	bool	If True then replace existing contents of table	False

list_catalogs

list_catalogs(['self', 'like=None'])

List existing catalogs in the current connection.

Ibis does not use the word schema to refer to database hierarchy.

A collection of table is referred to as a database. A collection of database is referred to as a catalog.

These terms are mapped onto the corresponding features in each backend (where available), regardless of whether the backend itself uses the same terminology.

Parameters

Name	Type	Description	Default
like	str | None	A pattern in Python’s regex format to filter returned database names.	None

Returns

Name	Type	Description
	list[str]	The catalog names that exist in the current connection, that match the like pattern if provided.

list_databases

list_databases(['self', 'like=None', 'catalog=None'])

List existing databases in the current connection.

Ibis does not use the word schema to refer to database hierarchy.

A collection of table is referred to as a database. A collection of database is referred to as a catalog.

These terms are mapped onto the corresponding features in each backend (where available), regardless of whether the backend itself uses the same terminology.

Parameters

Name	Type	Description	Default
like	str | None	A pattern in Python’s regex format to filter returned database names.	None
catalog	str | None	The catalog to list databases from. If None, the current catalog is searched.	None

Returns

Name	Type	Description
	list[str]	The database names that exist in the current connection, that match the like pattern if provided.

list_tables

list_tables(['self', 'like=None', 'database=None'])

Return the list of table names in the current database.

Parameters

Name	Type	Description	Default
like	str | None	A pattern in Python’s regex format.	None
database	str | None	Unused in the datafusion backend.	None

Returns

Name	Type	Description
	list[str]	The list of the table names that match the pattern like.

raw_sql

raw_sql(['self', 'query'])

Execute a SQL string query against the database.

Parameters

Name	Type	Description	Default
query	str | sge.Expression	Raw SQL string	required
kwargs		Backend specific query arguments	required

read_csv

read_csv(['self', 'source_list', 'table_name=None', '**kwargs'])

Register a CSV file as a table in the current database.

Parameters

Name	Type	Description	Default
source_list	str | Path | list[str | Path] | tuple[str | Path]	The data source. A string or Path to the CSV file.	required
table_name	str | None	An optional name to use for the created table. This defaults to a sequentially generated name.	None
**kwargs	Any	Additional keyword arguments passed to DataFusion loading function.	{}

Returns

Name	Type	Description
	ir.Table	The just-registered table

read_delta

read_delta(['self', 'source_table', 'table_name=None', '**kwargs'])

Register a Delta Lake table as a table in the current database.

Parameters

Name	Type	Description	Default
source_table	str | Path	The data source. Must be a directory containing a Delta Lake table.	required
table_name	str | None	An optional name to use for the created table. This defaults to a sequentially generated name.	None
**kwargs	Any	Additional keyword arguments passed to deltalake.DeltaTable.	{}

Returns

Name	Type	Description
	ir.Table	The just-registered table

read_json

read_json(['self', 'path', 'table_name=None', '**kwargs'])

Register a JSON file as a table in the current backend.

Parameters

Name	Type	Description	Default
path	str | Path	The data source. A string or Path to the JSON file.	required
table_name	str | None	An optional name to use for the created table. This defaults to a sequentially generated name.	None
**kwargs	Any	Additional keyword arguments passed to the backend loading function.	{}

Returns

Name	Type	Description
	ir.Table	The just-registered table

read_parquet

read_parquet(['self', 'path', 'table_name=None', '**kwargs'])

Register a parquet file as a table in the current database.

Parameters

Name	Type	Description	Default
path	str | Path	The data source.	required
table_name	str | None	An optional name to use for the created table. This defaults to a sequentially generated name.	None
**kwargs	Any	Additional keyword arguments passed to DataFusion loading function.	{}

Returns

Name	Type	Description
	ir.Table	The just-registered table

reconnect

reconnect(['self'])

Reconnect to the database already configured with connect.

register

register(['self', 'source', 'table_name=None', '**kwargs'])

register_options

register_options(['cls'])

Register custom backend options.

rename_table

rename_table(['self', 'old_name', 'new_name'])

Rename an existing table.

Parameters

Name	Type	Description	Default
old_name	str	The old name of the table.	required
new_name	str	The new name of the table.	required

sql

sql(['self', 'query', 'schema=None', 'dialect=None'])

table

table(['self', 'name', 'database=None'])

Construct a table expression.

Parameters

Name	Type	Description	Default
name	str	Table name	required
database	tuple[str, str] | str | None	Database name	None

Returns

Name	Type	Description
	Table	Table expression

to_csv

to_csv(['self', 'expr', 'path', '*', 'params=None', '**kwargs'])

Write the results of executing the given expression to a CSV file.

This method is eager and will execute the associated expression immediately.

Parameters

Name	Type	Description	Default
expr	ir.Table	The ibis expression to execute and persist to CSV.	required
path	str | Path	The data source. A string or Path to the CSV file.	required
params	Mapping[ir.Scalar, Any] | None	Mapping of scalar parameter expressions to value.	None
kwargs	Any	Additional keyword arguments passed to pyarrow.csv.CSVWriter	{}
https			required

to_delta

to_delta(['self', 'expr', 'path', '*', 'params=None', '**kwargs'])

Write the results of executing the given expression to a Delta Lake table.

This method is eager and will execute the associated expression immediately.

Parameters

Name	Type	Description	Default
expr	ir.Table	The ibis expression to execute and persist to Delta Lake table.	required
path	str | Path	The data source. A string or Path to the Delta Lake table.	required
params	Mapping[ir.Scalar, Any] | None	Mapping of scalar parameter expressions to value.	None
kwargs	Any	Additional keyword arguments passed to deltalake.writer.write_deltalake method	{}

to_pandas

to_pandas(['self', 'expr', '*', 'params=None', 'limit=None', '**kwargs'])

Execute an Ibis expression and return a pandas DataFrame, Series, or scalar.

Note

This method is a wrapper around execute.

Parameters

Name	Type	Description	Default
expr	ir.Expr	Ibis expression to execute.	required
params	Mapping[ir.Scalar, Any] | None	Mapping of scalar parameter expressions to value.	None
limit	int | str | None	An integer to effect a specific row limit. A value of None means “no limit”. The default is in ibis/config.py.	None
kwargs	Any	Keyword arguments	{}

to_pandas_batches

to_pandas_batches(['self', 'expr', '*', 'params=None', 'limit=None', 'chunk_size=1000000', '**kwargs'])

Execute an Ibis expression and return an iterator of pandas DataFrames.

Parameters

Name	Type	Description	Default
expr	ir.Expr	Ibis expression to execute.	required
params	Mapping[ir.Scalar, Any] | None	Mapping of scalar parameter expressions to value.	None
limit	int | str | None	An integer to effect a specific row limit. A value of None means “no limit”. The default is in ibis/config.py.	None
chunk_size	int	Maximum number of rows in each returned DataFrame batch. This may have no effect depending on the backend.	1000000
kwargs	Any	Keyword arguments	{}

Returns

Name	Type	Description
	Iterator[pd.DataFrame]	An iterator of pandas DataFrames.

to_parquet

to_parquet(['self', 'expr', 'path', '*', 'params=None', '**kwargs'])

Write the results of executing the given expression to a parquet file.

This method is eager and will execute the associated expression immediately.

Parameters

Name	Type	Description	Default
expr	ir.Table	The ibis expression to execute and persist to parquet.	required
path	str | Path	The data source. A string or Path to the parquet file.	required
params	Mapping[ir.Scalar, Any] | None	Mapping of scalar parameter expressions to value.	None
**kwargs	Any	Additional keyword arguments passed to pyarrow.parquet.ParquetWriter	{}
https			required

to_parquet_dir

to_parquet_dir(['self', 'expr', 'directory', '*', 'params=None', '**kwargs'])

Write the results of executing the given expression to a parquet file in a directory.

This method is eager and will execute the associated expression immediately.

Parameters

Name	Type	Description	Default
expr	ir.Table	The ibis expression to execute and persist to parquet.	required
directory	str | Path	The data source. A string or Path to the directory where the parquet file will be written.	required
params	Mapping[ir.Scalar, Any] | None	Mapping of scalar parameter expressions to value.	None
**kwargs	Any	Additional keyword arguments passed to pyarrow.dataset.write_dataset	{}
https			required

to_polars

to_polars(['self', 'expr', '*', 'params=None', 'limit=None', '**kwargs'])

Execute expression and return results in as a polars DataFrame.

This method is eager and will execute the associated expression immediately.

Parameters

Name	Type	Description	Default
expr	ir.Expr	Ibis expression to export to polars.	required
params	Mapping[ir.Scalar, Any] | None	Mapping of scalar parameter expressions to value.	None
limit	int | str | None	An integer to effect a specific row limit. A value of None means “no limit”. The default is in ibis/config.py.	None
kwargs	Any	Keyword arguments	{}

Returns

Name	Type	Description
	dataframe	A polars DataFrame holding the results of the executed expression.

to_pyarrow

to_pyarrow(['self', 'expr', '**kwargs'])

Execute expression and return results in as a pyarrow table.

This method is eager and will execute the associated expression immediately.

Parameters

Name	Type	Description	Default
expr	ir.Expr	Ibis expression to export to pyarrow	required
params	Mapping[ir.Scalar, Any] | None	Mapping of scalar parameter expressions to value.	None
limit	int | str | None	An integer to effect a specific row limit. A value of None means “no limit”. The default is in ibis/config.py.	None
kwargs	Any	Keyword arguments	{}

Returns

Name	Type	Description
	Table	A pyarrow table holding the results of the executed expression.

to_pyarrow_batches

to_pyarrow_batches(['self', 'expr', '*', 'chunk_size=1000000', '**kwargs'])

Execute expression and return an iterator of pyarrow record batches.

This method is eager and will execute the associated expression immediately.

Parameters

Name	Type	Description	Default
expr	ir.Expr	Ibis expression to export to pyarrow	required
limit	int | str | None	An integer to effect a specific row limit. A value of None means “no limit”. The default is in ibis/config.py.	None
params	Mapping[ir.Scalar, Any] | None	Mapping of scalar parameter expressions to value.	None
chunk_size	int	Maximum number of rows in each returned record batch.	1000000

Returns

Name	Type	Description
	RecordBatchReader	Collection of pyarrow RecordBatchs.

to_torch

to_torch(['self', 'expr', '*', 'params=None', 'limit=None', '**kwargs'])

Execute an expression and return results as a dictionary of torch tensors.

Parameters

Name	Type	Description	Default
expr	ir.Expr	Ibis expression to execute.	required
params	Mapping[ir.Scalar, Any] | None	Parameters to substitute into the expression.	None
limit	int | str | None	An integer to effect a specific row limit. A value of None means no limit.	None
kwargs	Any	Keyword arguments passed into the backend’s to_torch implementation.	{}

Returns

Name	Type	Description
	dict[str, torch.Tensor]	A dictionary of torch tensors, keyed by column name.

truncate_table

truncate_table(['self', 'name', 'database=None'])

Delete all rows from a table.

Parameters

Name	Type	Description	Default
name	str	Table name	required
database	str | None	Database name	None