DataFusion

https://datafusion.apache.org/

Install

Install Ibis and dependencies for the Apache DataFusion backend:

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.

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.

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 collections.abc.Mapping[str, str | pathlib.Path] | datafusion.SessionContext | None Mapping of table names to files. None
Examples
>>> import ibis
>>> config = {"t": "path/to/file.parquet", "s": "path/to/file.csv"}
>>> ibis.datafusion.connect(config)

datafusion.Backend

add_operation

add_operation(self, operation)

Add a translation function to the backend for a specific operation.

Operations are defined in ibis.expr.operations, and a translation function receives the translator object and an expression as parameters, and returns a value depending on the backend.

compile

compile(self, expr, limit=None, params=None, pretty=False, **kwargs)

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

Type Description
ibis.backends.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_schema

create_schema(self, name, database=None, force=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 ibis.expr.types.ibis.expr.types.Table | pandas.pandas.DataFrame | pyarrow.pyarrow.Table | pyarrow.pyarrow.RecordBatchReader | pyarrow.pyarrow.RecordBatch | polars.polars.DataFrame | polars.polars.LazyFrame | None The data with which to populate the table; optional, but at least one of obj or schema must be specified None
schema ibis.expr.schema.ibis.expr.schema.Schema | 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, schema=None, overwrite=False)

disconnect

disconnect(self)

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_schema

drop_schema(self, name, database=None, force=False)

drop_table

drop_table(self, name, database=None, force=False)

drop_view

drop_view(self, name, *, database=None, schema=None, force=False)

execute

execute(self, expr, **kwargs)

Execute an expression.

get_schema

get_schema(self, table_name, *, catalog=None, database=None)

has_operation

has_operation(cls, operation)

insert

insert(self, table_name, obj, schema=None, 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 pandas.pandas.DataFrame | ibis.expr.types.ibis.expr.types.Table | list | dict The source data or expression to insert required
schema str | None [deprecated] The name of the schema that the table is located in None
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

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

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

list_schemas

list_schemas(self, like=None, database=None)

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

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 | sqlglot.expressions.sqlglot.expressions.Expression Raw SQL string required
kwargs Backend specific query arguments required

read_csv

read_csv(self, path, table_name=None, **kwargs)

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

Parameters

Name Type Description Default
path str | pathlib.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 typing.Any Additional keyword arguments passed to Datafusion loading function. {}

Returns

Type Description
ibis.expr.types.ibis.expr.types.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 | pathlib.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 typing.Any Additional keyword arguments passed to deltalake.DeltaTable. {}

Returns

Type Description
ibis.expr.types.ibis.expr.types.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 | pathlib.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 typing.Any Additional keyword arguments passed to the backend loading function. {}

Returns

Type Description
ibis.expr.types.ibis.expr.types.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 | pathlib.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 typing.Any Additional keyword arguments passed to Datafusion loading function. {}

Returns

Type Description
ibis.expr.types.ibis.expr.types.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 a data set with table_name located at source.

Parameters

Name Type Description Default
source str | pathlib.Path | pyarrow.pyarrow.Table | pyarrow.pyarrow.RecordBatch | pyarrow.pyarrow.Dataset | pandas.pandas.DataFrame The data source(s). May be a path to a file or directory of parquet/csv files, a pandas dataframe, or a pyarrow table, dataset or record batch. required
table_name str | None The name of the table None
kwargs typing.Any Datafusion-specific keyword arguments {}

Examples

Register a csv:

>>> import ibis
>>> conn = ibis.datafusion.connect(config)
>>> conn.register("path/to/data.csv", "my_table")
>>> conn.table("my_table")

Register a PyArrow table:

>>> import pyarrow as pa
>>> tab = pa.table({"x": [1, 2, 3]})
>>> conn.register(tab, "my_table")
>>> conn.table("my_table")

Register a PyArrow dataset:

>>> import pyarrow.dataset as ds
>>> dataset = ds.dataset("path/to/table")
>>> conn.register(dataset, "my_table")
>>> conn.table("my_table")

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, schema=None, database=None)

Construct a table expression.

Parameters

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

Returns

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 ibis.expr.types.ibis.expr.types.Table The ibis expression to execute and persist to CSV. required
path str | pathlib.Path The data source. A string or Path to the CSV file. required
params collections.abc.Mapping[ibis.expr.types.ibis.expr.types.Scalar, typing.Any] | None Mapping of scalar parameter expressions to value. None
kwargs typing.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 ibis.expr.types.ibis.expr.types.Table The ibis expression to execute and persist to Delta Lake table. required
path str | pathlib.Path The data source. A string or Path to the Delta Lake table. required
params collections.abc.Mapping[ibis.expr.types.ibis.expr.types.Scalar, typing.Any] | None Mapping of scalar parameter expressions to value. None
kwargs typing.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 ibis.expr.types.ibis.expr.types.Expr Ibis expression to execute. required
params collections.abc.Mapping[ibis.expr.types.ibis.expr.types.Scalar, typing.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 typing.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 ibis.expr.types.ibis.expr.types.Expr Ibis expression to execute. required
params collections.abc.Mapping[ibis.expr.types.ibis.expr.types.Scalar, typing.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 typing.Any Keyword arguments {}

Returns

Type Description
collections.abc.Iterator[pandas.pandas.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 ibis.expr.types.ibis.expr.types.Table The ibis expression to execute and persist to parquet. required
path str | pathlib.Path The data source. A string or Path to the parquet file. required
params collections.abc.Mapping[ibis.expr.types.ibis.expr.types.Scalar, typing.Any] | None Mapping of scalar parameter expressions to value. None
**kwargs typing.Any Additional keyword arguments passed to pyarrow.parquet.ParquetWriter {}
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 ibis.expr.types.ibis.expr.types.Expr Ibis expression to export to polars. required
params collections.abc.Mapping[ibis.expr.types.ibis.expr.types.Scalar, typing.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 typing.Any Keyword arguments {}

Returns

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 ibis.expr.types.ibis.expr.types.Expr Ibis expression to export to pyarrow required
params collections.abc.Mapping[ibis.expr.types.ibis.expr.types.Scalar, typing.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 typing.Any Keyword arguments {}

Returns

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 ibis.expr.types.ibis.expr.types.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 collections.abc.Mapping[ibis.expr.types.ibis.expr.types.Scalar, typing.Any] | None Mapping of scalar parameter expressions to value. None
chunk_size int Maximum number of rows in each returned record batch. 1000000

Returns

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 ibis.expr.types.ibis.expr.types.Expr Ibis expression to execute. required
params collections.abc.Mapping[ibis.expr.types.ibis.expr.types.Scalar, typing.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 typing.Any Keyword arguments passed into the backend’s to_torch implementation. {}

Returns

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

truncate_table

truncate_table(self, name, database=None, schema=None)

Delete all rows from a table.

Parameters

Name Type Description Default
name str Table name required
database str | None Database name None
schema str | None Schema name None
Back to top