Dask

ibis.memtable Support

The Dask backend supports memtables by natively executing queries against the underlying storage (e.g., pyarrow Tables or pandas DataFrames).

Install

Install ibis and dependencies for the Dask backend:

pipcondamamba

pip install 'ibis-framework[dask]'

conda install -c conda-forge ibis-dask

mamba install -c conda-forge ibis-dask

Connect

API

Create a client by passing in a dictionary of paths to ibis.dask.connect.

See ibis.backends.dask.Backend.do_connect for connection parameter information.

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

Connection Parameters

do_connect(dictionary=None)

Construct a Dask backend client from a dictionary of data sources.

Parameters:

Name	Type	Description	Default
dictionary	MutableMapping[str, dd.DataFrame] | None	An optional mapping from str table names to Dask DataFrames.	None

Examples:

>>> import ibis
>>> import dask.dataframe as dd
>>> data = {
...     "t": dd.read_parquet("path/to/file.parquet"),
...     "s": dd.read_csv("path/to/file.csv"),
... }
>>> ibis.dask.connect(data)

Backend API

Backend

Bases: BasePandasBackend

Attributes

db_identity: str cached property

Return the identity of the database.

Multiple connections to the same database will return the same value for db_identity.

The default implementation assumes connection parameters uniquely specify the database.

Returns:

Type	Description
Hashable	Database identity

tables cached property

An accessor for tables in the database.

Tables may be accessed by name using either index or attribute access:

Examples:

>>> con = ibis.sqlite.connect("example.db")
>>> people = con.tables['people']  # access via index
>>> people = con.tables.people  # access via attribute

Functions

add_operation(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(query, params=None, **kwargs)

Compile expr.

Returns:

Type	Description
dask.dataframe.core.DataFrame | dask.dataframe.core.Series | das.dataframe.core.Scalar	Dask graph.

connect(*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
BaseBackend	An instance of the backend

create_table(name, obj=None, *, schema=None, database=None, temp=None, overwrite=False)

Create a table.

database(name=None)

Return a Database object for the name database.

Parameters:

Name	Type	Description	Default
name	str | None	Name of the database to return the object for.	None

Returns:

Type	Description
Database	A database object for the specified database.

from_dataframe(df, name='df', client=None)

Construct an ibis table from a pandas DataFrame.

Parameters:

Name	Type	Description	Default
df	pd.DataFrame	A pandas DataFrame	required
name	str	The name of the pandas DataFrame	'df'
client	BasePandasBackend | None	Client dictionary will be mutated with the name of the DataFrame, if not provided a new client is created	None

Returns:

Type	Description
Table	A table expression

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

Register a CSV 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 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 the backend loading function.	{}

Returns:

Type	Description
ir.Table	The just-registered table

read_parquet(path, table_name=None, **kwargs)

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

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 the backend loading function.	{}

Returns:

Type	Description
ir.Table	The just-registered table

register_options() classmethod

Register custom backend options.

to_csv(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	{}

to_delta(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_parquet(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	{}

to_pyarrow(expr, *, params=None, limit=None, **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:

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

to_pyarrow_batches(expr, *, params=None, limit=None, chunk_size=1000000, **kwargs)

Execute expression and return a RecordBatchReader.

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
kwargs	Any	Keyword arguments	{}

Returns:

Type	Description
results	RecordBatchReader

to_torch(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:

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

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Last update: August 1, 2023