Flink

https://nightlies.apache.org/flink/flink-docs-stable/

Install

Install Ibis and dependencies for the Flink backend:

pip

Install alongside the apache-flink package:

pip install ibis-framework apache-flink

And connect:

import ibis

con = ibis.flink.connect()

1

Adjust connection parameters as needed.

Connect

ibis.flink.connect

con = ibis.flink.connect(table_env=table_env)

Note

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

Note

The flink backend does not create TableEnvironment objects; you must create a TableEnvironment and pass that to ibis.flink.connect.

Connection Parameters

do_connect

do_connect(['self', 'table_env'])

Create a Flink Backend for use with Ibis.

Parameters

Name	Type	Description	Default
table_env	TableEnvironment	A table environment.	required

Examples

>>> import ibis
>>> from pyflink.table import EnvironmentSettings, TableEnvironment
>>> table_env = TableEnvironment.create(EnvironmentSettings.in_streaming_mode())
>>> ibis.flink.connect(table_env)
<ibis.backends.flink.Backend object at 0x...>

flink.Backend

compile

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

Compile an Ibis expression to Flink.

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_database

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

Create a new database.

Parameters

Name	Type	Description	Default
name	str	Name of the new database.	required
db_properties	dict	Properties of the database. Accepts dictionary of key-value pairs (key1=val1, key2=val2, …).	None
catalog	str	Name of the catalog in which the new database will be created.	None
force	bool	If False, an exception is raised if the database already exists.	False

create_table

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

Create a new table in Flink.

In Flink, tables can be either virtual (VIEWS) or regular (TABLES). VIEWS can be created from an existing Table object, usually the result of a Table API or SQL query. TABLES describe external data, such as a file, database table, or message queue. In other words, TABLES refer explicitly to tables constructed directly from source/sink connectors.

When obj is in-memory (e.g., Dataframe), currently this function can create only a TEMPORARY VIEW. If obj is in-memory and temp is False, it will raise an error.

Parameters

Name	Type	Description	Default
name	str	Name of the new table.	required
obj	pd.DataFrame | pa.Table | ir.Table | None	An Ibis table expression, pandas DataFrame, or PyArrow Table that will be used to extract the schema and the data of the new table. An optional schema can be used to override the schema.	None
schema	sch.Schema | None	The schema for the new table. Required if obj is not provided.	None
database	str | None	Name of the database where the table will be created, if not the default.	None
catalog	str | None	Name of the catalog where the table will be created, if not the default.	None
tbl_properties	dict | None	Table properties used to create a table source/sink. The properties are usually used to find and create the underlying connector. Accepts dictionary of key-value pairs (key1=val1, key2=val2, …).	None
watermark	Watermark | None	Watermark strategy for the table, only applicable on sources.	None
primary_key	str | list[str] | None	A single column or a list of columns to be marked as primary. Raises an error if the column(s) in primary_key is NOT a subset of the columns in schema. Primary keys must be non-nullable in Flink and the columns indicated as primary key will be designated as non-nullable.	None
temp	bool	Whether a table is temporary or not.	False
overwrite	bool	Whether to clobber existing data.	False

Returns

Name	Type	Description
	Table	The table that was created.

create_view

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

Create a new view from a dataframe or table.

When obj is in-memory (e.g., Dataframe), currently this function can create only a TEMPORARY VIEW. If obj is in-memory and temp is False, it will raise an error.

Parameters

Name	Type	Description	Default
name	str	Name of the new view.	required
obj	pd.DataFrame | ir.Table	An Ibis table expression that will be used to create the view.	required
schema	sch.Schema | None	The schema for the new view.	None
database	str | None	Name of the database where the view will be created, if not provided the database’s default is used.	None
catalog	str | None	Name of the catalog where the table exists, if not the default.	None
force	bool	If False, an exception is raised if the table is already present.	False
temp	bool	Whether the table is temporary or not.	False
overwrite	bool	If True, remove the existing view, and create a new one.	False

Returns

Name	Type	Description
	Table	The view that was created.

disconnect

disconnect(['self'])

Close the connection to the backend.

drop_database

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

Drop a database with name name.

Parameters

Name	Type	Description	Default
name	str	Database to drop.	required
catalog	str	Name of the catalog from which the database will be dropped.	None
force	bool	If False, an exception is raised if the database does not exist.	False

drop_table

drop_table(['self', 'name', '*', 'database=None', 'catalog=None', 'temp=False', '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
catalog	str | None	Name of the catalog where the table exists, if not the default.	None
temp	bool	Whether the table is temporary or not.	False
force	bool	If False, an exception is raised if the table does not exist.	False

drop_view

drop_view(['self', 'name', '*', 'database=None', 'catalog=None', 'temp=False', '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
catalog	str | None	Name of the catalog where the view exists, if not the default.	None
temp	bool	Whether the view is temporary or not.	False
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', 'table_env'])

Create a Flink Backend from an existing table environment.

Parameters

Name	Type	Description	Default
table_env	TableEnvironment	A table environment.	required

get_schema

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

Return a Schema object for the indicated table and database.

Parameters

Name	Type	Description	Default
table_name	str	Table name.	required
catalog	str	Catalog name.	None
database	str	Database name.	None

Returns

Name	Type	Description
	sch.Schema	Ibis schema

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', 'catalog=None', 'overwrite=False'])

Insert data into a table.

Parameters

Name	Type	Description	Default
table_name	str	The name of the table to insert data into.	required
obj	pa.Table | 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.	None
catalog	str | None	Name of the attached catalog that the table is located in.	None
overwrite	bool	If True then replace existing contents of table.	False

Returns

Name	Type	Description
	TableResult	The table result.

Raises

Name	Type	Description
	ValueError	If the type of obj isn’t supported

list_databases

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

Return the list of table/view names.

Return the list of table/view names in the database and catalog. If database/catalog are not specified, their default values will be used. Temporary tables can only be listed for the default database and catalog, hence database and catalog are ignored if temp is True.

Parameters

Name	Type	Description	Default
like	str	A pattern in Python’s regex format.	None
temp	bool	Whether to list temporary tables or permanent tables.	False
database	str	The database to list tables of, if not the current one.	None
catalog	str	The catalog to list tables of, if not the current one.	None

Returns

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

list_views

list_views(['self', 'like=None', 'temp=False'])

Return the list of view names.

Return the list of view names.

Parameters

Name	Type	Description	Default
like	str	A pattern in Python’s regex format.	None
temp	bool	Whether to list temporary views or permanent views.	False

Returns

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

raw_sql

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

read_csv

read_csv(['self', 'path', 'schema=None', 'table_name=None'])

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

Parameters

Name	Type	Description	Default
path	str | Path	The data source.	required
schema	sch.Schema | None	The schema for the new table.	None
table_name	str | None	An optional name to use for the created table. This defaults to a sequentially generated name.	None

Returns

Name	Type	Description
	ir.Table	The just-registered table

read_delta

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

Register a Delta Lake table in the current database.

Parameters

Name	Type	Description	Default
source	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 the underlying backend or library.	{}

Returns

Name	Type	Description
	ir.Table	The just-registered table.

read_json

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

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

Parameters

Name	Type	Description	Default
path	str | Path	The data source.	required
schema	sch.Schema | None	The schema for the new table.	None
table_name	str | None	An optional name to use for the created table. This defaults to a sequentially generated name.	None

Returns

Name	Type	Description
	ir.Table	The just-registered table

read_parquet

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

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

Parameters

Name	Type	Description	Default
path	str | Path	The data source.	required
schema	sch.Schema | None	The schema for the new table.	None
table_name	str | None	An optional name to use for the created table. This defaults to a sequentially generated name.	None

Returns

Name	Type	Description
	ir.Table	The just-registered table

reconnect

reconnect(['self'])

Reconnect to the database already configured with connect.

register_options

register_options(['cls'])

Register custom backend options.

rename_table

rename_table(['self', 'old_name', 'new_name', 'force=True'])

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
force	bool	If False, an exception is raised if the table does not exist.	True

sql

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

table

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

Return a table expression from a table or view in the database.

Parameters

Name	Type	Description	Default
name	str	Table name.	required
database	str | None	Database in which the table resides.	None
catalog	str | None	Catalog in which the table resides.	None

Returns

Name	Type	Description
	Table	Table named name from database

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', '*', '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

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

to_pyarrow_batches

to_pyarrow_batches(['self', 'expr', '*', 'params=None', 'chunk_size=None', 'limit=None', '**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.

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

A collection of tables 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	Table name	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