Trino

https://trino.io

Install

Install Ibis and dependencies for the Trino backend:

Install with the trino extra:

pip install 'ibis-framework[trino]'

And connect:

import ibis

con = ibis.trino.connect()
1
Adjust connection parameters as needed.

Install for Trino:

conda install -c conda-forge ibis-trino

And connect:

import ibis

con = ibis.trino.connect()
1
Adjust connection parameters as needed.

Install for Trino:

mamba install -c conda-forge ibis-trino

And connect:

import ibis

con = ibis.trino.connect()
1
Adjust connection parameters as needed.

Connect

ibis.trino.connect

con = ibis.trino.connect(
    user="user",
    password="password",
    port=8080,
    database="database",
    schema="default",
)
Note

ibis.trino.connect is a thin wrapper around ibis.backends.trino.Backend.do_connect.”

Connection Parameters

do_connect

do_connect(['self', "user='user'", 'password=None', "host='localhost'", 'port=8080', 'database=None', 'schema=None', 'source=None', "timezone='UTC'", 'auth=None', '**kwargs'])

Connect to Trino.

Parameters
Name Type Description Default
user str Username to connect with 'user'
password str | None Password to connect with. Mutually exclusive with auth. None
host str Hostname of the Trino server 'localhost'
port int Port of the Trino server 8080
database str | None Catalog to use on the Trino server None
schema str | None Schema to use on the Trino server None
source str | None Application name passed to Trino None
timezone str Timezone to use for the connection 'UTC'
auth str | None Authentication method to use for the connection. Mutually exclusive with password. None
kwargs Additional keyword arguments passed directly to the trino.dbapi.connect API. {}
Examples
>>> catalog = "hive"
>>> schema = "default"

Connect using a URL, with the default user, password, host and port

>>> con = ibis.connect(f"trino:///{catalog}/{schema}")

Connect using a URL

>>> con = ibis.connect(f"trino://user@localhost:8080/{catalog}/{schema}")

Connect using keyword arguments

>>> con = ibis.trino.connect(database=catalog, schema=schema)
>>> con = ibis.trino.connect(database=catalog, schema=schema, source="my-app")

Authenticating with SSO

Ibis supports connecting to SSO-enabled Trino clusters using the OAuth2Authentication helper from the trino library.

import ibis
from trino.auth import OAuth2Authentication

con = ibis.trino.connect(
  user="user",
  host="hostname",
  port=443,
  database="database",
  schema="default",
  auth=OAuth2Authentication(),
  http_scheme="https"
)

Connecting to Starburst managed Trino instances

Starburst makes use of role-based access controls. When connecting to a Starburst Trino cluster, if you encounter issues listing or connecting to tables, ensure that a role is specified using the roles keyword.

import ibis

con = ibis.trino.connect(
    user="user",
    host="hostname",
    port=443,
    database="sample",
    schema="demo",
    roles="defaultrolewithtableaccess",
    http_scheme="https"
)
1
Role names will be visible in the Starburst Galaxy dashboard.

Finding your Starburst host

Log into Starburst Galaxy and select Clusters from the left-hand-side menu:

Select Connection info for the cluster you wish to connect to – the username and hostname displayed can be copied directly into the Ibis connect call.

trino.Backend

begin

begin(['self'])

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_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', 'comment=None', 'properties=None'])

Create a table in Trino.

Parameters

Name Type Description Default
name str Name of the table to create required
obj ir.Table | pd.DataFrame | pa.Table | pl.DataFrame | pl.LazyFrame | None The data with which to populate the table; optional, but one of obj or schema must be specified None
schema sch.SchemaLike | None The schema of the table to create; optional, but one of obj or schema must be specified None
database str | None The database to insert the table into. If not provided, the current database is used. You can provide a single database name, like "mydb". For multi-level hierarchies, you can pass in a dotted string path like "catalog.database" or a tuple of strings like ("catalog", "database"). None
temp bool This parameter is not yet supported in the Trino backend, because Trino doesn’t implement temporary tables False
overwrite bool If True, replace the table if it already exists, otherwise fail if the table exists False
comment str | None Add a comment to the table None
properties Mapping[str, Any] | None Table properties to set on creation None

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_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', 'params=None', "limit='default'", '**kwargs'])

Execute an expression.

from_connection

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

Create an Ibis client from an existing connection to a Trino database.

Parameters

Name Type Description Default
con trino.dbapi.Connection An existing connection to a Trino database. required

get_schema

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

Compute the schema of a table.

Parameters

Name Type Description Default
table_name str May not be fully qualified. Use database if you want to qualify the identifier. required
catalog str | None Catalog name None
database str | None 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', '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'])

List the tables in the database.

Parameters

Name Type Description Default
like str | None A pattern to use for listing tables. None
database tuple[str, str] | str | None The database location to perform the list against. By default uses the current database (self.current_database) and catalog (self.current_catalog). To specify a table in a separate catalog, you can pass in the catalog and database as a string "catalog.database", or as a tuple of strings ("catalog", "database"). None

raw_sql

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

Execute a raw SQL query.

read_csv

read_csv(['self', '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

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', '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 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

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'])

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', '*', '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', 'limit=None', 'chunk_size=1000000', '**_'])

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
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