Druid

https://druid.apache.org

Install

Install Ibis and dependencies for the Druid backend:

Install with the druid extra:

pip install 'ibis-framework[druid]'

And connect:

import ibis

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

Install for Druid:

conda install -c conda-forge ibis-druid

And connect:

import ibis

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

Install for Druid:

mamba install -c conda-forge ibis-druid

And connect:

import ibis

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

Connect

ibis.druid.connect

con = ibis.druid.connect(
    host="hostname",
    port=8082,
    path="druid/v2/sql",
)
Note

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

Connection Parameters

do_connect

do_connect(['self', '**kwargs'])

Create an Ibis client using the passed connection parameters.

Examples
>>> import ibis
>>> con = ibis.connect("druid://localhost:8082/druid/v2/sql?header=true")
>>> con.list_tables()
[...]
>>> t = con.table("functional_alltypes")
>>> t
DatabaseTable: functional_alltypes
  __time          timestamp
  id              int64
  bool_col        int64
  tinyint_col     int64
  smallint_col    int64
  int_col         int64
  bigint_col      int64
  float_col       float64
  double_col      float64
  date_string_col string
  string_col      string
  timestamp_col   int64
  year            int64
  month           int64

ibis.connect URL format

In addition to ibis.druid.connect, you can also connect to Druid by passing a properly-formatted Druid connection URL to ibis.connect:

con = ibis.connect("druid://localhost:8082/druid/v2/sql")

druid.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_table

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

Create a new table.

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 or pandas table that will be used to extract the schema and the data of the new table. If not provided, schema must be given. None
schema ibis.Schema | None The schema for the new table. Only one of schema or obj can be provided. None
database str | None Name of the database where the table will be created, if not the default. 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', '*', '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_table

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

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 Druid database.

Parameters

Name Type Description Default
con pydruid.db.api.Connection An existing connection to a Druid database. 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_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 str | None Database to list tables from. Default behavior is to show tables in the current database. None

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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