atoti.AggregateProvider

atoti.AggregateProvider(
    *,
    filter: AggregateProviderFilterCondition | None = None,
    key: AggregateProviderPluginKey = 'leaf',
    levels: Annotated[AbstractSet[Identifiable[LevelIdentifier]], Field(min_length=1), AfterValidator(validate_hierarchy_unicity)] | None = None,
    measures: Annotated[AbstractSet[Identifiable[MeasureIdentifier]], Field(min_length=1)] | None = None,
    partitioning: str | None = None,
)

An aggregate provider pre-aggregates some measures up to certain levels. If a step of a query uses a subset of the aggregate provider’s levels and measures, the provider will speed up the query. An aggregate provider uses additional memory to store the intermediate aggregates. The more levels and measures are added, the more memory it requires.

>>> df = pd.DataFrame(
...     {
...         "Seller": ["Seller_1", "Seller_1", "Seller_2", "Seller_2"],
...         "ProductId": ["aBk3", "ceJ4", "aBk3", "ceJ4"],
...         "Price": [2.5, 49.99, 3.0, 54.99],
...     }
... )
>>> table = session.read_pandas(df, table_name="Seller")
>>> cube = session.create_cube(table)
>>> l, m = cube.levels, cube.measures
>>> cube.aggregate_providers["Seller"] = tt.AggregateProvider(
...     filter=l["Seller"] == "Seller_1",
...     key="bitmap",
...     levels={l["Seller"]},
...     measures={m["Price.SUM"]},
...     partitioning="modulo4(Seller)",
... )
>>> cube.aggregate_providers
{'Seller': AggregateProvider(filter=l['Seller', 'Seller', 'Seller'] == 'Seller_1', key='bitmap', levels=frozenset({l['Seller', 'Seller', 'Seller']}), measures=frozenset({m['Price.SUM']}), partitioning='modulo4(Seller)')}

Pre-aggregating all measures:

>>> from dataclasses import replace
>>> cube.aggregate_providers["Seller"] = replace(
...     cube.aggregate_providers["Seller"],
...     measures=None,
... )
>>> cube.aggregate_providers["Seller"]
AggregateProvider(filter=l['Seller', 'Seller', 'Seller'] == 'Seller_1', key='bitmap', levels=frozenset({l['Seller', 'Seller', 'Seller']}), measures=None, partitioning='modulo4(Seller)')

Attributes

filter

Only compute and provide aggregates matching this condition.

key

The key of the provider. The bitmap is generally faster but also takes more memory.

levels

The levels to build the provider on. If a passed level is part of a multilevel hierarchy, all shallower levels will be pre-aggregated too. If None, all eligible levels will be pre-aggregated.

measures

The measures to build the provider on. If None, all eligible measures will be pre-aggregated.

This collection cannot contain any measure created from a column in a partially joined table.

partitioning

The partitioning of the provider. Default to the partitioning of the cube’s fact table.

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AggregateProvider

Attributes

filter

key

levels

measures

partitioning

​Attributes

​filter

​key

​levels

​measures

​partitioning

Attributes

filter

key

levels

measures

partitioning