atoti.AggregateCache

atoti.AggregateCache(
    *,
    capacity: int,
    measures: Set[HasIdentifier[MeasureIdentifier] | MeasureIdentifier] | None = None,
)

Aggregate cache of a Cube.

>>> from dataclasses import replace
>>> table = session.create_table("Example", data_types={"id": "int"})
>>> cube = session.create_cube(table)
>>> m = cube.measures

There is a default cache:

>>> cube.aggregate_cache
AggregateCache(capacity=100, measures=None)

Increasing the capacity and only caching contributors.COUNT aggregates:

>>> cube.aggregate_cache = tt.AggregateCache(
...     capacity=200,
...     measures={m["contributors.COUNT"]},
... )
>>> cube.aggregate_cache
AggregateCache(capacity=200, measures=frozenset({m['contributors.COUNT']}))

Changing back to caching all the measures:

>>> cube.aggregate_cache = replace(cube.aggregate_cache, measures=None)
>>> cube.aggregate_cache
AggregateCache(capacity=200, measures=None)

Disabling caching but keeping sharing enabled:

>>> cube.aggregate_cache = replace(cube.aggregate_cache, capacity=0)
>>> cube.aggregate_cache
AggregateCache(capacity=0, measures=None)

Disabling caching and sharing:

>>> del cube.aggregate_cache
>>> print(cube.aggregate_cache)
None

Attributes

capacity

The capacity of the cache.

If greater than 0, this value corresponds to the maximum amount of {location: measure} pairs that the cache can hold.
If 0, caching is disabled but sharing stays enabled: concurrent queries will share their computed aggregates, but the aggregates will not be stored to be reused in later queries.

measures

The measures to cache. This should typically be the measures that are known to be the most expensive to compute. If None, all measures will be cached.

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AggregateCache

Attributes

capacity

measures

​Attributes

​capacity

​measures

Attributes

capacity

measures