## Bug description

When calculating Trends results with an aggregated (e.g. single output, like big number) display type, WAU/MAU don't work. This is because we have an `ACTIVE_USERS_SQL` query for time series display types, but we don't have a version of this for aggregated display types. (See ZEN-1043.)

## How to reproduce

1. Create an insight with a single WAU or MAU series.
2. Switch display type to "Number".
3. Open the "Debug ClickHouse queries" modal from the command palette.
4. See `COUNT(*)` instead of `COUNT(DISTINCT person_id)`.

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posthog/queries/trends/sql.py
GROUP BY {aggregator}, date
) GROUP BY date
"""
VOLUME_PER_ACTOR_AGGREGATE_SQL = """
SELECT {aggregate_operation} as data FROM (
    SELECT COUNT(*) AS intermediate_count, {aggregator}
    FROM ({event_query})
    GROUP BY {aggregator}
) events
"""
SESSION_DURATION_SQL = """
SELECT {aggregate_operation} as data, date FROM (
    SELECT {interval}(toTimeZone(toDateTime(timestamp, 'UTC'), %(timezone)s) {start_of_week_fix}) as date, any(session_duration) as session_duration
    FROM ({event_query})
    GROUP BY $session_id, date
) GROUP BY date
"""
SESSION_DURATION_AGGREGATE_SQL = """
SELECT {aggregate_operation} as data FROM (
    SELECT any(session_duration) as session_duration FROM ({event_query}) events GROUP BY $session_id
)
"""
ACTIVE_USERS_SQL = """
SELECT counts AS total, timestamp AS day_start FROM (
    SELECT d.timestamp, COUNT(DISTINCT {aggregator}) AS counts FROM (
        /* We generate a table of periods to match events against. This has to be synthesized from `numbers`
           and not `events`, because we cannot rely on there being an event for each period (this assumption previously
           caused active user counts to be off for sparse events). */
        SELECT {interval}(toDateTime(%(date_to)s, %(timezone)s) - {interval_func}(number) {start_of_week_fix}) AS timestamp
        FROM numbers(dateDiff(%(interval)s, {interval}(toDateTime(%(date_from_active_users_adjusted)s, %(timezone)s) {start_of_week_fix}), toDateTime(%(date_to)s, %(timezone)s)))