## 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/test/test_trends.py
),
                self.team,
            )
            event_response = Trends().run(
                Filter(
                    data={
                        "date_from": "-14d",
                        "breakdown": json.dumps([cohort.pk, cohort2.pk, cohort3.pk, "all"]),
                        "breakdown_type": "cohort",
                        "events": [{"id": "watched movie", "name": "watched movie", "type": "events", "order": 0}],
                    }
                ),
                self.team,
            )
        counts = {}
        break_val = {}
        for res in event_response:
            counts[res["label"]] = sum(res["data"])
            break_val[res["label"]] = res["breakdown_value"]
        self.assertEqual(counts["watched movie - cohort1"], 1)
        self.assertEqual(counts["watched movie - cohort2"], 3)
        self.assertEqual(counts["watched movie - cohort3"], 4)
        self.assertEqual(counts["watched movie - all users"], 7)
        self.assertEqual(break_val["watched movie - cohort1"], cohort.pk)
        self.assertEqual(break_val["watched movie - cohort2"], cohort2.pk)
        self.assertEqual(break_val["watched movie - cohort3"], cohort3.pk)
        self.assertEqual(break_val["watched movie - all users"], "all")
        self.assertEntityResponseEqual(event_response, action_response)
    @test_with_materialized_columns(verify_no_jsonextract=False)
    def test_interval_filtering_breakdown(self):