rolling_window fails when grouping by a time dimension without date_trunc

## Describe the bug

When using the SQL API, Cube's rolling window logic is only triggered if the query explicitly applies a `date_trunc` function to a time dimension in the `SELECT` clause.

If a time dimension is selected directly in a `GROUP BY` query without a `date_trunc` wrapper, its measure's `rolling_window` definition is applied incorrectly, leading to incorrect results. This happens even if the selected time dimension is already defined with `DATE_TRUNC` in the data model.

This bug affects **both the legacy and Tesseract query engines**:
* The **legacy engine** misinterprets the `rolling_window` parameters, applying them to an incorrect cumulative query.
* The **Tesseract engine** appears to ignore the `rolling_window` definition entirely, generating a simple `GROUP BY` query.

## To Reproduce

1. Define the following Cube schema:

```yaml
cubes:
- name: test_events
sql: |
(
SELECT 1 AS user_id, TIMESTAMP '2024-01-01 10:00:00' AS created_ts
UNION ALL
SELECT 2 AS user_id, TIMESTAMP '2024-01-02 14:00:00' AS created_ts
UNION ALL
SELECT 1 AS user_id, TIMESTAMP '2024-01-15 08:00:00' AS created_ts
UNION ALL
SELECT 3 AS user_id, TIMESTAMP '2024-02-20 11:00:00' AS created_ts
)
public: true

dimensions:
- name: user_id
sql: "{CUBE}.user_id"
type: number
primary_key: true

- name: created_ts
sql: "{CUBE}.created_ts"
type: time
primary_key: true

- name: created_date
sql: "DATE_TRUNC('day', {CUBE}.created_ts)"
type: time

measures:
- name: user_count_rolling_28d
sql: "{CUBE}.user_id"
type: count
rolling_window:
trailing: 28 day
```

2. Via the Cube SQL API, execute the following queries to observe the difference.

#### Failing Query (No `date_trunc` in `SELECT`)

This query selects the `created_date` dimension directly.

```sql
SELECT
created_date,
measure(user_count_rolling_28d)
FROM test_events
WHERE
created_date >= '2024-01-01' AND created_date < '2024-03-01'
GROUP BY 1
```

#### Working Query (With `date_trunc` in `SELECT`)

This query explicitly wraps `created_date` with `date_trunc`. This workaround **correctly** triggers the rolling window logic.

```sql
SELECT
date_trunc('day', created_date) as created_date_truncated,
measure(user_count_rolling_28d)
FROM test_events
WHERE
created_date >= '2024-01-01' AND created_date < '2024-03-01'
GROUP BY 1
```

## Actual Results (Incorrect Behavior)

The first (failing) query produces incorrect SQL. The behavior differs between the legacy and Tesseract engines, but neither performs a rolling window calculation.

#### Without Tesseract (Legacy Engine)

The engine generates a complex, non-rolling cumulative query, ignoring the `rolling_window` definition.

```sql
-- Incorrect SQL
SELECT
q_0."created_date",
"test_events__user_count_rolling_28d" "user_count_rolli"
FROM
(
SELECT
CAST(
date_add(
'minute',
timezone_minute(
DATE_TRUNC('day', "test_events_user_count_rolling_28d_cumulative__test_events".created_ts) AT TIME ZONE 'UTC'
),
date_add(
'hour',
timezone_hour(
DATE_TRUNC('day', "test_events_user_count_rolling_28d_cumulative__test_events".created_ts) AT TIME ZONE 'UTC'
),
DATE_TRUNC('day', "test_events_user_count_rolling_28d_cumulative__test_events".created_ts)
)
) AS TIMESTAMP
) "created_date",
count("test_events_user_count_rolling_28d_cumulative__test_events".user_id) "test_events__user_count_rolling_28d"
FROM
(
(
SELECT
1 AS user_id,
TIMESTAMP '2024-01-01 10:00:00' AS created_ts
UNION ALL
SELECT
2 AS user_id,
TIMESTAMP '2024-01-02 14:00:00' AS created_ts
UNION ALL
SELECT
1 AS user_id,
TIMESTAMP '2024-01-15 08:00:00' AS created_ts
UNION ALL
SELECT
3 AS user_id,
TIMESTAMP '2024-02-20 11:00:00' AS created_ts
)
) AS "test_events_user_count_rolling_28d_cumulative__test_events"
WHERE
(
CAST(
date_add(
'minute',
timezone_minute(
DATE_TRUNC('day', "test_events_user_count_rolling_28d_cumulative__test_events".created_ts) AT TIME ZONE 'UTC'
),
date_add(
'hour',
timezone_hour(
DATE_TRUNC('day', "test_events_user_count_rolling_28d_cumulative__test_events".created_ts) AT TIME ZONE 'UTC'
),
DATE_TRUNC('day', "test_events_user_count_rolling_28d_cumulative__test_events".created_ts)
)
) AS TIMESTAMP
) > CAST(
date_add(
'minute',
timezone_minute(from_iso8601_timestamp(?) AT TIME ZONE 'UTC'),
date_add(
'hour',
timezone_hour(from_iso8601_timestamp(?) AT TIME ZONE 'UTC'),
from_iso8601_timestamp(?)
)
) AS TIMESTAMP
) - interval '28' day
AND CAST(
date_add(
'minute',
timezone_minute(
DATE_TRUNC('day', "test_events_user_count_rolling_28d_cumulative__test_events".created_ts) AT TIME ZONE 'UTC'
),
date_add(
'hour',
timezone_hour(
DATE_TRUNC('day', "test_events_user_count_rolling_28d_cumulative__test_events".created_ts) AT TIME ZONE 'UTC'
),
DATE_TRUNC('day', "test_events_user_count_rolling_28d_cumulative__test_events".created_ts)
)
) AS TIMESTAMP
) <= CAST(
date_add(
'minute',
timezone_minute(from_iso8601_timestamp(?) AT TIME ZONE 'UTC'),
date_add(
'hour',
timezone_hour(from_iso8601_timestamp(?) AT TIME ZONE 'UTC'),
from_iso8601_timestamp(?)
)
) AS TIMESTAMP
)
)
GROUP BY
1
) as q_0
```

#### With Tesseract

The engine generates a simple `GROUP BY` query, completely ignoring the `rolling_window` definition.

```sql
WITH
cte_0 AS (
SELECT
DATE_TRUNC('day', "test_events".created_ts) "user_count_rolling_28d__created_date",
count("test_events".user_id) "test_events__user_count_rolling_28d"
FROM
(
(
SELECT
1 AS user_id,
TIMESTAMP '2024-01-01 10:00:00' AS created_ts
UNION ALL
SELECT
2 AS user_id,
TIMESTAMP '2024-01-02 14:00:00' AS created_ts
UNION ALL
SELECT
1 AS user_id,
TIMESTAMP '2024-01-15 08:00:00' AS created_ts
UNION ALL
SELECT
3 AS user_id,
TIMESTAMP '2024-02-20 11:00:00' AS created_ts
)
) AS "test_events"
WHERE
(
DATE_TRUNC('day', "test_events".created_ts) >= from_iso8601_timestamp(?)
AND DATE_TRUNC('day', "test_events".created_ts) <= from_iso8601_timestamp(?)
)
GROUP BY
1
ORDER BY
2 DESC
)
SELECT
"q_0"."user_count_rolling_28d__created_date" "user_count_rolling_28d__created_date",
"q_0"."test_events__user_count_rolling_28d" "user_count_rolling_28d__user_count_rolling_28d"
FROM
cte_0 AS "q_0"
```

## Expected Behavior

The first, intuitive SQL API query should trigger the rolling window logic without needing a redundant `date_trunc` wrapper. Both engines should generate the standard, correct SQL for a rolling window calculation, which involves a date-series CTE and a proper rolling join, as shown below (these are the actual results from the "Working Query").

#### With Tesseract:
```sql
WITH
time_series AS (
SELECT
d AS date_from,
date_add('MILLISECOND', -1, d + interval '1' day) AS date_to
FROM
UNNEST (
SEQUENCE(
CAST(from_iso8601_timestamp('2024-01-01T00:00:00.001') AS TIMESTAMP),
CAST(from_iso8601_timestamp('2024-02-29T23:59:59.999') AS TIMESTAMP),
INTERVAL '1' day
)
) AS dates (d)
),
cte_1 AS (
SELECT
date_trunc(
'day',
CAST(
date_add(
'minute',
timezone_minute(DATE_TRUNC('day', "test_events".created_ts) AT TIME ZONE 'UTC'),
date_add(
'hour',
timezone_hour(DATE_TRUNC('day', "test_events".created_ts) AT TIME ZONE 'UTC'),
DATE_TRUNC('day', "test_events".created_ts)
)
) AS TIMESTAMP
)
) "user_count_rolling_28d__created_date_day",
count("test_events".user_id) "test_events__user_count_rolling_28d"
FROM
(
(
SELECT
1 AS user_id,
TIMESTAMP '2024-01-01 10:00:00' AS created_ts
UNION ALL
SELECT
2 AS user_id,
TIMESTAMP '2024-01-02 14:00:00' AS created_ts
UNION ALL
SELECT
1 AS user_id,
TIMESTAMP '2024-01-15 08:00:00' AS created_ts
UNION ALL
SELECT
3 AS user_id,
TIMESTAMP '2024-02-20 11:00:00' AS created_ts
)
) AS "test_events"
WHERE
(
CAST(
date_add(
'minute',
timezone_minute(DATE_TRUNC('day', "test_events".created_ts) AT TIME ZONE 'UTC'),
date_add(
'hour',
timezone_hour(DATE_TRUNC('day', "test_events".created_ts) AT TIME ZONE 'UTC'),
DATE_TRUNC('day', "test_events".created_ts)
)
) AS TIMESTAMP
) >= (
SELECT
min("date_from") "value"
FROM
time_series
) - interval '28' day
AND CAST(
date_add(
'minute',
timezone_minute(DATE_TRUNC('day', "test_events".created_ts) AT TIME ZONE 'UTC'),
date_add(
'hour',
timezone_hour(DATE_TRUNC('day', "test_events".created_ts) AT TIME ZONE 'UTC'),
DATE_TRUNC('day', "test_events".created_ts)
)
) AS TIMESTAMP
) <= (
SELECT
max("date_to") "value"
FROM
time_series
)
)
GROUP BY
1
ORDER BY
1 ASC
),
cte_2 AS (
SELECT
"time_series"."date_from" "user_count_rolling_28d__created_date_day",
sum("rolling_source"."test_events__user_count_rolling_28d") "test_events__user_count_rolling_28d"
FROM
time_series AS "time_series"
LEFT JOIN cte_1 AS "rolling_source" ON "rolling_source"."user_count_rolling_28d__created_date_day" > "time_series"."date_to" - interval '28' day
AND "rolling_source"."user_count_rolling_28d__created_date_day" <= "time_series"."date_to"
GROUP BY
1
ORDER BY
1 ASC
)
SELECT
"q_0"."user_count_rolling_28d__created_date_day" "user_count_rolling_28d__created_date_day",
"q_0"."test_events__user_count_rolling_28d" "user_count_rolling_28d__user_count_rolling_28d"
FROM
cte_2 AS "q_0"
```

#### Without Tesseract:

```sql
SELECT
q_0."created_date",
"test_events__user_count_rolling_28d" "user_count_rolli"
FROM
(
SELECT
"user_count_rolling_28d.created_date_series"."date_from" "created_date",
sum("test_events__user_count_rolling_28d") "test_events__user_count_rolling_28d"
FROM (select '2024-01-01T00:00:00.000' f, '2024-01-01T23:59:59.999' t UNION ALL select '2024-01-02T00:00:00.000' f, '2024-01-02T23:59:59.999' t UNION ALL select '2024-01-03T00:00:00.000' f, '2024-01-03T23:59:59.999' t UNION ALL select '2024-01-04T00:00:00.000' f, '2024-01-04T23:59:59.999' t UNION ALL select '2024-01-05T00:00:00.000' f, '2024-01-05T23:59:59.999' t UNION ALL select '2024-01-06T00:00:00.000' f, '2024-01-06T23:59:59.999' t UNION ALL select '2024-01-07T00:00:00.000' f, '2024-01-07T23:59:59.999' t UNION ALL select '2024-01-08T00:00:00.000' f, '2024-01-08T23:59:59.999' t UNION ALL select '2024-01-09T00:00:00.000' f, '2024-01-09T23:59:59.999' t UNION ALL select '2024-01-10T00:00:00.000' f, '2024-01-10T23:59:59.999' t UNION ALL select '2024-01-11T00:00:00.000' f, '2024-01-11T23:59:59.999' t UNION ALL select '2024-01-12T00:00:00.000' f, '2024-01-12T23:59:59.999' t UNION ALL select '2024-01-13T00:00:00.000' f, '2024-01-13T23:59:59.999' t UNION ALL select '2024-01-14T00:00:00.000' f, '2024-01-14T23:59:59.999' t UNION ALL select '2024-01-15T00:00:00.000' f, '2024-01-15T23:59:59.999' t UNION ALL select '2024-01-16T00:00:00.000' f, '2024-01-16T23:59:59.999' t UNION ALL select '2024-01-17T00:00:00.000' f, '2024-01-17T23:59:59.999' t UNION ALL select '2024-01-18T00:00:00.000' f, '2024-01-18T23:59:59.999' t UNION ALL select '2024-01-19T00:00:00.000' f, '2024-01-19T23:59:59.999' t UNION ALL select '2024-01-20T00:00:00.000' f, '2024-01-20T23:59:59.999' t UNION ALL select '2024-01-21T00:00:00.000' f, '2024-01-21T23:59:59.999' t UNION ALL select '2024-01-22T00:00:00.000' f, '2024-01-22T23:59:59.999' t UNION ALL select '2024-01-23T00:00:00.000' f, '2024-01-23T23:59:59.999' t UNION ALL select '2024-01-24T00:00:00.000' f, '2024-01-24T23:59:59.999' t UNION ALL select '2024-01-25T00:00:00.000' f, '2024-01-25T23:59:59.999' t UNION ALL select '2024-01-26T00:00:00.000' f, '2024-01-26T23:59:59.999' t UNION ALL select '2024-01-27T00:00:00.000' f, '2024-01-27T23:59:59.999' t UNION ALL select '2024-01-28T00:00:00.000' f, '2024-01-28T23:59:59.999' t UNION ALL select '2024-01-29T00:00:00.000' f, '2024-01-29T23:59:59.999' t UNION ALL select '2024-01-30T00:00:00.000' f, '2024-01-30T23:59:59.999' t UNION ALL select '2024-01-31T00:00:00.000' f, '2024-01-31T23:59:59.999' t UNION ALL select '2024-02-01T00:00:00.000' f, '2024-02-01T23:59:59.999' t UNION ALL select '2024-02-02T00:00:00.000' f, '2024-02-02T23:59:59.999' t UNION ALL select '2024-02-03T00:00:00.000' f, '2024-02-03T23:59:59.999' t UNION ALL select '2024-02-04T00:00:00.000' f, '2024-02-04T23:59:59.999' t UNION ALL select '2024-02-05T00:00:00.000' f, '2024-02-05T23:59:59.999' t UNION ALL select '2024-02-06T00:00:00.000' f, '2024-02-06T23:59:59.999' t UNION ALL select '2024-02-07T00:00:00.000' f, '2024-02-07T23:59:59.999' t UNION ALL select '2024-02-08T00:00:00.000' f, '2024-02-08T23:59:59.999' t UNION ALL select '2024-02-09T00:00:00.000' f, '2024-02-09T23:59:59.999' t UNION ALL select '2024-02-10T00:00:00.000' f, '2024-02-10T23:59:59.999' t UNION ALL select '2024-02-11T00:00:00.000' f, '2024-02-11T23:59:59.999' t UNION ALL select '2024-02-12T00:00:00.000' f, '2024-02-12T23:59:59.999' t UNION ALL select '2024-02-13T00:00:00.000' f, '2024-02-13T23:59:59.999' t UNION ALL select '2024-02-14T00:00:00.000' f, '2024-02-14T23:59:59.999' t UNION ALL select '2024-02-15T00:00:00.000' f, '2024-02-15T23:59:59.999' t UNION ALL select '2024-02-16T00:00:00.000' f, '2024-02-16T23:59:59.999' t UNION ALL select '2024-02-17T00:00:00.000' f, '2024-02-17T23:59:59.999' t UNION ALL select '2024-02-18T00:00:00.000' f, '2024-02-18T23:59:59.999' t UNION ALL select '2024-02-19T00:00:00.000' f, '2024-02-19T23:59:59.999' t UNION ALL select '2024-02-20T00:00:00.000' f, '2024-02-20T23:59:59.999' t UNION ALL select '2024-02-21T00:00:00.000' f, '2024-02-21T23:59:59.999' t UNION ALL select '2024-02-22T00:00:00.000' f, '2024-02-22T23:59:59.999' t UNION ALL select '2024-02-23T00:00:00.000' f, '2024-02-23T23:59:59.999' t UNION ALL select '2024-02-24T00:00:00.000' f, '2024-02-24T23:59:59.999' t UNION ALL select '2024-02-25T00:00:00.000' f, '2024-02-25T23:59:59.999' t UNION ALL select '2024-02-26T00:00:00.000' f, '2024-02-26T23:59:59.999' t UNION ALL select '2024-02-27T00:00:00.000' f, '2024-02-27T23:59:59.999' t UNION ALL select '2024-02-28T00:00:00.000' f, '2024-02-28T23:59:59.999' t UNION ALL select '2024-02-29T00:00:00.000' f, '2024-02-29T23:59:59.999' t) AS dates) AS "user_count_rolling_28d.created_date_series"
LEFT JOIN (
SELECT
date_trunc(
'day',
CAST(
date_add(
'minute',
timezone_minute(
DATE_TRUNC('day', "test_events_user_count_rolling_28d_cumulative__test_events".created_ts) AT TIME ZONE 'UTC'
),
date_add(
'hour',
timezone_hour(
DATE_TRUNC('day', "test_events_user_count_rolling_28d_cumulative__test_events".created_ts) AT TIME ZONE 'UTC'
),
DATE_TRUNC('day', "test_events_user_count_rolling_28d_cumulative__test_events".created_ts)
)
) AS TIMESTAMP
)
) "created_date",
count("test_events_user_count_rolling_28d_cumulative__test_events".user_id) "test_events__user_count_rolling_28d"
FROM
(
(
SELECT
1 AS user_id,
TIMESTAMP '2024-01-01 10:00:00' AS created_ts
UNION ALL
SELECT
2 AS user_id,
TIMESTAMP '2024-01-02 14:00:00' AS created_ts
UNION ALL
SELECT
1 AS user_id,
TIMESTAMP '2024-01-15 08:00:00' AS created_ts
UNION ALL
SELECT
3 AS user_id,
TIMESTAMP '2024-02-20 11:00:00' AS created_ts
)
) AS "test_events_user_count_rolling_28d_cumulative__test_events"
WHERE
(
CAST(
date_add(
'minute',
timezone_minute(
DATE_TRUNC('day', "test_events_user_count_rolling_28d_cumulative__test_events".created_ts) AT TIME ZONE 'UTC'
),
date_add(
'hour',
timezone_hour(
DATE_TRUNC('day', "test_events_user_count_rolling_28d_cumulative__test_events".created_ts) AT TIME ZONE 'UTC'
),
DATE_TRUNC('day', "test_events_user_count_rolling_28d_cumulative__test_events".created_ts)
)
) AS TIMESTAMP
) > from_iso8601_timestamp(?) - interval '28' day
AND CAST(
date_add(
'minute',
timezone_minute(
DATE_TRUNC('day', "test_events_user_count_rolling_28d_cumulative__test_events".created_ts) AT TIME ZONE 'UTC'
),
date_add(
'hour',
timezone_hour(
DATE_TRUNC('day', "test_events_user_count_rolling_28d_cumulative__test_events".created_ts) AT TIME ZONE 'UTC'
),
DATE_TRUNC('day', "test_events_user_count_rolling_28d_cumulative__test_events".created_ts)
)
) AS TIMESTAMP
) <= from_iso8601_timestamp(?)
)
GROUP BY
1
) AS "test_events_user_count_rolling_28d_cumulative__base" ON "test_events_user_count_rolling_28d_cumulative__base"."created_date" > "user_count_rolling_28d.created_date_series"."date_to" - interval '28' day
AND "test_events_user_count_rolling_28d_cumulative__base"."created_date" <= "user_count_rolling_28d.created_date_series"."date_to"
GROUP BY
1
) as q_0
```

## Version
1.3.39

## Additional context
The query planner in both the legacy and Tesseract engines seems to have a rigid condition for activating rolling window logic. It appears to be strictly dependent on the presence of a `date_trunc()` function call in the SQL query's `SELECT` list. It does not analyze the properties of the selected dimension itself to determine if it already has the correct granularity. Consequently, when the `date_trunc()` function is absent from the query, the planner takes the wrong path and fails to apply the rolling window.