尝试

SELECT d.id, MIN(dt) AS start_dt, MAX(dt) AS end_dt
FROM 
(
    SELECT 
        d.*, 
        row_number() OVER(PARTITION BY id ORDER BY dt) - row_number() OVER(PARTITION BY id, type ORDER BY dt) AS grp
    FROM DATA d
) d
WHERE d.type = 'Error'
GROUP BY d.id, d.grp HAVING( COUNT(d.id) >= 3 )
;

谢谢你，P3咨询。它的工作，我将深入到差距和岛屿的问题更多。下面是我编辑的结果与虚拟数据。

WITH DATA AS (
SELECT 'A' AS id, cast('2023-04-01 5:00:00' as datetime) AS dt, 'Success' AS type UNION ALL
SELECT 'A', cast('2023-04-01 5:30:00' as datetime), 'Error' UNION ALL
SELECT 'A', cast('2023-04-01 5:33:00' as datetime), 'Error' UNION ALL
SELECT 'A', cast('2023-04-01 5:34:00' as datetime), 'Error' UNION ALL
SELECT 'A', cast('2023-04-01 5:40:00' as datetime), 'Error' UNION ALL
SELECT 'B', cast('2023-04-01 4:00:00' as datetime), 'Success' UNION ALL
SELECT 'B', cast('2023-04-01 4:20:00' as datetime), 'Error' UNION ALL
SELECT 'B', cast('2023-04-01 4:45:00' as datetime), 'Error' UNION ALL
SELECT 'B', cast('2023-04-01 4:50:00' as datetime), 'Error' ),

base as (
  SELECT 
    d.*,
    row_number() OVER(PARTITION BY id ORDER BY dt) as rn1,
    row_number() OVER(PARTITION BY id, type ORDER BY dt) as rn2,
    row_number() OVER(PARTITION BY id ORDER BY dt) - row_number() OVER(PARTITION BY id, type ORDER BY dt) AS grp
FROM DATA d)

SELECT 
base.id,
base.type,
MIN(dt) AS start_dt, 
MAX(dt) AS end_dt,
COUNT(base.id) AS activities
FROM base
WHERE base.type = 'Error'
GROUP BY base.id, base.grp, base.type
HAVING(COUNT(base.id) >= 3 )
ORDER BY base.id;