Postgresql 如何计算刷卡和刷卡时间

您可以使用lead/lag以及一些Case/WHEN/End来实现这一点.

Schema (PostgreSQL v15)

CREATE TABLE swipes (
    "username"  VARCHAR(6),
    "building"  VARCHAR(10),
    "action"    VARCHAR(3),
    "timestamp" TIMESTAMP
);

INSERT INTO swipes
    ("username", "building", "action", "timestamp")
VALUES ('user-1', 'building-1', 'IN', '2024-04-10 01:00:00.000')
     , ('user-1', 'building-1', 'OUT', '2024-04-10 02:00:00.000')
     , ('user-1', 'building-1', 'IN', '2024-04-10 02:30:00.000')
     , ('user-1', 'building-1', 'OUT', '2024-04-10 04:00:00.000')
     , ('user-1', 'building-1', 'IN', '2024-04-11 10:00:00.000')
     , ('user-1', 'building-1', 'OUT', '2024-04-11 11:00:00.000')
     , ('user-2', 'building-2', 'IN', '2024-04-10 08:00:00.000')
     , ('user-2', 'building-2', 'OUT', '2024-04-10 09:00:00.000')
     , ('user-2', 'building-3', 'OUT', '2024-04-11 02:30:00.000')
     , ('user-2', 'building-4', 'IN', '2024-04-11 04:00:00.000')
     , ('user-2', 'building-1', 'IN', '2024-04-12 10:00:00.000')
     , ('user-2', 'building-1', 'OUT', '2024-04-12 11:00:00.000')
     -- added those rows to showcase the results when the same action happens twice in a row
     , ('user-3', 'building-1', 'IN', '2024-04-12 11:00:00.000')
     , ('user-3', 'building-1', 'IN', '2024-04-12 12:00:00.000')
     , ('user-3', 'building-1', 'OUT', '2024-04-12 13:00:00.000')
;

Query #1

-- Since the information may be partial we can't simply look at all "in"s or "out"s,
-- so we look at all the rows & end up with everything twice, hence the DISTINCT.
SELECT DISTINCT
       username
     , building
     , CASE
           WHEN action = 'IN' THEN timestamp
           -- To find the entry time corresponding to this "out" row, we'll look at the previous row.
           -- If it's an "in", then we keep the timestamp.
           -- If it's an "out", then there were 2 "outs" in a row, so the "in" value is set to null (see user-3's rows for an example of this).
           WHEN action = 'OUT' THEN
               CASE WHEN LAG(action) OVER user_actions_per_building_by_timestamp = 'IN'
                   THEN LAG(timestamp) OVER user_actions_per_building_by_timestamp
               END
       END AS "in"
     , CASE
           -- same concept as above, with IN/OUT & LAG/LEAD flipped.
           WHEN action = 'IN' THEN
               CASE WHEN LEAD(action) OVER user_actions_per_building_by_timestamp = 'OUT'
                   THEN LEAD(timestamp) OVER user_actions_per_building_by_timestamp
               END
           WHEN action = 'OUT' THEN timestamp
    END AS "out"
FROM swipes
WINDOW user_actions_per_building_by_timestamp AS (PARTITION BY username, building ORDER BY timestamp)
ORDER BY username, building, "in", "out";

View on DB Fiddle

另一种方法可以是使用循环CTE，如果条件变得更加复杂，它可能会更容易理解(而且它的性能也会有所不同，尽管您需要对照一些实际数据判断这一点).