我正在撰写报告以生成
我有这样的数据
CREATE TABLE stops
([TripStopId] [int] IDENTITY(1,1) NOT NULL,[ObjectId] int, [DateFrom] varchar(23), [DateTo] varchar(23), [X] int, [Y] int, [ByIgnition] int, [BySpeed0] int, [BySpeed5] int, [BySpeed10] int, [BySpeed15] int, [ByCanSpeed0] int, [ByCanSpeed5] int, [ByCanSpeed10] int, [ByCanSpeed15] int, [GpsDistance] int, [CanDistance] int, [OdometerDistance] int, [Location] int)
;
INSERT INTO stops
([ObjectId], [DateFrom], [DateTo], [X], [Y], [ByIgnition], [BySpeed0], [BySpeed5], [BySpeed10], [BySpeed15], [ByCanSpeed0], [ByCanSpeed5], [ByCanSpeed10], [ByCanSpeed15], [GpsDistance], [CanDistance], [OdometerDistance], [Location])
VALUES
(2729, '2016-01-27 06:21:51.320', '2016-01-27 06:22:27.070', 46.651984, 24.6881872, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0.0086855611934854, 0, 0, NULL),
(2729, '2016-01-27 06:22:27.070', '2016-01-27 06:22:54.000', 46.652, 24.6881104, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0.0667479017095136, 0, 0, NULL),
(2729, '2016-01-27 06:22:54.000', '2016-01-27 06:23:03.920', 46.651408, 24.68804, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0.0248830291828213, 0, 0, NULL),
(2729, '2016-01-27 06:23:03.920', '2016-01-27 06:23:05.920', 46.6511616, 24.6880448, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0.00384351436414536, 0, 0, NULL),
(2729, '2016-01-27 06:23:05.920', '2016-01-27 06:23:15.910', 46.651136, 24.6880704, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0.104523323509783, 0, 0, NULL),
(2729, '2016-01-27 06:23:15.910', '2016-01-27 06:25:32.820', 46.6509376, 24.6889936, 1, 1, 1, 1, 1, 0, 0, 0, 0, 1.57522938946324, 0, 0, NULL),
(2729, '2016-01-27 06:25:32.820', '2016-01-27 06:25:53.810', 46.636304, 24.6873888, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0.0144023488655963, 0, 0, NULL),
(2729, '2016-01-27 06:25:53.810', '2016-01-27 06:27:14.700', 46.6361632, 24.6874096, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0.00893761079401728, 0, 0, NULL),
(2729, '2016-01-27 06:27:14.700', '2016-01-27 06:27:21.680', 46.6360864, 24.6873696, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0.0369525263958736, 0, 0, NULL),
(2729, '2016-01-27 06:27:21.680', '2016-01-27 06:27:34.680', 46.6358208, 24.6871408, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0.0333843719279574, 0, 0, NULL),
(2729, '2016-01-27 06:27:34.680', '2016-01-27 06:27:45.660', 46.6354912, 24.6871648, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0.114545761834751, 0, 0, NULL),
(2729, '2016-01-27 06:27:45.660', '2016-01-27 06:35:00.480', 46.6346432, 24.6878496, 1, 1, 1, 1, 1, 0, 0, 0, 0, 7.52942986526197, 0, 0, NULL)
;
-
+----------+-------------------------+-------------------------+------------+------------+------------+----------+----------+-----------+-----------+-------------+-------------+--------------+--------------+---------------------+-------------+------------------+----------+
| ObjectId | DateFrom | DateTo | X | Y | ByIgnition | BySpeed0 | BySpeed5 | BySpeed10 | BySpeed15 | ByCanSpeed0 | ByCanSpeed5 | ByCanSpeed10 | ByCanSpeed15 | GpsDistance | CanDistance | OdometerDistance | Location |
+----------+-------------------------+-------------------------+------------+------------+------------+----------+----------+-----------+-----------+-------------+-------------+--------------+--------------+---------------------+-------------+------------------+----------+
| 2729 | 2016-01-27 06:21:51.320 | 2016-01-27 06:22:27.070 | 46.651984 | 24.6881872 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.0086855611934854 | 0 | 0 | |
| 2729 | 2016-01-27 06:22:27.070 | 2016-01-27 06:22:54.000 | 46.652 | 24.6881104 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0.0667479017095136 | 0 | 0 | |
| 2729 | 2016-01-27 06:22:54.000 | 2016-01-27 06:23:03.920 | 46.651408 | 24.68804 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0.0248830291828213 | 0 | 0 | |
| 2729 | 2016-01-27 06:23:03.920 | 2016-01-27 06:23:05.920 | 46.6511616 | 24.6880448 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0.00384351436414536 | 0 | 0 | |
| 2729 | 2016-01-27 06:23:05.920 | 2016-01-27 06:23:15.910 | 46.651136 | 24.6880704 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0.104523323509783 | 0 | 0 | |
| 2729 | 2016-01-27 06:23:15.910 | 2016-01-27 06:25:32.820 | 46.6509376 | 24.6889936 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 1.57522938946324 | 0 | 0 | |
| 2729 | 2016-01-27 06:25:32.820 | 2016-01-27 06:25:53.810 | 46.636304 | 24.6873888 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0.0144023488655963 | 0 | 0 | |
| 2729 | 2016-01-27 06:25:53.810 | 2016-01-27 06:27:14.700 | 46.6361632 | 24.6874096 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.00893761079401728 | 0 | 0 | |
| 2729 | 2016-01-27 06:27:14.700 | 2016-01-27 06:27:21.680 | 46.6360864 | 24.6873696 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0.0369525263958736 | 0 | 0 | |
| 2729 | 2016-01-27 06:27:21.680 | 2016-01-27 06:27:34.680 | 46.6358208 | 24.6871408 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0.0333843719279574 | 0 | 0 | |
| 2729 | 2016-01-27 06:27:34.680 | 2016-01-27 06:27:45.660 | 46.6354912 | 24.6871648 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0.114545761834751 | 0 | 0 | |
| 2729 | 2016-01-27 06:27:45.660 | 2016-01-27 06:35:00.480 | 46.6346432 | 24.6878496 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 7.52942986526197 | 0 | 0 | |
+----------+-------------------------+-------------------------+------------+------------+------------+----------+----------+-----------+-----------+-------------+-------------+--------------+--------------+---------------------+-------------+------------------+----------+
每辆车的数据移动及其起点X，Y和总距离
任何比CURSOR更好的方式，因为我相信CURSOR是SLOW，做出以下
我问最好的方法，因为这份报告可以有超过100万次的行程停止行
这是CURSOR的预期结果，需要很长时间才能输出
+----------+-------------------------+-------------------------+------------+------------+------------+------------+----------+----------+----------+----------+----------+--------+-----------+----------+-----------+----------+---------+--------------+--------------+------------+------------+---------------------+------------+----------+-------------+----------+
| ObjectId | DateFrom | DateTo | X | Y | X2 | Y2 | IsMoving | Distance | Location | AvgSpeed | DriverId | Driver | IButtonId | DateYear | DateMonth | DateWeek | DateDay | StartGeoName | StartAddress | EndGeoName | EndAddress | DeductionPointValue | PoiAtStart | PoiAtEnd | DrivingTime | StopTime |
+----------+-------------------------+-------------------------+------------+------------+------------+------------+----------+----------+----------+----------+----------+--------+-----------+----------+-----------+----------+---------+--------------+--------------+------------+------------+---------------------+------------+----------+-------------+----------+
| 2729 | 2016-01-27 06:21:51.320 | 2016-01-27 06:22:27.070 | 46.651984 | 24.6881872 | 46.652 | 24.6881104 | 0 | 0.01 | | 0.87 | NULL | NULL | NULL | 2016 | 1 | 5 | 27 | | NULL | NULL | NULL | 0.01 | NULL | NULL | 0 | 35750 |
| 2729 | 2016-01-27 06:22:27.070 | 2016-01-27 06:25:53.810 | 46.652 | 24.6881104 | 46.6361632 | 24.6874096 | 1 | 1.79 | | 31.16 | NULL | NULL | NULL | 2016 | 1 | 5 | 27 | | NULL | NULL | NULL | 1.8 | NULL | NULL | 206740 | 0 |
| 2729 | 2016-01-27 06:25:53.810 | 2016-01-27 06:27:14.700 | 46.6361632 | 24.6874096 | 46.6360864 | 24.6873696 | 0 | 0.01 | | 0.4 | NULL | NULL | NULL | 2016 | 1 | 5 | 27 | | NULL | NULL | NULL | 1.81 | NULL | NULL | 0 | 80890 |
| 2729 | 2016-01-27 06:27:14.700 | 2016-01-27 06:35:00.480 | 46.6360864 | 24.6873696 | NULL | NULL | 1 | 7.71 | | 59.62 | NULL | NULL | NULL | 2016 | 1 | 5 | 27 | | NULL | NULL | NULL | 9.52 | NULL | NULL | 465780 | 0 |
+----------+-------------------------+-------------------------+------------+------------+------------+------------+----------+----------+----------+----------+----------+--------+-----------+----------+-----------+----------+---------+--------------+--------------+------------+------------+---------------------+------------+----------+-------------+----------+
答案 0 :(得分：1)
我没有对此进行测试，以确保我没有错误，但是这样的事情应该可以解决问题。我们的想法是根据BySpeed0列将值组合在一起，然后进行聚合。
WITH AdjacentValues AS (
/*
This adds the prior BySpeed0 value to the row
*/
SELECT
ObjectID,
DateFrom,
DateTo,
X,
Y,
[BySpeed0] AS 'IsMoving',
LAG([BySpeed0]) OVER (PARTITION BY ObjectID ORDER BY DateFrom ASC) AS 'PriorValue'
FROM
stops
), GroupedResults AS (
/*
This will create a number that increments every time the current BySpeed0 value is not the same as the next one.
*/
SELECT
ObjectID,
DateFrom,
DateTo,
X,
Y,
IsMoving,
NextValue,
SUM(IIF(IsMoving <> PriorValue, 1, 0)) OVER (PARTITION BY ObjectID ORDER BY DateFrom ASC) AS 'GroupingValue'
FROM
AdjacentValues
), AggregateResult AS (
/*
This will Select the minimum date and maximum date for a particular grouping
*/
SELECT
ObjectID,
MIN(DateFrom) AS 'DateFrom',
MAX(DateTo) AS 'DateTo'
FROM
AdjacentValues
GROUP BY
ObjectID,
GroupingValue
)
/*
This will add the X/Y information
*/
SELECT
R.*,
A.X,
A.Y,
AA.X AS 'X2',
AA.Y AS 'Y2'
FROM
AggregateResult R
LEFT JOIN
AdjacentValues A
ON
A.DateFrom = R.DateFrom
AND A.ObjectID = R.ObjectID
LEFT JOIN
AdjacentValues AA
ON
AA.DateTo = R.DateTo
AND A.ObjectID = R.ObjectID
P.S。如果您正在使用空间数据，则只需稍作调整即可将这些坐标对转换为几何/地理线。
答案 1 :(得分：1)
with cte as
(
select tripstopid,datefrom,dateto,x,y,byspeed0,
case when lag(byspeed0,1,'') over(order by datefrom,dateto) = byspeed0 then 0 else 1 end as ischange from stops
),cte1 as
(
select t.*,
(select sum(ischange) from cte where tripstopid <= t.tripstopid) groupno
from cte t
),cte3 as
(
select *,row_number() over(partition by groupno order by tripstopid) as rn1 from cte1
),cte4 as
(
select *from cte3
where rn1=1
)
select *from cte4 c1 left
join cte4 c2 on c1.groupno+1 =c2.groupno
order by c1.datefrom
答案 2 :(得分：0)
这是核心查询，您可以在其中包含其他计算列：
WITH CTE AS
(
SELECT S.*
FROM stops S
INNER JOIN
(SELECT A.TripStopId AS TA, B.TripStopId AS TB
FROM stops A
INNER JOIN stops B ON A.ObjectId = B.ObjectId AND A.DateTo = B.DateFrom
WHERE A.BySpeed0 = 0 AND B.BySpeed0 = 1) T ON S.TripStopId = T.TA OR S.TripStopId = T.TB
)
SELECT CTE.TripStopId, CTE.ObjectId, CTE.DateFrom, CTE.DateTo, CTE.X, CTE.Y, S.X AS X2, S.Y AS Y2, CTE.BySpeed0 AS IsMoving
FROM CTE
LEFT JOIN stops S ON CTE.ObjectId = S.ObjectId
AND ((CTE.BySpeed0 = 0 AND S.BySpeed0 = 1 AND CTE.DateTo = S.DateFrom)
OR (CTE.BySpeed0 = 1 AND S.BySpeed0 = 0 AND CTE.DateTo <= S.DateFrom))