我用这个最终答案取代了原来的问题。在MTO先生和Ponder Stibbons先生的帮助下，我和我的oracle 11G实例玩了四个月，我终于得到了你在这里看到的东西。此查询主要用于SCADA系统，并将执行以下操作...
此查询将在两个日期时间之间每小时执行一次时间加权平均值，该间隔期间的TWA，最小值和最大值为Vmin和Vmax。它还将返回最小时间和最大时间为Hmin和Hmax。 （这些是最小值出现和最大值出现的日期时间。）起始和结束间隔值为VSTART和VEND。在3月或8月的夏令时，此查询不会失败。 （这就是我使用TO_TIMESTAMP_TZ的原因）
注意：此查询设置为1小时间隔，并且可以通过替换和添加几个项目来实现任何所需的间隔。所以尽情享受!!!
此查询在我的Oracle 11g实例中有效，在写完这篇文章后，我复制了下面的确切文本并粘贴到我的SQL Developer中。它的确有效！ 我在sqlfiddle中运行它时遇到了麻烦，但很快我就会想出来并为你进行运行测试。
-- Lets Begin the Query
WITH INPUTS AS (
SELECT RECNM,
TO_TIMESTAMP_TZ ( '01-JAN-15 00:00:00 AMERICA/LOS_ANGELES','DD-MON-RR HH24:MI:SS TZR' ) AS START_TIME,
TO_TIMESTAMP_TZ ( '06-NOV-15 23:59:59 AMERICA/LOS_ANGELES','DD-MON-RR HH24:MI:SS TZR' ) AS END_TIME
FROM POINTS
WHERE ACRONYM = 'WELL32-PSI'
) ,
ALL_INTERVALS AS (
SELECT RECNM,
START_TIME + NUMTODSINTERVAL ( ( LEVEL-1 ) , 'HOUR' ) AS TIME
FROM INPUTS
CONNECT BY
LEVEL-1 <=
EXTRACT ( DAY FROM END_TIME - START_TIME ) * 24 +
EXTRACT ( HOUR FROM END_TIME - START_TIME )
) ,
ALL_TIMES AS (
SELECT
TIME,
VALUE,
1 AS HAS_VALUE
FROM HST H
INNER JOIN INPUTS I
ON ( H.RECNM = I.RECNM
AND H.TIME BETWEEN CAST ( I.START_TIME AS TIMESTAMP )
AND CAST ( I.END_TIME AS TIMESTAMP ) )
UNION ALL
SELECT
TIME,
NULL,
0
FROM ALL_INTERVALS
ORDER BY TIME,1, 2 NULLS FIRST
) ,
LEAD_LAG_TIMES AS (
SELECT
TIME,
LAST_VALUE ( VALUE IGNORE NULLS ) OVER ( ORDER BY TIME ASC, VALUE ASC ) AS VALUE,
24 * 60 * 60 * EXTRACT ( DAY FROM LEAD ( TIME ) OVER ( ORDER BY TIME ASC,VALUE ASC ) -TIME ) +
60 * 60 * EXTRACT ( HOUR FROM LEAD ( TIME ) OVER ( ORDER BY TIME ASC,VALUE ASC ) -TIME ) +
60 * EXTRACT ( MINUTE FROM LEAD ( TIME ) OVER ( ORDER BY TIME ASC,VALUE ASC ) -TIME ) +
EXTRACT ( SECOND FROM LEAD ( TIME ) OVER ( ORDER BY TIME ASC,VALUE ASC ) -TIME ) AS DURATION
FROM ALL_TIMES
)
SELECT CAST ( TRUNC ( TIME,'HH24' ) AS TIMESTAMP WITH TIME ZONE ) AS TIME,
SUM ( VALUE * DURATION ) / SUM ( DURATION ) AS TWA,
MIN ( VALUE ) AS VMIN,
MAX ( TIME ) KEEP ( DENSE_RANK LAST ORDER BY VALUE DESC ) AS TMIN,
MAX ( VALUE ) AS VMAX,
MAX ( TIME ) KEEP ( DENSE_RANK LAST ORDER BY VALUE ASC ) AS TMAX,
SUM ( VALUE ) AS TOTAL,
MAX ( VALUE ) KEEP (DENSE_RANK FIRST ORDER BY TIME ASC) as VSTART,
MAX ( VALUE ) KEEP (DENSE_RANK LAST ORDER BY TIME ASC) as VEND,
SUM ( DURATION ) AS TOTAL_DURATION
FROM LEAD_LAG_TIMES
GROUP BY CAST ( TRUNC ( TIME,'HH24' ) AS TIMESTAMP WITH TIME ZONE )
ORDER BY TIME ASC
编辑：您可以在最终选择语句中包含这个时间加权的1小时滚动平均值！我发现这在废水行业非常有用，因为州法规/报告要求24小时滚动平均值和72分钟滚动平均值。如果您需要24个滚动平均值更改ROWS 1 PROCECDING to ROWS 24 PROCEDING
ROUND( AVG ( SUM ( value * DURATION ) / sum ( DURATION ) ) OVER (ORDER BY CAST ( TRUNC ( TIME,'hh24' ) AS TIMESTAMP WITH TIME ZONE ), CAST ( TRUNC ( TIME,'hh24' ) AS TIMESTAMP WITH TIME ZONE ) ROWS 1 PRECEDING),2) AS ROLLING_1H_VAVG,
标准偏差很有趣，所以也要添加它。
ROUND( STDDEV ( VALUE ) , 2 ) as VDEV,
如果您需要在开始时间之前和停止时间之后的值，您可以将其与其他工会全部放在一起。
UNION ALL
SELECT
MAX(H.TIME) KEEP (DENSE_RANK FIRST ORDER BY H.TIME DESC) AS TIME,
MAX(H.VALUE) KEEP (DENSE_RANK FIRST ORDER BY H.TIME DESC),
1
FROM INPUTS I
INNER JOIN HST H
ON H.TIME < I.START_TIME
UNION ALL
SELECT
MIN(H.TIME) KEEP (DENSE_RANK FIRST ORDER BY H.TIME) AS TIME,
MIN(H.VALUE) KEEP (DENSE_RANK FIRST ORDER BY H.TIME),
1
FROM INPUTS I
INNER JOIN HST H
ON H.TIME > I.END_TIME
答案 0 :(得分：2)
使用您的示例数据 - 它没有完整的小时数据，所以我已经完成了每分钟的加权平均值。
您尚未在边界处指定要执行的操作，因此我已采用前一个和后一个值的加权平均值。
Oracle 11g R2架构设置：
CREATE TABLE TEST ( Acronym, Date_Time, Value ) AS
SELECT '32-PRESS', TIMESTAMP '15-01-01 00:00:07.120000000', 63.7363 FROM DUAL
UNION ALL SELECT '32-PRESS', TIMESTAMP '15-01-01 00:00:17.088000000', 64.5604 FROM DUAL
UNION ALL SELECT '32-PRESS', TIMESTAMP '15-01-01 00:00:27.864000000', 66.3004 FROM DUAL
UNION ALL SELECT '32-PRESS', TIMESTAMP '15-01-01 00:00:45.080000000', 66.804 FROM DUAL
UNION ALL SELECT '32-PRESS', TIMESTAMP '15-01-01 00:00:55.056000000', 67.4908 FROM DUAL
UNION ALL SELECT '32-PRESS', TIMESTAMP '15-01-01 00:01:11.384000000', 66.9872 FROM DUAL
UNION ALL SELECT '32-PRESS', TIMESTAMP '15-01-01 00:01:30.424000000', 67.4451 FROM DUAL
UNION ALL SELECT '32-PRESS', TIMESTAMP '15-01-01 00:01:40.408000000', 67.9487 FROM DUAL
UNION ALL SELECT '32-PRESS', TIMESTAMP '15-01-01 00:01:50.408000000', 68.6813 FROM DUAL
UNION ALL SELECT '32-PRESS', TIMESTAMP '15-01-01 00:02:01.304000000', 68.1777 FROM DUAL
UNION ALL SELECT '32-PRESS', TIMESTAMP '15-01-01 00:02:11.304000000', 67.1245 FROM DUAL
UNION ALL SELECT '32-PRESS', TIMESTAMP '15-01-01 00:02:21.264000000', 66.5293 FROM DUAL
UNION ALL SELECT '32-PRESS', TIMESTAMP '15-01-01 00:02:31.232000000', 65.4762 FROM DUAL
UNION ALL SELECT '32-PRESS', TIMESTAMP '15-01-01 00:02:45.736000000', 65.0183 FROM DUAL
UNION ALL SELECT '32-PRESS', TIMESTAMP '15-01-01 00:02:59.312000000', 64.5604 FROM DUAL
UNION ALL SELECT '32-PRESS', TIMESTAMP '15-01-01 00:03:14.712000000', 64.1026 FROM DUAL;
查询1 ：
WITH temp AS (
SELECT ACRONYM,
DATE_TIME,
VALUE
FROM TEST
UNION
SELECT ACRONYM,
TO_TIMESTAMP( TO_CHAR( DATE_TIME, 'YYYY-MM-DD HH24:MI' ), 'YYYY-MM-DD HH24:MI' ),
NULL
FROM TEST
GROUP BY
ACRONYM,
TO_TIMESTAMP( TO_CHAR( DATE_TIME, 'YYYY-MM-DD HH24:MI' ), 'YYYY-MM-DD HH24:MI' )
UNION
SELECT ACRONYM,
TO_TIMESTAMP( TO_CHAR( DATE_TIME, 'YYYY-MM-DD HH24:MI' ), 'YYYY-MM-DD HH24:MI' ) + INTERVAL '1' MINUTE,
NULL
FROM TEST
GROUP BY
ACRONYM,
TO_TIMESTAMP( TO_CHAR( DATE_TIME, 'YYYY-MM-DD HH24:MI' ), 'YYYY-MM-DD HH24:MI' )
ORDER BY
1,2
),
temp2 AS (
SELECT ACRONYM,
DATE_TIME,
COALESCE(
VALUE,
COALESCE(
LAG( VALUE ) OVER ( PARTITION BY ACRONYM ORDER BY DATE_TIME ),
LEAD( VALUE ) OVER ( PARTITION BY ACRONYM ORDER BY DATE_TIME )
)
+
(
COALESCE(
LEAD( VALUE ) OVER ( PARTITION BY ACRONYM ORDER BY DATE_TIME ),
LAG( VALUE ) OVER ( PARTITION BY ACRONYM ORDER BY DATE_TIME )
)
-
COALESCE(
LAG( VALUE ) OVER ( PARTITION BY ACRONYM ORDER BY DATE_TIME ),
LEAD( VALUE ) OVER ( PARTITION BY ACRONYM ORDER BY DATE_TIME )
)
)
*
EXTRACT( SECOND FROM ( DATE_TIME - LAG( DATE_TIME, 1, DATE_TIME ) OVER ( PARTITION BY ACRONYM ORDER BY DATE_TIME ) ) )
/
EXTRACT( SECOND FROM (
LEAD( DATE_TIME, 1, DATE_TIME ) OVER ( PARTITION BY ACRONYM ORDER BY DATE_TIME )
-
LAG( DATE_TIME, 1, DATE_TIME ) OVER ( PARTITION BY ACRONYM ORDER BY DATE_TIME )
) )
) AS VALUE,
LEAD( DATE_TIME ) OVER ( PARTITION BY ACRONYM ORDER BY DATE_TIME ) AS NEXT_DATE_TIME
FROM temp
)
SELECT ACRONYM,
TO_DATE( TO_CHAR( DATE_TIME, 'YYYY-MM-DD HH24:MI' ), 'YYYY-MM-DD HH24:MI' ) AS DATE_TIME,
SUM( VALUE * EXTRACT( SECOND FROM ( NEXT_DATE_TIME - DATE_TIME ) ) ) / 60 AS VALUE
FROM temp2
WHERE NEXT_DATE_TIME IS NOT NULL
GROUP BY
ACRONYM,
TO_DATE( TO_CHAR( DATE_TIME, 'YYYY-MM-DD HH24:MI' ), 'YYYY-MM-DD HH24:MI' )
ORDER BY
1,2
<强> Results ：
| ACRONYM | DATE_TIME | VALUE |
|----------|---------------------------|-------------------|
| 32-PRESS | January, 01 0015 00:00:00 | 65.43946117333333 |
| 32-PRESS | January, 01 0015 00:01:00 | 67.56109262835211 |
| 32-PRESS | January, 01 0015 00:02:00 | 66.32093658633383 |
| 32-PRESS | January, 01 0015 00:03:00 | 64.20983764043636 |
修改
Oracle 11g R2架构设置：
CREATE TABLE POINTS ( RECNM NUMBER, ACRONYM VARCHAR2(20) );
INSERT INTO POINTS VALUES(1136, '32-PRESS');
INSERT INTO POINTS VALUES(1138, 'OTHER_POINT');
CREATE TABLE HST ( RECNM NUMBER, TIME TIMESTAMP, VALUE NUMBER );
INSERT INTO HST VALUES(1136, TIMESTAMP '15-01-01 00:00:00',63.3);
INSERT INTO HST VALUES(1138, TIMESTAMP '15-01-01 00:00:00',0.0);
INSERT INTO HST VALUES(1136, TIMESTAMP '15-01-01 00:00:07',63.7);
INSERT INTO HST VALUES(1136, TIMESTAMP '15-01-01 00:00:17',64.6);
INSERT INTO HST VALUES(1136, TIMESTAMP '15-01-01 00:00:28',66.3);
INSERT INTO HST VALUES(1136, TIMESTAMP '15-01-01 00:00:45',66.8);
INSERT INTO HST VALUES(1136, TIMESTAMP '15-01-01 00:00:55',67.5);
INSERT INTO HST VALUES(1136, TIMESTAMP '15-01-01 00:01:11',67.0);
INSERT INTO HST VALUES(1136, TIMESTAMP '15-01-01 00:01:30',67.4);
INSERT INTO HST VALUES(1136, TIMESTAMP '15-01-01 00:01:40',67.9);
INSERT INTO HST VALUES(1136, TIMESTAMP '15-01-01 00:01:50',68.7);
INSERT INTO HST VALUES(1136, TIMESTAMP '15-01-01 00:02:01',68.2);
INSERT INTO HST VALUES(1136, TIMESTAMP '15-01-01 00:02:11',67.1);
INSERT INTO HST VALUES(1136, TIMESTAMP '15-01-01 00:02:21',66.5);
INSERT INTO HST VALUES(1136, TIMESTAMP '15-01-01 00:02:31',65.5);
INSERT INTO HST VALUES(1136, TIMESTAMP '15-01-01 00:02:46',65.0);
INSERT INTO HST VALUES(1136, TIMESTAMP '15-01-01 00:02:59',64.6);
INSERT INTO HST VALUES(1136, TIMESTAMP '15-01-01 00:03:15',64.1);
INSERT INTO HST VALUES(1136, TIMESTAMP '15-01-01 00:03:25',63.2);
INSERT INTO HST VALUES(1136, TIMESTAMP '15-01-01 00:03:35',62.7);
INSERT INTO HST VALUES(1136, TIMESTAMP '15-01-01 00:04:05',62.2);
INSERT INTO HST VALUES(1136, TIMESTAMP '15-01-01 00:04:32',61.8);
INSERT INTO HST VALUES(1136, TIMESTAMP '15-01-01 00:05:40',61.3);
INSERT INTO HST VALUES(1136, TIMESTAMP '15-01-01 00:05:55',60.8);
INSERT INTO HST VALUES(1136, TIMESTAMP '15-01-01 00:10:20',60.3);
INSERT INTO HST VALUES(1136, TIMESTAMP '15-01-01 00:10:38',60.9);
INSERT INTO HST VALUES(1136, TIMESTAMP '15-01-01 00:10:48',61.3);
INSERT INTO HST VALUES(1136, TIMESTAMP '15-01-01 00:10:58',61.8);
INSERT INTO HST VALUES(1136, TIMESTAMP '15-01-01 00:11:27',62.3);
INSERT INTO HST VALUES(1136, TIMESTAMP '15-01-01 00:13:54',61.8);
INSERT INTO HST VALUES(1136, TIMESTAMP '15-01-01 00:14:10',61.4);
INSERT INTO HST VALUES(1136, TIMESTAMP '15-01-01 00:14:41',60.9);
INSERT INTO HST VALUES(1136, TIMESTAMP '15-01-01 00:15:18',61.4);
INSERT INTO HST VALUES(1136, TIMESTAMP '15-01-01 00:15:51',60.9);
INSERT INTO HST VALUES(1136, TIMESTAMP '15-01-01 00:16:19',60.4);
INSERT INTO HST VALUES(1136, TIMESTAMP '15-01-01 00:16:32',59.9);
INSERT INTO HST VALUES(1136, TIMESTAMP '15-01-01 00:17:04',59.4);
INSERT INTO HST VALUES(1136, TIMESTAMP '15-01-01 00:17:27',59.9);
INSERT INTO HST VALUES(1136, TIMESTAMP '15-01-01 00:17:37',59.4);
INSERT INTO HST VALUES(1136, TIMESTAMP '15-01-01 00:17:58',59.0);
INSERT INTO HST VALUES(1136, TIMESTAMP '15-01-01 00:18:22',59.4);
INSERT INTO HST VALUES(1136, TIMESTAMP '15-01-01 00:18:50',59.9);
INSERT INTO HST VALUES(1136, TIMESTAMP '15-01-01 00:19:00',60.3);
INSERT INTO HST VALUES(1136, TIMESTAMP '15-01-01 00:19:25',60.8);
INSERT INTO HST VALUES(1136, TIMESTAMP '15-01-01 00:19:34',61.4);
INSERT INTO HST VALUES(1136, TIMESTAMP '15-01-01 00:19:45',62.1);
INSERT INTO HST VALUES(1136, TIMESTAMP '15-01-01 00:19:55',62.5);
INSERT INTO HST VALUES(1136, TIMESTAMP '15-01-01 00:20:30',63.0);
INSERT INTO HST VALUES(1136, TIMESTAMP '15-01-01 00:20:51',63.5);
INSERT INTO HST VALUES(1136, TIMESTAMP '15-01-01 00:21:03',63.9);
INSERT INTO HST VALUES(1136, TIMESTAMP '15-01-01 00:22:04',64.4);
INSERT INTO HST VALUES(1136, TIMESTAMP '15-01-01 00:22:28',64.8);
INSERT INTO HST VALUES(1136, TIMESTAMP '15-01-01 00:23:17',64.4);
INSERT INTO HST VALUES(1136, TIMESTAMP '15-01-01 00:23:27',63.9);
INSERT INTO HST VALUES(1136, TIMESTAMP '15-01-01 00:24:31',63.4);
INSERT INTO HST VALUES(1136, TIMESTAMP '15-01-01 00:26:06',63.0);
INSERT INTO HST VALUES(1136, TIMESTAMP '15-01-01 00:27:20',62.5);
INSERT INTO HST VALUES(1136, TIMESTAMP '15-01-01 00:27:30',61.9);
INSERT INTO HST VALUES(1136, TIMESTAMP '15-01-01 00:28:08',62.4);
INSERT INTO HST VALUES(1136, TIMESTAMP '15-01-01 00:28:37',62.0);
INSERT INTO HST VALUES(1136, TIMESTAMP '15-01-01 00:29:21',62.5);
INSERT INTO HST VALUES(1136, TIMESTAMP '15-01-01 00:29:38',62.9);
INSERT INTO HST VALUES(1136, TIMESTAMP '15-01-01 00:31:27',62.5);
INSERT INTO HST VALUES(1136, TIMESTAMP '15-01-01 00:32:01',62.0);
INSERT INTO HST VALUES(1136, TIMESTAMP '15-01-01 00:32:25',62.5);
INSERT INTO HST VALUES(1136, TIMESTAMP '15-01-01 00:35:07',62.9);
INSERT INTO HST VALUES(1136, TIMESTAMP '15-01-01 00:35:56',62.5);
INSERT INTO HST VALUES(1136, TIMESTAMP '15-01-01 00:36:06',62.0);
INSERT INTO HST VALUES(1136, TIMESTAMP '15-01-01 00:36:59',61.5);
INSERT INTO HST VALUES(1136, TIMESTAMP '15-01-01 00:39:31',62.0);
INSERT INTO HST VALUES(1136, TIMESTAMP '15-01-01 00:40:12',61.5);
INSERT INTO HST VALUES(1136, TIMESTAMP '15-01-01 00:40:22',60.9);
INSERT INTO HST VALUES(1136, TIMESTAMP '15-01-01 00:40:35',60.5);
INSERT INTO HST VALUES(1136, TIMESTAMP '15-01-01 00:40:55',60.0);
INSERT INTO HST VALUES(1136, TIMESTAMP '15-01-01 00:41:22',60.5);
INSERT INTO HST VALUES(1136, TIMESTAMP '15-01-01 00:41:46',60.1);
INSERT INTO HST VALUES(1136, TIMESTAMP '15-01-01 00:42:31',60.6);
查询1 ：
WITH inputs AS (
SELECT RECNM,
TIMESTAMP '15-01-01 00:00:00' AS start_time,
TIMESTAMP '15-01-01 00:40:00' AS end_time
FROM POINTS
WHERE ACRONYM = '32-PRESS'
),
all_minutes AS (
SELECT RECNM,
start_time + (LEVEL-1)/24/60 AS time
FROM inputs
CONNECT BY
LEVEL - 1 <= EXTRACT( MINUTE FROM end_time - start_time )
),
all_times AS (
SELECT TIME,
VALUE,
1 AS HAS_VALUE
FROM HST h
INNER JOIN inputs i
ON ( h.RECNM = i.RECNM
AND h.TIME BETWEEN i.start_time
AND i.end_time )
UNION ALL
SELECT TIME,
NULL,
0
FROM all_minutes
ORDER BY 1, 2 NULLS FIRST
),
lag_lead_ignore_nulls AS (
SELECT TIME,
VALUE,
COUNT( VALUE ) OVER ( ORDER BY TIME ASC, VALUE ASC NULLS FIRST ) AS LAG_GRP,
COUNT( VALUE ) OVER ( ORDER BY TIME DESC, VALUE DESC NULLS LAST ) AS LEAD_GRP
FROM all_times
),
lag_lead_values AS (
SELECT TIME,
VALUE,
FIRST_VALUE( TIME ) OVER ( PARTITION BY LAG_GRP ORDER BY VALUE ASC NULLS LAST ) AS PREV_MEASURED_TIME,
FIRST_VALUE( VALUE ) OVER ( PARTITION BY LAG_GRP ORDER BY VALUE ASC NULLS LAST ) AS PREV_MEASURED_VALUE,
FIRST_VALUE( TIME ) OVER ( PARTITION BY LEAD_GRP ORDER BY VALUE ASC NULLS LAST ) AS NEXT_MEASURED_TIME,
FIRST_VALUE( VALUE ) OVER ( PARTITION BY LEAD_GRP ORDER BY VALUE ASC NULLS LAST ) AS NEXT_MEASURED_VALUE,
LEAD( TIME ) OVER ( ORDER BY TIME ASC ) AS NEXT_TIME
FROM lag_lead_ignore_nulls
),
interpolated_values AS (
SELECT CAST( TIME AS DATE ) TIME,
COALESCE(
VALUE,
PREV_MEASURED_VALUE
+ ( NEXT_MEASURED_VALUE - PREV_MEASURED_VALUE )
* (
60 * EXTRACT( MINUTE FROM TIME - PREV_MEASURED_TIME )
+ EXTRACT( SECOND FROM TIME - PREV_MEASURED_TIME )
)
/ (
60 * EXTRACT( MINUTE FROM NEXT_MEASURED_TIME - PREV_MEASURED_TIME )
+ EXTRACT( SECOND FROM NEXT_MEASURED_TIME - PREV_MEASURED_TIME )
)
) AS INTERPOLATED_VALUE,
60 * EXTRACT( MINUTE FROM NEXT_TIME - TIME )
+ EXTRACT( SECOND FROM NEXT_TIME - TIME ) AS DURATION
FROM lag_lead_values
)
SELECT TRUNC( TIME, 'MI' ) AS TIME,
SUM( INTERPOLATED_VALUE * DURATION ) / SUM( DURATION ) AS TWA,
SUM( DURATION ) AS TOTAL_DURATION
FROM interpolated_values
WHERE INTERPOLATED_VALUE IS NOT NULL
GROUP BY TRUNC( TIME, 'MI' )
ORDER BY TIME ASC
<强> Results ：
| TIME | TWA | TOTAL_DURATION |
|---------------------------|--------------------|----------------|
| January, 01 0015 00:00:00 | 65.38833333333333 | 60 |
| January, 01 0015 00:01:00 | 67.56302083333334 | 60 |
| January, 01 0015 00:02:00 | 66.30575757575758 | 60 |
| January, 01 0015 00:03:00 | 63.48385416666667 | 60 |
| January, 01 0015 00:04:00 | 62.02027777777778 | 60 |
| January, 01 0015 00:05:00 | 61.45441176470588 | 60 |
| January, 01 0015 00:06:00 | 60.79056603773585 | 60 |
| January, 01 0015 00:07:00 | 60.677358490566036 | 60 |
| January, 01 0015 00:08:00 | 60.56415094339623 | 60 |
| January, 01 0015 00:09:00 | 60.450943396226414 | 60 |
| January, 01 0015 00:10:00 | 60.62924528301887 | 60 |
| January, 01 0015 00:11:00 | 62.09051724137931 | 60 |
| January, 01 0015 00:12:00 | 62.18775510204082 | 60 |
| January, 01 0015 00:13:00 | 61.96530612244898 | 60 |
| January, 01 0015 00:14:00 | 61.28333333333333 | 60 |
| January, 01 0015 00:15:00 | 61.252027027027026 | 60 |
| January, 01 0015 00:16:00 | 60.27410714285714 | 60 |
| January, 01 0015 00:17:00 | 59.47416666666667 | 60 |
| January, 01 0015 00:18:00 | 59.34888888888889 | 60 |
| January, 01 0015 00:19:00 | 61.06 | 60 |
| January, 01 0015 00:20:00 | 62.86071428571429 | 60 |
| January, 01 0015 00:21:00 | 63.895 | 60 |
| January, 01 0015 00:22:00 | 64.61114754098361 | 60 |
| January, 01 0015 00:23:00 | 64.16431972789115 | 60 |
| January, 01 0015 00:24:00 | 63.52513020833333 | 60 |
| January, 01 0015 00:25:00 | 63.27789473684211 | 60 |
| January, 01 0015 00:26:00 | 63.002526315789474 | 60 |
| January, 01 0015 00:27:00 | 62.245045045045046 | 60 |
| January, 01 0015 00:28:00 | 62.23263157894737 | 60 |
| January, 01 0015 00:29:00 | 62.56314393939394 | 60 |
| January, 01 0015 00:30:00 | 62.81926605504587 | 60 |
| January, 01 0015 00:31:00 | 62.544587155963306 | 60 |
| January, 01 0015 00:32:00 | 62.29191176470588 | 60 |
| January, 01 0015 00:33:00 | 62.58641975308642 | 60 |
| January, 01 0015 00:34:00 | 62.73456790123457 | 60 |
| January, 01 0015 00:35:00 | 62.87131687242798 | 60 |
| January, 01 0015 00:36:00 | 62.02166666666667 | 60 |
| January, 01 0015 00:37:00 | 61.50328947368421 | 60 |
| January, 01 0015 00:38:00 | 61.70065789473684 | 60 |
| January, 01 0015 00:39:00 | 61.94731359649123 | 60 |
答案 1 :(得分：1)
此查询生成了所需的值：
with input as (
select value, htime, to_char(htime, 'yyyy-mm-dd hh24:mi') mnt,
extract(day from d)+extract(hour from d)/24+
extract(minute from d)/(24*60)+extract (second from d)/(24*60*60) tm
from (select value, htime, htime-timestamp '1899-12-30 00:00:00' d from test))
select distinct mnt, round(
sum(tm*value) over (partition by mnt)/sum(tm) over (partition by mnt), 6) wav
from input order by mnt
输出：
MNT WAV
---------------- ----------
2015-01-01 12:00 65.77838
2015-01-01 12:01 67.765575
2015-01-01 12:02 66.147733
2015-01-01 12:03 64.1026
根据documentation Excel日历以'1900-01-01'开头，
但是我必须稍微修改这个日期以达到“日期零”以获得与电子表格完全相同的时差数字值。
休息只是减去时间戳的问题，将此差异转换为数字，并在分析版本中使用函数sum()对每分钟的结果求和。
如果您在首先使用递归查询（connect by）创建每分钟的句点时需要数据空白，然后将此查询与我的填充数据一起加入，以填充加权平均函数lag(wav ignore nulls)的空白从前一分钟开始。
编辑：版本填补空白：
with input as (
select value, htime, to_char(htime, 'yyyy-mm-dd hh24:mi') mnt,
extract(day from d)+extract(hour from d)/24+
extract(minute from d)/(24*60)+extract (second from d)/(24*60*60) tm
from (select value, htime, htime-timestamp '1899-12-30 00:00:00' d from data)),
period as (select to_date(min(mnt), 'yyyy-mm-dd hh24:mi') m1,
to_date(max(mnt), 'yyyy-mm-dd hh24:mi') m2 from input),
minutes as (
select to_char(to_date(m1) + (level - 1)/(24*60), 'yyyy-mm-dd hh24:mi') mnt
from period connect by level+1<(m2-m1)*24*60),
calc as (
select distinct mnt,
round(sum(tm*value) over (partition by mnt)/sum(tm) over (partition by mnt), 6) wav
from minutes left join input using (mnt) order by mnt)
select mnt, wav, nvl(wav, lag(wav ignore nulls) over (order by mnt)) wavg from calc
子查询input 准备数据以便进一步处理，period从表中选择最小和最大分钟
（您可以在此处手动插入一些值，而不是从表中查询，例如“date'2015-01-01 13:52:00'”），
minutes在给定时间段内递归生成...分钟，calc计算加入输入和分钟的加权平均值，
最后一次选择填写空分钟的最后已知平均值 - 您可以在SQLFiddle中观察分钟6,7,12。