在 Oracle 11g 中，你如何计算两个日期之间每小时的平均数据时间？
In Oracle 11g how do you time weight average data hourly between two dates?
我已经用这个最终答案替换了我原来的问题。在 MTO 先生和 Ponder Stibbons 先生的帮助下，以及使用我的 Oracle 11G 实例四个月的时间，我终于拥有了您在这里看到的内容。此查询主要是为 SCADA 系统设计的，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作为 TWA，该时间间隔内的最小值和最大值作为 Vmin 和 Vmax。它还将 return 最小时间和最大时间作为 Hmin 和 Hmax。 （这些是最小值出现和最大值出现的日期时间）。开始和结束间隔值作为 VSTART 和 VEND。此查询不会因三月或八月的夏令时而失败。 （这就是我使用 TO_TIMESTAMP_TZ 的原因）
注意：此查询设置为 1 小时的间隔，只需替换和添加一些项目即可实现任何所需的间隔。尽情享受吧！！！
此查询适用于我的 Oracle 11g 实例，在编写此 post 后，我复制了下面的确切文本并粘贴到我的 SQL 开发人员中。所以它有效！
我在 sqlfiddle 中遇到了 运行 这个问题，但很快我会解决这个问题并为你做一个 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：您可以将其包含在最终的 select 语句中，以获得时间加权的 1 小时滚动平均值！我发现这在废水行业非常有用，因为州 regulations/reporting 需要 24 小时滚动平均值和 72 分钟滚动平均值。如果您需要 24 滚动平均值，请将 ROWS 1 PROCECDING 更改为 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，所以也加上这个。
ROUND( STDDEV ( VALUE ) , 2 ) as VDEV,
如果您需要开始时间之前和停止时间之后的值，您可以将其与其他并集一起放置。
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
使用您的示例数据 - 它没有完整小时的数据，所以我做了每分钟的加权平均值。
您没有指定要在边界处执行的操作，因此我取了紧邻的前后值的加权平均值。
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
| 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 |
编辑
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
| 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 |
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”开始，
但我不得不稍微修改此日期以实现 "date zero" 以获得与电子表格中完全相同的时差数值。
剩下的只是减去时间戳的问题，将这个差异转换为数字，并在解析版本中使用函数 sum() 对每分钟的结果求和。
如果你的数据有差距，你首先需要用递归查询（connect by）为每分钟创建一个时间段，然后将这个查询与我的数据一起加入，用函数 lag(wav ignore nulls) 收集来填补差距前一分钟的加权平均值。
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 数据以供进一步处理，period selects min and max minute from table
（您可以在这里手动插入一些值，而不是从 table 查询，例如 "date '2015-01-01 13:52:00'"），
minutes 为给定时间递归生成...分钟数，calc 计算加入输入和分钟数的加权平均值，
last select 填充 empty 分钟的最后已知平均值 - 您可以在 SQLFiddle 中观察第 6、7、12 分钟。
我已经用这个最终答案替换了我原来的问题。在 MTO 先生和 Ponder Stibbons 先生的帮助下，以及使用我的 Oracle 11G 实例四个月的时间，我终于拥有了您在这里看到的内容。此查询主要是为 SCADA 系统设计的，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作为 TWA，该时间间隔内的最小值和最大值作为 Vmin 和 Vmax。它还将 return 最小时间和最大时间作为 Hmin 和 Hmax。 （这些是最小值出现和最大值出现的日期时间）。开始和结束间隔值作为 VSTART 和 VEND。此查询不会因三月或八月的夏令时而失败。 （这就是我使用 TO_TIMESTAMP_TZ 的原因）
注意：此查询设置为 1 小时的间隔，只需替换和添加一些项目即可实现任何所需的间隔。尽情享受吧！！！
此查询适用于我的 Oracle 11g 实例，在编写此 post 后，我复制了下面的确切文本并粘贴到我的 SQL 开发人员中。所以它有效！ 我在 sqlfiddle 中遇到了 运行 这个问题，但很快我会解决这个问题并为你做一个 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：您可以将其包含在最终的 select 语句中，以获得时间加权的 1 小时滚动平均值！我发现这在废水行业非常有用，因为州 regulations/reporting 需要 24 小时滚动平均值和 72 分钟滚动平均值。如果您需要 24 滚动平均值，请将 ROWS 1 PROCECDING 更改为 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，所以也加上这个。
ROUND( STDDEV ( VALUE ) , 2 ) as VDEV,
如果您需要开始时间之前和停止时间之后的值，您可以将其与其他并集一起放置。
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
使用您的示例数据 - 它没有完整小时的数据，所以我做了每分钟的加权平均值。
您没有指定要在边界处执行的操作，因此我取了紧邻的前后值的加权平均值。
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
| 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 |
编辑
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
| 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 |
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”开始，
但我不得不稍微修改此日期以实现 "date zero" 以获得与电子表格中完全相同的时差数值。
剩下的只是减去时间戳的问题，将这个差异转换为数字，并在解析版本中使用函数 sum() 对每分钟的结果求和。
如果你的数据有差距，你首先需要用递归查询（connect by）为每分钟创建一个时间段，然后将这个查询与我的数据一起加入，用函数 lag(wav ignore nulls) 收集来填补差距前一分钟的加权平均值。
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 数据以供进一步处理，period selects min and max minute from table
（您可以在这里手动插入一些值，而不是从 table 查询，例如 "date '2015-01-01 13:52:00'"），
minutes 为给定时间递归生成...分钟数，calc 计算加入输入和分钟数的加权平均值，
last select 填充 empty 分钟的最后已知平均值 - 您可以在 SQLFiddle 中观察第 6、7、12 分钟。