在 Oracle 11g 中，您如何对两个日期之间每小时的加权平均数据进行计时?
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，以及在我的 oracle 11G 实例上玩了四个月，我终于有了你在这里看到的东西.此查询主要为 SCADA 系统设计，并将执行以下操作...
I have replaced my original question with this final answer. With the help from Mr. MTO and Mr. Ponder Stibbons and four months of playing around with my oracle 11G instance, I finally have what you see here. This query is Designed for SCADA systems primarily and will do the following...
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，在该间隔内作为 Vmin 和 Vmax 的最小值和最大值.它还将以 Hmin 和 Hmax 形式返回最小值时间和最大值时间.(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.此查询不会在三月或八月的夏令时失败.(这就是我使用 TO_TIMESTAMP_TZ 的原因)
This query will perform a Time Weighted Average hourly between two date times as TWA, Minimum and Maximum Values during that Interval as Vmin and Vmax. It will also return Time of Minimum and Time of Maximum as Hmin and Hmax. (These are the date times of the minimum value occurrence and maximum value occurrence ).Starting and Ending Interval values as VSTART and VEND. This query will not fail on daylight savings in March or August. (This is why I am using TO_TIMESTAMP_TZ)
注意:此查询设置为 1 小时间隔，通过替换和添加几个项目，任何所需的间隔都是可能的.所以享受吧！！！
Note: this query is setup for 1 hour intervals and any desired interval is possible by replacing and adding just a few items. So Enjoy!!!
这个查询在我的 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.所以它有效！！我在 sqlfiddle 中运行它时遇到问题，但很快我会解决这个问题并为您进行运行测试.
This Query works in my Oracle 11g instance and after writing this post i copy-ed the exact text below and pasted into my SQL Developer. So it works!! I am having trouble running this in sqlfiddle but soon i will figure this out and have a running test for you.
SQL 小提琴
-- 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
您可以将其包含在时间加权的 1 小时滚动平均值的最终选择语句中！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.如果你需要一个 24 的滚动平均改变 ROWS 1 PROCECDING 到 ROWS 24 PROCEDING
You can Include this in the final select statement for a 1 hour Rolling Average that is Time Weighted! I find this very useful in the waste water industry as state regulations/reporting require 24 hour rolling averages and 72 minute rolling averages. If you need a 24 rolling average change 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，所以也添加这个.
Standard deviation is fun, so add this as well.
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，您可以将其与其他联合的所有值一起放置.
If you need the value prior to your start time and after your stop time you can place this with the other union all's.
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
推荐答案
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.
Using your sample data - it didn't have a full hour's data so I've done a weighted average per minute.
您尚未指定要在边界处执行的操作，因此我采用了前一个值和后一个值的加权平均值.
You haven't specified what you want to do at the boundaries so I've taken the weighted average of the immediately preceding and succeeding values.
SQL 小提琴
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
结果:
| 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
SQL 小提琴
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
结果:
| 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 |
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