夫妇事情似乎“腥”给我..
1)你排序上RAW_ID ..这是一个字符串...它包含数字,... 您的排序顺序将整理raw_1,然后raw_10 ..然后raw_11(etc)...然后raw_19,然后raw_2 ..然后raw_20 ..然后raw_21 ... etc ...然后raw_3 ..等等 您应该考虑使用一个PROPER序列...纯数值..所以你可以适当地分类。
2)你的第二个CASE子句中..你..有本质:当LAG(东西)=数量 - 数量... 这基本上是:当LAG(东西)= 0 ... 是这个意?如果你是第一次出现后,它可能是更明确地说: 当LAG(东西)IS NULL你显示为您的结果
3)..绝对不符合他们的查询/数据您提供的。 ..我重新键入所有的数据后(感谢图像btw ..下一次,请将实际的文本,以便我们可以复制/粘贴..使我们的工作更容易帮助你:P)我不得到和你一样的结果... 所以请重新发布一个完整的测试案例...与适当的数据,查询..和这样的文本格式...所以我们可以验证,我们不会在示例中引入错别字;)
这就是我从你发布的内容中得到的:
RAW_ID UPDATE_DA INITIAL_QTY ACTUAL_QTY USED_QTY SINGLE_USE_QTY
------ --------- ----------- ---------- ---------- --------------
raw_1 06-JUN-17 20000 48.52559 19951.47 0
raw_10 06-JUN-17 20000 20.76559 19979.23 -27.76
raw_11 06-JUN-17 20000 17.29559 19982.7 -3.47
raw_12 06-JUN-17 20000 13.82559 19986.17 -3.47
raw_13 06-JUN-17 20000 10.35559 19989.64 -3.47
raw_14 06-JUN-17 20000 6.885593 19996.11 -6.47
raw_15 06-JUN-17 20000 3.415594 19996.58 -.47
raw_2 06-JUN-17 20000 45.0556 19954.94 41.64
raw_3 06-JUN-17 20000 41.58559 19958.41 -3.47
raw_4 06-JUN-17 20000 38.11559 19961.88 -3.47
raw_5 06-JUN-17 20000 38.11559 19961.88 0
raw_6 06-JUN-17 20000 34.6456 19965.35 -3.47
raw_7 06-JUN-17 20000 31.17559 19968.82 -3.47
raw_8 06-JUN-17 20000 27.70559 19972.29 -3.47
raw_9 06-JUN-17 20000 24.23559 19975.76 -3.47
15 rows selected.
这里是我重新工作的查询..但不知道你真正想要的..
with data_view as (
select 'raw_1' raw_id, 1 raw_id2, to_date('6/6/2017 16:01','dd/mm/yyyy hh24:mi') update_date, 20000 initial_qty, 48.52559 actual_qty, 19951.47 used_qty from dual union all
select 'raw_2' raw_id, 2 raw_id2, to_date('6/6/2017 16:01','dd/mm/yyyy hh24:mi') update_date, 20000 initial_qty, 45.0556 actual_qty, 19954.94 used_qty from dual union all
select 'raw_3' raw_id, 3 raw_id2, to_date('6/6/2017 16:01','dd/mm/yyyy hh24:mi') update_date, 20000 initial_qty, 41.58559 actual_qty, 19958.41 used_qty from dual union all
select 'raw_4' raw_id, 4 raw_id2, to_date('6/6/2017 16:01','dd/mm/yyyy hh24:mi') update_date, 20000 initial_qty, 38.11559 actual_qty, 19961.88 used_qty from dual union all
select 'raw_5' raw_id, 5 raw_id2, to_date('6/6/2017 16:01','dd/mm/yyyy hh24:mi') update_date, 20000 initial_qty, 38.11559 actual_qty, 19961.88 used_qty from dual union all
select 'raw_6' raw_id, 6 raw_id2, to_date('6/6/2017 16:01','dd/mm/yyyy hh24:mi') update_date, 20000 initial_qty, 34.6456 actual_qty, 19965.35 used_qty from dual union all
select 'raw_7' raw_id, 7 raw_id2, to_date('6/6/2017 16:01','dd/mm/yyyy hh24:mi') update_date, 20000 initial_qty, 31.17559 actual_qty, 19968.82 used_qty from dual union all
select 'raw_8' raw_id, 8 raw_id2, to_date('6/6/2017 16:01','dd/mm/yyyy hh24:mi') update_date, 20000 initial_qty, 27.70559 actual_qty, 19972.29 used_qty from dual union all
select 'raw_9' raw_id, 9 raw_id2, to_date('6/6/2017 16:01','dd/mm/yyyy hh24:mi') update_date, 20000 initial_qty, 24.23559 actual_qty, 19975.76 used_qty from dual union all
select 'raw_10' raw_id, 10 raw_id2, to_date('6/6/2017 16:01','dd/mm/yyyy hh24:mi') update_date, 20000 initial_qty, 20.76559 actual_qty, 19979.23 used_qty from dual union all
select 'raw_11' raw_id, 11 raw_id2, to_date('6/6/2017 16:01','dd/mm/yyyy hh24:mi') update_date, 20000 initial_qty, 17.29559 actual_qty, 19982.7 used_qty from dual union all
select 'raw_12' raw_id, 12 raw_id2, to_date('6/6/2017 16:01','dd/mm/yyyy hh24:mi') update_date, 20000 initial_qty, 13.82559 actual_qty, 19986.17 used_qty from dual union all
select 'raw_13' raw_id, 13 raw_id2, to_date('6/6/2017 16:01','dd/mm/yyyy hh24:mi') update_date, 20000 initial_qty, 10.35559 actual_qty, 19989.64 used_qty from dual union all
select 'raw_14' raw_id, 14 raw_id2, to_date('6/6/2017 16:01','dd/mm/yyyy hh24:mi') update_date, 20000 initial_qty, 6.885593 actual_qty, 19996.11 used_qty from dual union all
select 'raw_15' raw_id, 15 raw_id2, to_date('6/6/2017 16:01','dd/mm/yyyy hh24:mi') update_date, 20000 initial_qty, 3.415594 actual_qty, 19996.58 used_qty from dual
)
SELECT
DATA_VIEW.RAW_ID as RAW_ID,
DATA_VIEW.RAW_ID2 as RAW_ID2,
DATA_VIEW.UPDATE_DATE as UPDATE_DATE,
DATA_VIEW.INITIAL_QTY as INITIAL_QTY,
DATA_VIEW.ACTUAL_QTY as ACTUAL_QTY,
DATA_VIEW.USED_QTY as USED_QTY,
LAG(DATA_VIEW.USED_QTY, 1, 0) OVER
(ORDER BY DATA_VIEW.RAW_ID2 ASC,DATA_VIEW.ACTUAL_QTY,DATA_VIEW.UPDATE_DATE)
as lag_used_qty,
CASE
WHEN DATA_VIEW.ACTUAL_QTY = DATA_VIEW.INITIAL_QTY
THEN 0
WHEN LAG(DATA_VIEW.USED_QTY, 1, 0) OVER
(ORDER BY DATA_VIEW.RAW_ID2 ASC,DATA_VIEW.ACTUAL_QTY,DATA_VIEW.UPDATE_DATE) IS NULL
THEN 0
ELSE
LAG(DATA_VIEW.USED_QTY, 1, 0) OVER
(ORDER BY DATA_VIEW.RAW_ID2 ASC,DATA_VIEW.ACTUAL_QTY,DATA_VIEW.UPDATE_DATE)
- DATA_VIEW.USED_QTY
END as SINGLE_USE_QTY
FROM
DATA_VIEW
order by RAW_ID2 asc, ACTUAL_QTY, UPDATE_DATE ;
和这里的结果:
RAW_ID RAW_ID2 UPDATE_DA INITIAL_QTY ACTUAL_QTY USED_QTY SINGLE_USE_QTY
------ ---------- --------- ----------- ---------- ---------- --------------
raw_1 1 06-JUN-17 20000 48.52559 19951.47 0
raw_2 2 06-JUN-17 20000 45.0556 19954.94 -3.47
raw_3 3 06-JUN-17 20000 41.58559 19958.41 -3.47
raw_4 4 06-JUN-17 20000 38.11559 19961.88 -3.47
raw_5 5 06-JUN-17 20000 38.11559 19961.88 0
raw_6 6 06-JUN-17 20000 34.6456 19965.35 -3.47
raw_7 7 06-JUN-17 20000 31.17559 19968.82 -3.47
raw_8 8 06-JUN-17 20000 27.70559 19972.29 -3.47
raw_9 9 06-JUN-17 20000 24.23559 19975.76 -3.47
raw_10 10 06-JUN-17 20000 20.76559 19979.23 -3.47
raw_11 11 06-JUN-17 20000 17.29559 19982.7 -3.47
raw_12 12 06-JUN-17 20000 13.82559 19986.17 -3.47
raw_13 13 06-JUN-17 20000 10.35559 19989.64 -3.47
raw_14 14 06-JUN-17 20000 6.885593 19996.11 -6.47
raw_15 15 06-JUN-17 20000 3.415594 19996.58 -.47
15 rows selected.
你的主要'ORDER BY'不匹配'LAG'中使用'ORDER BY',所以显示的最后一条记录可能不是LAG中使用的最后一条记录? –
ORDER BY似乎是问题,因为我有不同的顺序。谢谢 –