我写了一个查询来收集一些数据，以便在自动更新框中显示。 excel中的whisker图。我想使用汇总为每种类型的train_line（PF和MJ）创建汇总行，以包含在Excel图表中。
我可以使用Rollup吗？
我试图绕过Rollup，但我没有走得太远。我试过把它包裹在我的小组中的随机内容中，但它没有做我想要的。
以下是结果的前几列内容。
DUMP_YEAR DUMP_WEEK LINE MINE PRODUCT CODE
2009 30 MJ MJ C MJ-C
2009 30 PF BR F BR-F
2009 30 PF BR L BR-L
2009 30 PF HD F HD-F
2009 30 PF HD L HD-L
2009 30 PF MA F MA-F
2009 30 PF MA L MA-L
2009 30 PF NM F NM-F
2009 30 PF NM L NM-L
2009 30 PF PA F PA-F
2009 30 PF PA L PA-L
2009 30 PF TP F TP-F
2009 30 PF TP L TP-L
2009 30 PF WA F WA-F
2009 30 PF WA L WA-L
2009 30 PF YA F YA-F
这是我的SQL查询。
select t.dump_year,
t.dump_week,
(case when t.product = 'L' or t.product = 'F' then 'PF'
when t.product = 'C' then 'MJ'
else null
end) as train_line,
t.mine_id,
t.product,
t.mine_id||'-'||t.product as code,
count(distinct t.tpps_train_id) as trains,
count(1) as wagons,
count(CASE WHEN w.tonnes >= 1121 THEN w.tonnes END) as overload,
round(count(CASE WHEN w.tonnes >= 1121 THEN w.tonnes END)/count(1)*100,1) as pct_ol,
min(t.dump_date) as first_train,
max(t.dump_date) as last_train,
119 as u_limit,
100 as target,
round(avg(w.tonnes),2) as average,
round(stddev(w.tonnes),2) as deviation,
round(min(w.tonnes),2) as minimum,
round(max(w.tonnes),2) as maximum,
round(percentile_disc(0.99) within group (order by (w.tonnes) desc),2) as pct_1st,
round((percentile_disc(0.75) within group (order by (w.tonnes) desc)),2)-round((percentile_disc(0.99) within group (order by (w.tonnes) desc)),2) as whisker1,
round(percentile_disc(0.75) within group (order by (w.tonnes) desc),2) as pct_25th,
round((percentile_disc(0.50) within group (order by (w.tonnes) desc)),2)-round((percentile_disc(0.75) within group (order by (w.tonnes) desc)),2) as box50,
round((percentile_disc(0.25) within group (order by (w.tonnes) desc)),2)-round(percentile_disc(0.50) within group (order by (w.tonnes) desc),2) as box75,
round((percentile_disc(0.01) within group (order by (w.tonnes) desc)),2)-round((percentile_disc(0.25) within group (order by (w.tonnes) desc)),2) as whisker99,
round(percentile_disc(0.50) within group (order by (w.tonnes) desc),2) as pct_50th,
round(percentile_disc(0.25) within group (order by (w.tonnes) desc),2) as pct_75th,
round(percentile_disc(0.01) within group (order by (w.tonnes) desc),2) as pct_99th
from
(
select trn.mine_code as mine_id,
substr(trn.train_control_id,2,1) as port,
trn.train_tpps_id as tpps_train_id,
con.weight_total-con.empty_weight_total as tonnes
from widsys.train trn
INNER JOIN widsys.consist con
USING (train_record_id)
where trn.direction = 'N'
and (con.weight_total-con.empty_weight_total) > 10
and trn.num_cars > 10
) w,
(
select td.datetime_act_comp_dump as dump_date,
to_char(td.datetime_act_comp_dump-7/24, 'IYYY') as dump_year,
to_char(td.datetime_act_comp_dump-7/24, 'IW') as dump_week,
td.mine_code as mine_id,
td.train_id as tpps_train_id,
pt.product_type_code as product
from tpps.train_details td
inner join tpps.ore_products op
using (ore_product_key)
inner join tpps.product_types pt
using (product_type_key)
where to_char(td.datetime_act_comp_dump-7/24, 'IYYY') = 2009
and to_char(td.datetime_act_comp_dump-7/24, 'IW') = 30
order by td.datetime_act_comp_dump asc
) t
where w.mine_id = t.mine_id
and w.tpps_train_id = t.tpps_train_id
--having t.product is not null or t.mine_id is null
group by
t.dump_year,
t.dump_week,
(case when t.product = 'L' or t.product = 'F' then 'PF'when t.product = 'C' then 'MJ'else null end),
t.mine_id,
t.product
order by train_line asc
答案 0 :(得分：9)
您可以使用ROLLUP为查询生成分层小计，例如：
SQL> WITH DATA AS (
2 SELECT 'i' || MOD(ROWNUM, 1) dim1,
3 'j' || MOD(ROWNUM, 2) dim2,
4 'k' || MOD(ROWNUM, 3) dim3,
5 ROWNUM qty
6 FROM dual
7 CONNECT BY LEVEL <= 100
8 )
9 SELECT dim1, dim2, dim3, SUM(qty) tot
10 FROM DATA
11 GROUP BY dim1, rollup(dim2,dim3)
12 ORDER BY 1, 2, 3;
DIM1 DIM2 DIM3 TOT
----- ----- ----- ----------
i0 j0 k0 816
i0 j0 k1 884
i0 j0 k2 850
i0 j0 2550 (*)
i0 j1 k0 867
i0 j1 k1 833
i0 j1 k2 800
i0 j1 2500 (*)
i0 5050 (*)
ROLLUP子句生成标记为（*）
的行如果您只想获得一组小计而不是所有层级，您可以使用GROUPING SETS子句，i-e：
SQL> WITH DATA AS (
2 SELECT 'i' || MOD(ROWNUM, 1) dim1,
3 'j' || MOD(ROWNUM, 2) dim2,
4 'k' || MOD(ROWNUM, 3) dim3,
5 ROWNUM qty
6 FROM dual
7 CONNECT BY LEVEL <= 100
8 )
9 SELECT dim1, dim2, dim3, SUM(qty) tot
10 FROM DATA
11 GROUP BY GROUPING SETS (
12 (dim1, dim2, dim3), -- detail
13 (dim1) -- total
14 )
15 ORDER BY 1, 2, 3;
DIM1 DIM2 DIM3 TOT
----- ----- ----- ----------
i0 j0 k0 816
i0 j0 k1 884
i0 j0 k2 850
i0 j1 k0 867
i0 j1 k1 833
i0 j1 k2 800
i0 5050
答案 1 :(得分：0)