Frage

Ich habe eine Abfrage geschrieben, einige Daten zu sammeln, in einem Auto-Update-Box & Whisker Diagramm in Excel angezeigt werden soll. Ich mag Rollup verwenden, um Zusammenfassungszeilen für jede Art von train_line (PF und MJ) enthalten in dem Excel-Diagramm zu erstellen.

Kann ich das mit Rollup?

Ich habe versucht, meinen Kopf um Rollup zu bekommen, aber ich bin nicht weit zu bekommen. Ich habe gerade versucht es um zufällige Dinge in meiner Gruppe-durch Umwickeln, aber es hat nicht getan, was ich haben wollte.

Hier ist, was die ersten paar Spalten der Ergebnisse aussehen.

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

Und hier ist meine SQL-Abfrage.

 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
War es hilfreich?

Lösung

Sie würden verwenden ROLLUP- hierarchische Teilergebnisse für Ihre Anfrage zu erzeugen, das heißt:

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 (*)

Die ROLLUP-Klausel erzeugt, um die Linien markiert (*)

Wenn Sie nur einen Satz von Zwischensummen erhalten möchten und nicht alle Hierarchieebenen, können Sie die GROUPING SETS Klausel, dh:

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

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