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                                                                      Oracle 9i 分析函數參考手冊    
          出處   
           
                   Oracle從8.1.6開始提供分析函數,分析函數用于計算基于組的某種聚合值,它和聚合函數的不同之處是對于每個組返回多行,而聚合函數對于每個組只返回一行。
          下面例子中使用的表來自Oracle自帶的HR用戶下的表,如果沒有安裝該用戶,可以在SYS用戶下運行$ORACLE_HOME/demo/schema/human_resources/hr_main.sql來創建。
                  少數幾個例子需要訪問SH用戶下的表,如果沒有安裝該用戶,可以在SYS用戶下運行$ORACLE_HOME/demo/schema/sales_history/sh_main.sql來創建。
                  如果未指明缺省是在HR用戶下運行例子。
                  開窗函數的的理解:
                  開窗函數指定了分析函數工作的數據窗口大小,這個數據窗口大小可能會隨著行的變化而變化,舉例如下:
          over(order by salary) 按照salary排序進行累計,order by是個默認的開窗函數
          over(partition by deptno)按照部門分區
          over(order by salary range between 50 preceding and 150 following)
          每行對應的數據窗口是之前行幅度值不超過50,之后行幅度值不超過150
          over(order by salary rows between 50 preceding and 150 following)
          每行對應的數據窗口是之前50行,之后150行
          over(order by salary rows between unbounded preceding and unbounded following)
          每行對應的數據窗口是從第一行到最后一行,等效:
          over(order by salary range between unbounded preceding and unbounded following)

          主要參考資料:《expert one-on-one》 Tom Kyte  《Oracle9i SQL Reference》第6章


          AVG
          功能描述:用于計算一個組和數據窗口內表達式的平均值。
          SAMPLE:下面的例子中列c_mavg計算員工表中每個員工的平均薪水報告,該平均值由當前員工和與之具有相同經理的前一個和后一個三者的平均數得來;

          SELECT manager_id, last_name, hire_date, salary,
             AVG(salary) OVER (PARTITION BY manager_id ORDER BY hire_date
             ROWS BETWEEN 1 PRECEDING AND 1 FOLLOWING) AS c_mavg
             FROM employees;

          MANAGER_ID LAST_NAME                 HIRE_DATE     SALARY     C_MAVG
          ---------- ------------------------- --------- ---------- ----------
                 100 Kochhar                   21-SEP-89      17000      17000
                 100 De Haan                   13-JAN-93      17000      15000
                 100 Raphaely                  07-DEC-94      11000 11966.6667
                 100 Kaufling                  01-MAY-95       7900 10633.3333
                 100 Hartstein                 17-FEB-96      13000 9633.33333
                 100 Weiss                     18-JUL-96       8000 11666.6667
                 100 Russell                   01-OCT-96      14000 11833.3333
          .
          .
          .


          CORR
          功能描述:返回一對表達式的相關系數,它是如下的縮寫:
                    COVAR_POP(expr1,expr2)/STDDEV_POP(expr1)*STDDEV_POP(expr2))
                    從統計上講,相關性是變量之間關聯的強度,變量之間的關聯意味著在某種程度
                    上一個變量的值可由其它的值進行預測。通過返回一個-1~1之間的一個數, 相關
                    系數給出了關聯的強度,0表示不相關。
          SAMPLE:下例返回1998年月銷售收入和月單位銷售的關系的累積系數(本例在SH用戶下運行)

          SELECT t.calendar_month_number,
                 CORR (SUM(s.amount_sold), SUM(s.quantity_sold))
                 OVER (ORDER BY t.calendar_month_number) as CUM_CORR
            FROM sales s, times t
          WHERE s.time_id = t.time_id AND calendar_year = 1998
          GROUP BY t.calendar_month_number
          ORDER BY t.calendar_month_number;

          CALENDAR_MONTH_NUMBER   CUM_CORR
          --------------------- ----------
                              1
                              2          1
                              3 .994309382
                              4 .852040875
                              5 .846652204
                              6 .871250628
                              7 .910029803
                              8 .917556399
                              9 .920154356
                             10  .86720251
                             11 .844864765
                             12 .903542662


          COVAR_POP 
          功能描述:返回一對表達式的總體協方差。
          SAMPLE:下例CUM_COVP返回定價和最小產品價格的累積總體協方差

          SELECT product_id, supplier_id,
                  COVAR_POP(list_price, min_price)
                    OVER (ORDER BY product_id, supplier_id) AS CUM_COVP,
                  COVAR_SAMP(list_price, min_price)
                    OVER (ORDER BY product_id, supplier_id) AS CUM_COVS
            FROM product_information p
          WHERE category_id = 29
          ORDER BY product_id, supplier_id;

          PRODUCT_ID SUPPLIER_ID   CUM_COVP   CUM_COVS
          ---------- ----------- ---------- ----------
                1774      103088          0
                1775      103087    1473.25     2946.5
                1794      103096 1702.77778 2554.16667
                1825      103093    1926.25 2568.33333
                2004      103086     1591.4    1989.25
                2005      103086     1512.5       1815
                2416      103088 1475.97959 1721.97619
          .
          .


          COVAR_SAMP 
          功能描述:返回一對表達式的樣本協方差
          SAMPLE:下例CUM_COVS返回定價和最小產品價格的累積樣本協方差

          SELECT product_id, supplier_id,
                  COVAR_POP(list_price, min_price)
                    OVER (ORDER BY product_id, supplier_id) AS CUM_COVP,
                  COVAR_SAMP(list_price, min_price)
                    OVER (ORDER BY product_id, supplier_id) AS CUM_COVS
            FROM product_information p
          WHERE category_id = 29
          ORDER BY product_id, supplier_id;

          PRODUCT_ID SUPPLIER_ID   CUM_COVP   CUM_COVS
          ---------- ----------- ---------- ----------
                1774      103088          0
                1775      103087    1473.25     2946.5
                1794      103096 1702.77778 2554.16667
                1825      103093    1926.25 2568.33333
                2004      103086     1591.4    1989.25
                2005      103086     1512.5       1815
                2416      103088 1475.97959 1721.97619
          .
          .


          COUNT
          功能描述:對一組內發生的事情進行累積計數,如果指定*或一些非空常數,count將對所有行計數,如果指定一個表達式,count返回表達式非空賦值的計數,當有相同值出現時,這些相等的值都會被納入被計算的值;可以使用DISTINCT來記錄去掉一組中完全相同的數據后出現的行數。
          SAMPLE:下面例子中計算每個員工在按薪水排序中當前行附近薪水在[n-50,n+150]之間的行數,n表示當前行的薪水
          例如,Philtanker的薪水2200,排在他之前的行中薪水大于等于2200-50的有1行,排在他之后的行中薪水小于等于2200+150的行沒有,所以count計數值cnt3為2(包括自己當前行);cnt2值相當于小于等于當前行的SALARY值的所有行數

          SELECT last_name, salary, COUNT(*) OVER () AS cnt1,
                 COUNT(*) OVER (ORDER BY salary) AS cnt2,
                 COUNT(*) OVER (ORDER BY salary RANGE BETWEEN 50 PRECEDING
                 AND 150 FOLLOWING) AS cnt3 FROM employees;

          LAST_NAME                     SALARY       CNT1       CNT2       CNT3
          ------------------------- ---------- ---------- ---------- ----------
          Olson                           2100        107          1          3
          Markle                          2200        107          3          2
          Philtanker                      2200        107          3          2
          Landry                          2400        107          5          8
          Gee                             2400        107          5          8
          Colmenares                      2500        107         11         10
          Patel                           2500        107         11         10
          .
          .


          CUME_DIST
          功能描述:計算一行在組中的相對位置,CUME_DIST總是返回大于0、小于或等于1的數,該數表示該行在N行中的位置。例如,在一個3行的組中,返回的累計分布值為1/3、2/3、3/3
          SAMPLE:下例中計算每個工種的員工按薪水排序依次累積出現的分布百分比

          SELECT job_id, last_name, salary, CUME_DIST()
                 OVER (PARTITION BY job_id ORDER BY salary) AS cume_dist
            FROM employees  WHERE job_id LIKE 'PU%';

          JOB_ID     LAST_NAME                     SALARY  CUME_DIST
          ---------- ------------------------- ---------- ----------
          PU_CLERK   Colmenares                      2500         .2
          PU_CLERK   Himuro                          2600         .4
          PU_CLERK   Tobias                          2800         .6
          PU_CLERK   Baida                           2900         .8
          PU_CLERK   Khoo                            3100          1
          PU_MAN     Raphaely                       11000          1


          DENSE_RANK
          功能描述:根據ORDER BY子句中表達式的值,從查詢返回的每一行,計算它們與其它行的相對位置。組內的數據按ORDER BY子句排序,然后給每一行賦一個號,從而形成一個序列,該序列從1開始,往后累加。每次ORDER BY表達式的值發生變化時,該序列也隨之增加。有同樣值的行得到同樣的數字序號(認為null時相等的)。密集的序列返回的時沒有間隔的數
          SAMPLE:下例中計算每個員工按部門分區再按薪水排序,依次出現的序列號(注意與RANK函數的區別)

          SELECT d.department_id , e.last_name, e.salary, DENSE_RANK()
                  OVER (PARTITION BY e.department_id ORDER BY e.salary) as drank
            FROM employees e, departments d
          WHERE e.department_id = d.department_id
             AND d.department_id IN ('60', '90');

          DEPARTMENT_ID LAST_NAME                     SALARY      DRANK
          ------------- ------------------------- ---------- ----------
                     60 Lorentz                         4200          1
                     60 Austin                          4800          2
                     60 Pataballa                       4800          2
                     60 Ernst                           6000          3
                     60 Hunold                          9000          4
                     90 Kochhar                        17000          1
                     90 De Haan                        17000          1
                     90 King                           24000          2


          FIRST
          功能描述:從DENSE_RANK返回的集合中取出排在最前面的一個值的行(可能多行,因為值可能相等),因此完整的語法需要在開始處加上一個集合函數以從中取出記錄
          SAMPLE:下面例子中DENSE_RANK按部門分區,再按傭金commission_pct排序,FIRST取出傭金最低的對應的所有行,然后前面的MAX函數從這個集合中取出薪水最低的值;LAST取出傭金最高的對應的所有行,然后前面的MIN函數從這個集合中取出薪水最高的值
          SELECT last_name, department_id, salary,
                   MIN(salary) KEEP (DENSE_RANK FIRST ORDER BY commission_pct)
                   OVER (PARTITION BY department_id) "Worst",
                   MAX(salary) KEEP (DENSE_RANK LAST ORDER BY commission_pct)
                   OVER (PARTITION BY department_id) "Best"
            FROM employees
          WHERE department_id in (20,80)
          ORDER BY department_id, salary;

          LAST_NAME                 DEPARTMENT_ID     SALARY      Worst       Best
          ------------------------- ------------- ---------- ---------- ----------
          Fay                                  20       6000       6000      13000
          Hartstein                            20      13000       6000      13000
          Kumar                                80       6100       6100      14000
          Banda                                80       6200       6100      14000
          Johnson                              80       6200       6100      14000
          Ande                                 80       6400       6100      14000
          Lee                                  80       6800       6100      14000
          Tuvault                              80       7000       6100      14000
          Sewall                               80       7000       6100      14000
          Marvins                              80       7200       6100      14000
          Bates                                80       7300       6100      14000
          .
          .
          .


          FIRST_VALUE 
          功能描述:返回組中數據窗口的第一個值。
          SAMPLE:下面例子計算按部門分區按薪水排序的數據窗口的第一個值對應的名字,如果薪水的第一個值有多個,則從多個對應的名字中取缺省排序的第一個名字

          SELECT department_id, last_name, salary, FIRST_VALUE(last_name)
            OVER (PARTITION BY department_id ORDER BY salary ASC ) AS lowest_sal
            FROM employees
          WHERE department_id in(20,30);

          DEPARTMENT_ID LAST_NAME                     SALARY LOWEST_SAL
          ------------- ------------------------- ---------- --------------
                     20 Fay                             6000 Fay
                     20 Hartstein                      13000 Fay
                     30 Colmenares                      2500 Colmenares
                     30 Himuro                          2600 Colmenares
                     30 Tobias                          2800 Colmenares
                     30 Baida                           2900 Colmenares
                     30 Khoo                            3100 Colmenares
                     30 Raphaely                       11000 Colmenares


          LAG
          功能描述:可以訪問結果集中的其它行而不用進行自連接。它允許去處理游標,就好像游標是一個數組一樣。在給定組中可參考當前行之前的行,這樣就可以從組中與當前行一起選擇以前的行。Offset是一個正整數,其默認值為1,若索引超出窗口的范圍,就返回默認值(默認返回的是組中第一行),其相反的函數是LEAD
          SAMPLE:下面的例子中列prev_sal返回按hire_date排序的前1行的salary值

          SELECT last_name, hire_date, salary,
                 LAG(salary, 1, 0) OVER (ORDER BY hire_date) AS prev_sal
            FROM employees
          WHERE job_id = 'PU_CLERK';

          LAST_NAME                 HIRE_DATE      SALARY   PREV_SAL
          ------------------------- ---------- ---------- ----------
          Khoo                      18-5月 -95       3100          0
          Tobias                    24-7月 -97       2800       3100
          Baida                     24-12月-97       2900       2800
          Himuro                    15-11月-98       2600       2900
          Colmenares                10-8月 -99       2500       2600


          LAST
          功能描述:從DENSE_RANK返回的集合中取出排在最后面的一個值的行(可能多行,因為值可能相等),因此完整的語法需要在開始處加上一個集合函數以從中取出記錄
          SAMPLE:下面例子中DENSE_RANK按部門分區,再按傭金commission_pct排序,FIRST取出傭金最低的對應的所有行,然后前面的MAX函數從這個集合中取出薪水最低的值;LAST取出傭金最高的對應的所有行,然后前面的MIN函數從這個集合中取出薪水最高的值
          SELECT last_name, department_id, salary,
                   MIN(salary) KEEP (DENSE_RANK FIRST ORDER BY commission_pct)
                   OVER (PARTITION BY department_id) "Worst",
                   MAX(salary) KEEP (DENSE_RANK LAST ORDER BY commission_pct)
                   OVER (PARTITION BY department_id) "Best"
            FROM employees
          WHERE department_id in (20,80)
          ORDER BY department_id, salary;

          LAST_NAME                 DEPARTMENT_ID     SALARY      Worst       Best
          ------------------------- ------------- ---------- ---------- ----------
          Fay                                  20       6000       6000      13000
          Hartstein                            20      13000       6000      13000
          Kumar                                80       6100       6100      14000
          Banda                                80       6200       6100      14000
          Johnson                              80       6200       6100      14000
          Ande                                 80       6400       6100      14000
          Lee                                  80       6800       6100      14000
          Tuvault                              80       7000       6100      14000
          Sewall                               80       7000       6100      14000
          Marvins                              80       7200       6100      14000
          Bates                                80       7300       6100      14000
          .
          .
          .


          LAST_VALUE
          功能描述:返回組中數據窗口的最后一個值。
          SAMPLE:下面例子計算按部門分區按薪水排序的數據窗口的最后一個值對應的名字,如果薪水的最后一個值有多個,則從多個對應的名字中取缺省排序的最后一個名字
          SELECT department_id, last_name, salary, LAST_VALUE(last_name)
              OVER(PARTITION BY department_id ORDER BY salary) AS highest_sal
            FROM employees
          WHERE department_id in(20,30);

          DEPARTMENT_ID LAST_NAME                     SALARY HIGHEST_SAL
          ------------- ------------------------- ---------- ------------
                     20 Fay                             6000 Fay
                     20 Hartstein                      13000 Hartstein
                     30 Colmenares                      2500 Colmenares
                     30 Himuro                          2600 Himuro
                     30 Tobias                          2800 Tobias
                     30 Baida                           2900 Baida
                     30 Khoo                            3100 Khoo
                     30 Raphaely                       11000 Raphaely


          LEAD
          功能描述:LEAD與LAG相反,LEAD可以訪問組中當前行之后的行。Offset是一個正整數,其默認值為1,若索引超出窗口的范圍,就返回默認值(默認返回的是組中第一行)
          SAMPLE:下面的例子中每行的"NextHired"返回按hire_date排序的下一行的hire_date值

          SELECT last_name, hire_date,
                  LEAD(hire_date, 1) OVER (ORDER BY hire_date) AS "NextHired"
            FROM employees WHERE department_id = 30;

          LAST_NAME                 HIRE_DATE NextHired
          ------------------------- --------- ---------
          Raphaely                  07-DEC-94 18-MAY-95
          Khoo                      18-MAY-95 24-JUL-97
          Tobias                    24-JUL-97 24-DEC-97
          Baida                     24-DEC-97 15-NOV-98
          Himuro                    15-NOV-98 10-AUG-99
          Colmenares                10-AUG-99


          MAX
          功能描述:在一個組中的數據窗口中查找表達式的最大值。
          SAMPLE:下面例子中dept_max返回當前行所在部門的最大薪水值

          SELECT department_id, last_name, salary,
             MAX(salary) OVER (PARTITION BY department_id) AS dept_max
             FROM employees WHERE department_id in (10,20,30);

          DEPARTMENT_ID LAST_NAME                     SALARY   DEPT_MAX
          ------------- ------------------------- ---------- ----------
                     10 Whalen                          4400       4400
                     20 Hartstein                      13000      13000
                     20 Fay                             6000      13000
                     30 Raphaely                       11000      11000
                     30 Khoo                            3100      11000
                     30 Baida                           2900      11000
                     30 Tobias                          2800      11000
                     30 Himuro                          2600      11000
                     30 Colmenares                      2500      11000


          MIN
          功能描述:在一個組中的數據窗口中查找表達式的最小值。
          SAMPLE:下面例子中dept_min返回當前行所在部門的最小薪水值

          SELECT department_id, last_name, salary,
             MIN(salary) OVER (PARTITION BY department_id) AS dept_min
             FROM employees WHERE department_id in (10,20,30);

          DEPARTMENT_ID LAST_NAME                     SALARY   DEPT_MIN
          ------------- ------------------------- ---------- ----------
                     10 Whalen                          4400       4400
                     20 Hartstein                      13000       6000
                     20 Fay                             6000       6000
                     30 Raphaely                       11000       2500
                     30 Khoo                            3100       2500
                     30 Baida                           2900       2500
                     30 Tobias                          2800       2500
                     30 Himuro                          2600       2500
                     30 Colmenares                      2500       2500


          NTILE
          功能描述:將一個組分為"表達式"的散列表示,例如,如果表達式=4,則給組中的每一行分配一個數(從1到4),如果組中有20行,則給前5行分配1,給下5行分配2等等。如果組的基數不能由表達式值平均分開,則對這些行進行分配時,組中就沒有任何percentile的行數比其它percentile的行數超過一行,最低的percentile是那些擁有額外行的percentile。例如,若表達式=4,行數=21,則percentile=1的有5行,percentile=2的有5行等等。
          SAMPLE:下例中把6行數據分為4份

          SELECT last_name, salary,
                 NTILE(4) OVER (ORDER BY salary DESC) AS quartile FROM employees
          WHERE department_id = 100;

          LAST_NAME                     SALARY   QUARTILE
          ------------------------- ---------- ----------
          Greenberg                      12000          1
          Faviet                          9000          1
          Chen                            8200          2
          Urman                           7800          2
          Sciarra                         7700          3
          Popp                            6900          4


          PERCENT_RANK
          功能描述:和CUME_DIST(累積分配)函數類似,對于一個組中給定的行來說,在計算那行的序號時,先減1,然后除以n-1(n為組中所有的行數)。該函數總是返回0~1(包括1)之間的數。
          SAMPLE:下例中如果Khoo的salary為2900,則pr值為0.6,因為RANK函數對于等值的返回序列值是一樣的

          SELECT department_id, last_name, salary,
                 PERCENT_RANK()
                 OVER (PARTITION BY department_id ORDER BY salary) AS pr
            FROM employees
          WHERE department_id < 50
            ORDER BY department_id,salary;

          DEPARTMENT_ID LAST_NAME                     SALARY         PR
          ------------- ------------------------- ---------- ----------
                     10 Whalen                          4400          0
                     20 Fay                             6000          0
                     20 Hartstein                      13000          1
                     30 Colmenares                      2500          0
                     30 Himuro                          2600        0.2
                     30 Tobias                          2800        0.4
                     30 Baida                           2900        0.6
                     30 Khoo                            3100        0.8
                     30 Raphaely                       11000          1
                     40 Mavris                          6500          0


          PERCENTILE_CONT
          功能描述:返回一個與輸入的分布百分比值相對應的數據值,分布百分比的計算方法見函數PERCENT_RANK,如果沒有正好對應的數據值,就通過下面算法來得到值:
                  RN = 1+ (P*(N-1)) 其中P是輸入的分布百分比值,N是組內的行數
                  CRN = CEIL(RN)  FRN = FLOOR(RN)
          if (CRN = FRN = RN) then
                          (value of expression from row at RN)
                  else
                          (CRN - RN) * (value of expression for row at FRN) +
                          (RN - FRN) * (value of expression for row at CRN)
                    注意:本函數與PERCENTILE_DISC的區別在找不到對應的分布值時返回的替代值的計算方法不同

          SAMPLE:在下例中,對于部門60的Percentile_Cont值計算如下:
                  P=0.7  N=5 RN =1+ (P*(N-1)=1+(0.7*(5-1))=3.8 CRN = CEIL(3.8)=4 
          FRN = FLOOR(3.8)=3
                    (4 - 3.8)* 4800 + (3.8 - 3) * 6000 = 5760

          SELECT last_name, salary, department_id,
                 PERCENTILE_CONT(0.7) WITHIN GROUP (ORDER BY salary)
                 OVER (PARTITION BY department_id) "Percentile_Cont",
                 PERCENT_RANK()
                 OVER (PARTITION BY department_id ORDER BY salary) "Percent_Rank"
            FROM employees WHERE department_id IN (30, 60);

          LAST_NAME                     SALARY DEPARTMENT_ID Percentile_Cont Percent_Rank
          ------------------------- ---------- ------------- --------------- ------------
          Colmenares                      2500            30            3000            0
          Himuro                          2600            30            3000          0.2
          Tobias                          2800            30            3000          0.4
          Baida                           2900            30            3000          0.6
          Khoo                            3100            30            3000          0.8
          Raphaely                       11000            30            3000            1
          Lorentz                         4200            60            5760            0
          Austin                          4800            60            5760         0.25
          Pataballa                       4800            60            5760         0.25
          Ernst                           6000            60            5760         0.75
          Hunold                          9000            60            5760            1


          PERCENTILE_DISC
          功能描述:返回一個與輸入的分布百分比值相對應的數據值,分布百分比的計算方法見函數CUME_DIST,如果沒有正好對應的數據值,就取大于該分布值的下一個值。
          注意:本函數與PERCENTILE_CONT的區別在找不到對應的分布值時返回的替代值的計算方法不同

          SAMPLE:下例中0.7的分布值在部門30中沒有對應的Cume_Dist值,所以就取下一個分布值0.83333333所對應的SALARY來替代

          SELECT last_name, salary, department_id,
                 PERCENTILE_DISC(0.7) WITHIN GROUP (ORDER BY salary )
                 OVER (PARTITION BY department_id) "Percentile_Disc",
                 CUME_DIST() OVER (PARTITION BY department_id ORDER BY salary)      "Cume_Dist"
            FROM employees
          WHERE department_id in (30, 60);

          LAST_NAME                     SALARY DEPARTMENT_ID Percentile_Disc  Cume_Dist
          ------------------------- ---------- ------------- --------------- ----------
          Colmenares                      2500            30            3100 .166666667
          Himuro                          2600            30            3100 .333333333
          Tobias                          2800            30            3100         .5
          Baida                           2900            30            3100 .666666667
          Khoo                            3100            30            3100 .833333333
          Raphaely                       11000            30            3100          1
          Lorentz                         4200            60            6000         .2
          Austin                          4800            60            6000         .6
          Pataballa                       4800            60            6000         .6
          Ernst                           6000            60            6000         .8
          Hunold                          9000            60            6000          1


          RANK
          功能描述:根據ORDER BY子句中表達式的值,從查詢返回的每一行,計算它們與其它行的相對位置。組內的數據按ORDER BY子句排序,然后給每一行賦一個號,從而形成一個序列,該序列從1開始,往后累加。每次ORDER BY表達式的值發生變化時,該序列也隨之增加。有同樣值的行得到同樣的數字序號(認為null時相等的)。然而,如果兩行的確得到同樣的排序,則序數將隨后跳躍。若兩行序數為1,則沒有序數2,序列將給組中的下一行分配值3,DENSE_RANK則沒有任何跳躍。
          SAMPLE:下例中計算每個員工按部門分區再按薪水排序,依次出現的序列號(注意與DENSE_RANK函數的區別)

          SELECT d.department_id , e.last_name, e.salary, RANK()
                  OVER (PARTITION BY e.department_id ORDER BY e.salary) as drank
            FROM employees e, departments d
          WHERE e.department_id = d.department_id
             AND d.department_id IN ('60', '90');

          DEPARTMENT_ID LAST_NAME                     SALARY      DRANK
          ------------- ------------------------- ---------- ----------
                     60 Lorentz                         4200          1
                     60 Austin                          4800          2
                     60 Pataballa                       4800          2
                     60 Ernst                           6000          4
                     60 Hunold                          9000          5
                     90 Kochhar                        17000          1
                     90 De Haan                        17000          1
                     90 King                           24000          3


          RATIO_TO_REPORT
          功能描述:該函數計算expression/(sum(expression))的值,它給出相對于總數的百分比,即當前行對sum(expression)的貢獻。
          SAMPLE:下例計算每個員工的工資占該類員工總工資的百分比

          SELECT last_name, salary, RATIO_TO_REPORT(salary) OVER () AS rr
            FROM employees
          WHERE job_id = 'PU_CLERK';

          LAST_NAME                     SALARY         RR
          ------------------------- ---------- ----------
          Khoo                            3100 .223021583
          Baida                           2900 .208633094
          Tobias                          2800 .201438849
          Himuro                          2600  .18705036
          Colmenares                      2500 .179856115


          REGR_ (Linear Regression) Functions
          功能描述:這些線性回歸函數適合最小二乘法回歸線,有9個不同的回歸函數可使用。
                    REGR_SLOPE:返回斜率,等于COVAR_POP(expr1, expr2) / VAR_POP(expr2)
                    REGR_INTERCEPT:返回回歸線的y截距,等于
                                    AVG(expr1) - REGR_SLOPE(expr1, expr2) * AVG(expr2)
                    REGR_COUNT:返回用于填充回歸線的非空數字對的數目
                    REGR_R2:返回回歸線的決定系數,計算式為:
                             If VAR_POP(expr2)  = 0 then return NULL
                             If VAR_POP(expr1)  = 0 and VAR_POP(expr2) != 0 then return 1
                             If VAR_POP(expr1)  > 0 and VAR_POP(expr2  != 0 then
                                return POWER(CORR(expr1,expr),2)
                    REGR_AVGX:計算回歸線的自變量(expr2)的平均值,去掉了空對(expr1, expr2)后,等于AVG(expr2)
                    REGR_AVGY:計算回歸線的應變量(expr1)的平均值,去掉了空對(expr1, expr2)后,等于AVG(expr1)
                    REGR_SXX: 返回值等于REGR_COUNT(expr1, expr2) * VAR_POP(expr2)
                    REGR_SYY: 返回值等于REGR_COUNT(expr1, expr2) * VAR_POP(expr1)
                    REGR_SXY:  返回值等于REGR_COUNT(expr1, expr2) * COVAR_POP(expr1, expr2)

          (下面的例子都是在SH用戶下完成的)
          SAMPLE 1:下例計算1998年最后三個星期中兩種產品(260和270)在周末的銷售量中已開發票數量和總數量的累積斜率和回歸線的截距

          SELECT t.fiscal_month_number "Month", t.day_number_in_month "Day",
                 REGR_SLOPE(s.amount_sold, s.quantity_sold)
                   OVER (ORDER BY t.fiscal_month_desc, t.day_number_in_month) AS CUM_SLOPE,
                 REGR_INTERCEPT(s.amount_sold, s.quantity_sold)
                   OVER (ORDER BY t.fiscal_month_desc, t.day_number_in_month) AS CUM_ICPT
            FROM sales s, times t
          WHERE s.time_id = t.time_id
             AND s.prod_id IN (270, 260)
             AND t.fiscal_year=1998
             AND t.fiscal_week_number IN (50, 51, 52)
             AND t.day_number_in_week IN (6,7)
             ORDER BY t.fiscal_month_desc, t.day_number_in_month;

               Month        Day  CUM_SLOPE   CUM_ICPT
          ---------- ---------- ---------- ----------
                  12         12        -68       1872
                  12         12        -68       1872
                  12         13 -20.244898 1254.36735
                  12         13 -20.244898 1254.36735
                  12         19 -18.826087       1287
                  12         20 62.4561404  125.28655
                  12         20 62.4561404  125.28655
                  12         20 62.4561404  125.28655
                  12         20 62.4561404  125.28655
                  12         26 67.2658228 58.9712313
                  12         26 67.2658228 58.9712313
                  12         27 37.5245541 284.958221
                  12         27 37.5245541 284.958221
                  12         27 37.5245541 284.958221

          SAMPLE 2:下例計算1998年4月每天的累積交易數量

          SELECT UNIQUE t.day_number_in_month,
                 REGR_COUNT(s.amount_sold, s.quantity_sold)
                  OVER (PARTITION BY t.fiscal_month_number ORDER BY t.day_number_in_month)
              "Regr_Count"
          FROM sales s, times t
          WHERE s.time_id = t.time_id
          AND t.fiscal_year = 1998 AND t.fiscal_month_number = 4;

          DAY_NUMBER_IN_MONTH Regr_Count
          ------------------- ----------
                            1        825
                            2       1650
                            3       2475
                            4       3300
          .
          .
          .
                           26      21450
                           30      22200

          SAMPLE 3:下例計算1998年每月銷售量中已開發票數量和總數量的累積回歸線決定系數

          SELECT t.fiscal_month_number,
                 REGR_R2(SUM(s.amount_sold), SUM(s.quantity_sold))
                    OVER (ORDER BY t.fiscal_month_number) "Regr_R2"
             FROM sales s, times t
             WHERE s.time_id = t.time_id
             AND t.fiscal_year = 1998
             GROUP BY t.fiscal_month_number
             ORDER BY t.fiscal_month_number;

          FISCAL_MONTH_NUMBER    Regr_R2
          ------------------- ----------
                            1
                            2          1
                            3 .927372984
                            4 .807019972
                            5 .932745567
                            6  .94682861
                            7 .965342011
                            8 .955768075
                            9 .959542618
                           10 .938618575
                           11 .880931415
                           12 .882769189

          SAMPLE 4:下例計算1998年12月最后兩周產品260的銷售量中已開發票數量和總數量的累積平均值

          SELECT t.day_number_in_month,
             REGR_AVGY(s.amount_sold, s.quantity_sold)
                OVER (ORDER BY t.fiscal_month_desc, t.day_number_in_month)
                "Regr_AvgY",
             REGR_AVGX(s.amount_sold, s.quantity_sold)
                OVER (ORDER BY t.fiscal_month_desc, t.day_number_in_month)
                "Regr_AvgX"
             FROM sales s, times t
             WHERE s.time_id = t.time_id
                AND s.prod_id = 260
                AND t.fiscal_month_desc = '1998-12'
                AND t.fiscal_week_number IN (51, 52)
             ORDER BY t.day_number_in_month;

          DAY_NUMBER_IN_MONTH  Regr_AvgY  Regr_AvgX
          ------------------- ---------- ----------
                           14        882       24.5
                           14        882       24.5
                           15        801      22.25
                           15        801      22.25
                           16      777.6       21.6
                           18 642.857143 17.8571429
                           18 642.857143 17.8571429
                           20      589.5     16.375
                           21        544 15.1111111
                           22 592.363636 16.4545455
                           22 592.363636 16.4545455
                           24 553.846154 15.3846154
                           24 553.846154 15.3846154
                           26        522       14.5
                           27      578.4 16.0666667

          SAMPLE 5:下例計算產品260和270在1998年2月周末銷售量中已開發票數量和總數量的累積REGR_SXY, REGR_SXX, and REGR_SYY統計值

          SELECT t.day_number_in_month,
             REGR_SXY(s.amount_sold, s.quantity_sold)
                OVER (ORDER BY t.fiscal_year, t.fiscal_month_desc) "Regr_sxy",
             REGR_SYY(s.amount_sold, s.quantity_sold)
                OVER (ORDER BY t.fiscal_year, t.fiscal_month_desc) "Regr_syy",
             REGR_SXX(s.amount_sold, s.quantity_sold)
                OVER (ORDER BY t.fiscal_year, t.fiscal_month_desc) "Regr_sxx"
          FROM sales s, times t
          WHERE s.time_id = t.time_id
             AND prod_id IN (270, 260)
             AND t.fiscal_month_desc = '1998-02'
             AND t.day_number_in_week IN (6,7)
          ORDER BY t.day_number_in_month;

          DAY_NUMBER_IN_MONTH   Regr_sxy   Regr_syy   Regr_sxx
          ------------------- ---------- ---------- ----------
                            1    18870.4  2116198.4      258.4
                            1    18870.4  2116198.4      258.4
                            1    18870.4  2116198.4      258.4
                            1    18870.4  2116198.4      258.4
                            7    18870.4  2116198.4      258.4
                            8    18870.4  2116198.4      258.4
                           14    18870.4  2116198.4      258.4
                           15    18870.4  2116198.4      258.4
                           21    18870.4  2116198.4      258.4
                           22    18870.4  2116198.4      258.4


          ROW_NUMBER
          功能描述:返回有序組中一行的偏移量,從而可用于按特定標準排序的行號。
          SAMPLE:下例返回每個員工再在每個部門中按員工號排序后的順序號

          SELECT department_id, last_name, employee_id, ROW_NUMBER()
                 OVER (PARTITION BY department_id ORDER BY employee_id) AS emp_id
            FROM employees
          WHERE department_id < 50;

          DEPARTMENT_ID LAST_NAME                 EMPLOYEE_ID     EMP_ID
          ------------- ------------------------- ----------- ----------
                     10 Whalen                            200          1
                     20 Hartstein                         201          1
                     20 Fay                               202          2
                     30 Raphaely                          114          1
                     30 Khoo                              115          2
                     30 Baida                             116          3
                     30 Tobias                            117          4
                     30 Himuro                            118          5
                     30 Colmenares                        119          6
                     40 Mavris                            203          1


          STDDEV
          功能描述:計算當前行關于組的標準偏離。(Standard Deviation)
          SAMPLE:下例返回部門30按雇傭日期排序的薪水值的累積標準偏離

          SELECT last_name, hire_date,salary,
                   STDDEV(salary) OVER (ORDER BY hire_date) "StdDev"
            FROM employees 
          WHERE department_id = 30;

          LAST_NAME                 HIRE_DATE      SALARY     StdDev
          ------------------------- ---------- ---------- ----------
          Raphaely                  07-12月-94      11000          0
          Khoo                      18-5月 -95       3100 5586.14357
          Tobias                    24-7月 -97       2800  4650.0896
          Baida                     24-12月-97       2900 4035.26125
          Himuro                    15-11月-98       2600  3649.2465
          Colmenares                10-8月 -99       2500 3362.58829


          STDDEV_POP
          功能描述:該函數計算總體標準偏離,并返回總體變量的平方根,其返回值與VAR_POP函數的平方根相同。(Standard Deviation-Population)
          SAMPLE:下例返回部門20、30、60的薪水值的總體標準偏差

          SELECT department_id, last_name, salary,
                 STDDEV_POP(salary) OVER (PARTITION BY department_id) AS pop_std
            FROM employees
          WHERE department_id in (20,30,60);

          DEPARTMENT_ID LAST_NAME                     SALARY    POP_STD
          ------------- ------------------------- ---------- ----------
                     20 Hartstein                      13000       3500
                     20 Fay                             6000       3500
                     30 Raphaely                       11000  3069.6091
                     30 Khoo                            3100  3069.6091
                     30 Baida                           2900  3069.6091
                     30 Colmenares                      2500  3069.6091
                     30 Himuro                          2600  3069.6091
                     30 Tobias                          2800  3069.6091
                     60 Hunold                          9000 1722.32401
                     60 Ernst                           6000 1722.32401
                     60 Austin                          4800 1722.32401
                     60 Pataballa                       4800 1722.32401
                     60 Lorentz                         4200 1722.32401


          STDDEV_SAMP
          功能描述: 該函數計算累積樣本標準偏離,并返回總體變量的平方根,其返回值與VAR_POP函數的平方根相同。(Standard Deviation-Sample)
          SAMPLE:下例返回部門20、30、60的薪水值的樣本標準偏差

          SELECT department_id, last_name, hire_date, salary,
                  STDDEV_SAMP(salary) OVER
                  (PARTITION BY department_id ORDER BY hire_date
                   ROWS BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW) AS cum_sdev
            FROM employees
          WHERE department_id in (20,30,60);

          DEPARTMENT_ID LAST_NAME                 HIRE_DATE      SALARY   CUM_SDEV
          ------------- ------------------------- ---------- ---------- ----------
                     20 Hartstein                 17-2月 -96      13000
                     20 Fay                       17-8月 -97       6000 4949.74747
                     30 Raphaely                  07-12月-94      11000
                     30 Khoo                      18-5月 -95       3100 5586.14357
                     30 Tobias                    24-7月 -97       2800  4650.0896
                     30 Baida                     24-12月-97       2900 4035.26125
                     30 Himuro                    15-11月-98       2600  3649.2465
                     30 Colmenares                10-8月 -99       2500 3362.58829
                     60 Hunold                    03-1月 -90       9000
                     60 Ernst                     21-5月 -91       6000 2121.32034
                     60 Austin                    25-6月 -97       4800 2163.33077
                     60 Pataballa                 05-2月 -98       4800 1982.42276
                     60 Lorentz                   07-2月 -99       4200 1925.61678


          SUM
          功能描述:該函數計算組中表達式的累積和。
          SAMPLE:下例計算同一經理下員工的薪水累積值

          SELECT manager_id, last_name, salary,
                  SUM (salary) OVER (PARTITION BY manager_id ORDER BY salary
             RANGE UNBOUNDED PRECEDING) l_csum
              FROM employees
             WHERE manager_id in (101,103,108);

          MANAGER_ID LAST_NAME                     SALARY     L_CSUM
          ---------- ------------------------- ---------- ----------
                 101 Whalen                          4400       4400
                 101 Mavris                          6500      10900
                 101 Baer                           10000      20900
                 101 Greenberg                      12000      44900
                 101 Higgins                        12000      44900
                 103 Lorentz                         4200       4200
                 103 Austin                          4800      13800
                 103 Pataballa                       4800      13800
                 103 Ernst                           6000      19800
                 108 Popp                            6900       6900
                 108 Sciarra                         7700      14600
                 108 Urman                           7800      22400
                 108 Chen                            8200      30600
                 108 Faviet                          9000      39600
                
                
          VAR_POP
          功能描述:(Variance Population)該函數返回非空集合的總體變量(忽略null),VAR_POP進行如下計算:
                    (SUM(expr2) - SUM(expr)2 / COUNT(expr)) / COUNT(expr)
          SAMPLE:下例計算1998年每月銷售的累積總體和樣本變量(本例在SH用戶下運行)

          SELECT t.calendar_month_desc,
                 VAR_POP(SUM(s.amount_sold))
                   OVER (ORDER BY t.calendar_month_desc) "Var_Pop",
                 VAR_SAMP(SUM(s.amount_sold))
                   OVER (ORDER BY t.calendar_month_desc) "Var_Samp"
            FROM sales s, times t
          WHERE s.time_id = t.time_id AND t.calendar_year = 1998
          GROUP BY t.calendar_month_desc;

          CALENDAR    Var_Pop   Var_Samp
          -------- ---------- ----------
          1998-01           0
          1998-02  6.1321E+11 1.2264E+12
          1998-03  4.7058E+11 7.0587E+11
          1998-04  4.6929E+11 6.2572E+11
          1998-05  1.5524E+12 1.9405E+12
          1998-06  2.3711E+12 2.8453E+12
          1998-07  3.7464E+12 4.3708E+12
          1998-08  3.7852E+12 4.3260E+12
          1998-09  3.5753E+12 4.0222E+12
          1998-10  3.4343E+12 3.8159E+12
          1998-11  3.4245E+12 3.7669E+12
          1998-12  4.8937E+12 5.3386E+12


          VAR_SAMP
          功能描述:(Variance Sample)該函數返回非空集合的樣本變量(忽略null),VAR_POP進行如下計算:
                    (SUM(expr*expr)-SUM(expr)*SUM(expr)/COUNT(expr))/(COUNT(expr)-1)
          SAMPLE:下例計算1998年每月銷售的累積總體和樣本變量

          SELECT t.calendar_month_desc,
                  VAR_POP(SUM(s.amount_sold))
                    OVER (ORDER BY t.calendar_month_desc) "Var_Pop",
                  VAR_SAMP(SUM(s.amount_sold))
                    OVER (ORDER BY t.calendar_month_desc) "Var_Samp"
            FROM sales s, times t
          WHERE s.time_id = t.time_id AND t.calendar_year = 1998
          GROUP BY t.calendar_month_desc;

          CALENDAR    Var_Pop   Var_Samp
          -------- ---------- ----------
          1998-01           0
          1998-02  6.1321E+11 1.2264E+12
          1998-03  4.7058E+11 7.0587E+11
          1998-04  4.6929E+11 6.2572E+11
          1998-05  1.5524E+12 1.9405E+12
          1998-06  2.3711E+12 2.8453E+12
          1998-07  3.7464E+12 4.3708E+12
          1998-08  3.7852E+12 4.3260E+12
          1998-09  3.5753E+12 4.0222E+12
          1998-10  3.4343E+12 3.8159E+12
          1998-11  3.4245E+12 3.7669E+12
          1998-12  4.8937E+12 5.3386E+12


          VARIANCE
          功能描述:該函數返回表達式的變量,Oracle計算該變量如下:
                    如果表達式中行數為1,則返回0
                    如果表達式中行數大于1,則返回VAR_SAMP
          SAMPLE:下例返回部門30按雇傭日期排序的薪水值的累積變化

          SELECT last_name, salary, VARIANCE(salary)
                  OVER (ORDER BY hire_date) "Variance"
            FROM employees
          WHERE department_id = 30;

          LAST_NAME                     SALARY   Variance
          ------------------------- ---------- ----------
          Raphaely                       11000          0
          Khoo                            3100   31205000
          Tobias                          2800 21623333.3
          Baida                           2900 16283333.3
          Himuro                          2600   13317000
          Colmenares                      2500   11307000

          posted on 2007-12-03 14:29 有貓相伴的日子 閱讀(513) 評論(0)  編輯  收藏 所屬分類: pl/sql
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