以下分析函式雖然是在 oracle 9i 的基礎上整理的,但是仍然適用于 10g,11g以及12c等后續版本
Oracle從8.1.6開始提供分析函式,分析函式用于計算基于組的某種聚合值,它和聚合函式的不同之處是對于每個組回傳多行,而聚合函式對于每個組只回傳一行。
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。
如果未指明預設是在HR用戶下運行例子。
開窗函式的理解:
開窗函式指定了分析函式作業的資料視窗大小,這個資料視窗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是個默認的開窗函式
over(partition by deptno)按照部門磁區
over(order by salary range between 50 preceding and 150 following)每行對應的資料視窗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)每行對應的資料視窗是之前50行,之后150行
over(order by salary rows between unbounded preceding and unbounded following)每行對應的資料視窗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
分析函式串列:
#AVG #CORR #COVAR_POP #COVAR_SAMP #COUNT #CUME_DIST #DENSE_RANK #FIRST #FIRST_VALUE #LAG #LAST #LAST_VALUE #LEAD
#MAX #MIN #NTILE #PERCENT_RANK #PERCENTILE_CONT #PERCENTILE_DISC #RANK #RATIO_TO_REPORT #RATIO_TO_REPORT #REGR_ (Linear Regression) Functions #ROW_NUMBER #STDDEV #STDDEV_POP #STDDEV_SAMP
AVG 功能描述:用于計算一個組和資料視窗內運算式的平均值。
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:回傳一對運算式的相關系數,它是如下的縮寫:
COVAR_POP(expr1,expr2)/STDDEV_POP(expr1)*STDDEV_POP(expr2))
從統計上講,相關性是變數之間關聯的強度,變數之間的關聯意味著在某種程度
上一個變數的值可由其它的值進行預測。通過回傳一個-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:下例回傳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:回傳一對運算式的總體協方差。
SAMPLE:下例CUM_COVP回傳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
2416103088 1475.97959 1721.97619..
COVAR_SAMP 功能描述:回傳一對運算式的樣本協方差
SAMPLE:下例CUM_COVS回傳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,如果指定一個運算式,count回傳運算式非空賦值的計數,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資料后出現的行數。
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總是回傳大于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,回傳的累計分布值為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子句中運算式的值,從查詢回傳的每一行,計算它們與其它行的相對位置。組內的資料按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運算式的值發生變化時,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)。密集的序列回傳的時沒有間隔的數
SAMPLE:下例中計算每個員工按部門磁區再按薪水排序,依次出現的序列號(注意與RANK函式的區別)
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回傳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式以從中取出記錄。
SAMPLE:下面例子中DENSE_RANK按部門磁區,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 MIN 函式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 MAX 函式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...
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續 1:FIRST_VALUE 功能描述:回傳組中資料視窗的第一個值。
SAMPLE:下面例子計算按部門磁區按薪水排序的資料視窗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預設排序的第一個名字
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,就好像游標是一個陣列一樣。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,若索引超出視窗的范圍,就回傳默認值(默認回傳的是組中第一行),其相反的函式是LEAD
SAMPLE:下面的例子中列prev_sal回傳按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回傳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式以從中取出記錄
SAMPLE:下面例子中DENSE_RANK按部門磁區,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函式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函式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:回傳組中資料視窗的最后一個值。
SAMPLE:下面例子計算按部門磁區按薪水排序的資料視窗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預設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,若索引超出視窗的范圍,就回傳默認值(默認回傳的是組中第一行)
SAMPLE:下面的例子中每行的"NextHired"回傳按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:在一個組中的資料視窗中查找運算式的最大值。
SAMPLE:下面例子中dept_max回傳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:在一個組中的資料視窗中查找運算式的最小值。
SAMPLE:下面例子中dept_min回傳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"運算式"的散串列示,例如,如果運算式=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運算式值平均分開,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,若運算式=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行資料分為4份
SELECT last_name, salary,NTILE(4) OVER (ORDER BY salary DESC) AS quartile FROM employeesWHERE 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)函式類似,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)。該函式總是回傳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函式對于等值的回傳序列值是一樣的
SELECT department_id, last_name, salary,PERCENT_RANK() OVER (PARTITION BY department_id ORDER BY salary) AS pr FROM employeesWHERE 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
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續 2:PERCENTILE_CONT 功能描述:回傳一個與輸入的分布百分比值相對應的資料值,分布百分比的計算方法見函式PERCENT_RANK,如果沒有正好對應的資料值,就通過下面演算法來得到值:
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:本函式與PERCENTILE_DISC的區別在找不到對應的分布值時回傳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:回傳一個與輸入的分布百分比值相對應的資料值,分布百分比的計算方法見函式CUME_DIST,如果沒有正好對應的資料值,就取大于該分布值的下一個值。注意:本函式與PERCENTILE_CONT的區別在找不到對應的分布值時回傳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子句中運算式的值,從查詢回傳的每一行,計算它們與其它行的相對位置。組內的資料按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運算式的值發生變化時,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磁區再按薪水排序,依次出現的序列號(注意與DENSE_RANK函式的區別)
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 dWHERE 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:該函式計算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 employeesWHERE 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:這些線性回歸函式適合最小二乘法回歸線,有9個不同的回歸函式可使用。
REGR_SLOPE:回傳斜率,等于COVAR_POP(expr1, expr2) / VAR_POP(expr2)
REGR_INTERCEPT:回傳回歸線的y截距,等于AVG(expr1) - REGR_SLOPE(expr1, expr2) * AVG(expr2)
REGR_COUNT:回傳用于填充回歸線的非空數字對的數目
REGR_R2:回傳回歸線的決定系數,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:計算回歸線的自變數(expr2)的平均值,去掉了空對(expr1, expr2)后,等于AVG(expr2)
REGR_AVGY:計算回歸線的應變數(expr1)的平均值,去掉了空對(expr1, expr2)后,等于AVG(expr1)
REGR_SXX: 回傳值等于REGR_COUNT(expr1, expr2) * VAR_POP(expr2)
REGR_SYY: 回傳值等于REGR_COUNT(expr1, expr2) * VAR_POP(expr1)
REGR_SXY: 回傳值等于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
uj5u.com熱心網友回復:
續3: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_mont;
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
ROW_NUMBER 功能描述:回傳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:下例回傳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:下例回傳部門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
0Khoo 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:該函式計算總體標準偏離,并回傳總體變數的平方根,其回傳值與VAR_POP函式的平方根相同。(Standard Deviation-Population)
SAMPLE:下例回傳部門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 employeesWHERE 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: 該函式計算累積樣本標準偏離,并回傳總體變數的平方根,其回傳值與VAR_POP函式的平方根相同。(Standard Deviation-Sample)
SAMPLE:下例回傳部門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 employeesWHERE 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:該函式計算組中運算式的累積和。
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)該函式回傳非空集合的總體變數(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數(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)該函式回傳非空集合的樣本變數(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數
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:該函式回傳運算式的變數,Oracle計算該變數如下:
如果運算式中行數為1,則回傳0
如果運算式中行數大于1,則回傳VAR_SAMPSAMPLE:
下例回傳部門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
0Khoo 3100 31205000
Tobias 2800 21623333.3
Baida 2900 16283333.3
Himuro 2600 13317000
Colmenares 2500 11307000
uj5u.com熱心網友回復:
仍然適用于 10g,11g以及12c等后續版本uj5u.com熱心網友回復:
講的真詳細啊。
只用其中幾個
uj5u.com熱心網友回復:
6666666666666666uj5u.com熱心網友回復:
6666666666666666uj5u.com熱心網友回復:
666666uj5u.com熱心網友回復:
感謝樓主分享
uj5u.com熱心網友回復:
看看是什么~
uj5u.com熱心網友回復:
66666666666666666666666666666666666666666666666uj5u.com熱心網友回復:
uj5u.com熱心網友回復:
寫的太好了,很有用!uj5u.com熱心網友回復:
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666666666666uj5u.com熱心網友回復:
感謝樓主分享!uj5u.com熱心網友回復:
不錯啊不錯啊不錯啊不錯啊不錯啊不錯啊不錯啊不錯啊不錯啊不錯啊不錯啊不錯啊uj5u.com熱心網友回復:
按時打算的撒發放uj5u.com熱心網友回復:
uj5u.com熱心網友回復:
多謝樓主分享。。。。uj5u.com熱心網友回復:
分析函式挺有用uj5u.com熱心網友回復:
路過,幫忙頂下。
uj5u.com熱心網友回復:
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標籤:高級技術
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