Oracle分析函數(shù)——數(shù)據(jù)分布函數(shù)及報(bào)表函數(shù)

CUME_DIST

功能描述：計(jì)算一行在組中的相對(duì)位置，CUME_DIST總是返回大于0、小于或等于1的數(shù)，該數(shù)表示該行在N行中的位置。例如，在一個(gè)3行的組中，返回的累計(jì)分布值為1/3、2/3、3/3

SAMPLE：下例中計(jì)算每個(gè)部門的員工按薪水排序依次累積出現(xiàn)的分布百分比

SELECT

?department_id,

?first_name||' '||last_name employee_name,

?salary,

?CUME_DIST() OVER (PARTITION BY department_id ORDER BY salary) AS cume_dist

FROM employees

NTILE

功能描述：將一個(gè)組分為"表達(dá)式"的散列表示，例如，如果表達(dá)式=4，則給組中的每一行分配一個(gè)數(shù)（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(shù)不能由表達(dá)式值平均分開(kāi)，則對(duì)這些行進(jìn)行分配時(shí)，組中就沒(méi)有任何percentile的行數(shù)比其它percentile的行數(shù)超過(guò)一行，最低的percentile是那些擁有額外行的percentile。例如，若表達(dá)式=4，行數(shù)=21，則percentile=1的有5行，percentile=2的有5行等等。

SAMPLE：下例中把6行數(shù)據(jù)分為4份

SELECT

?department_id,

?first_name||' '||last_name employee_name,

?salary,

?NTILE(4) OVER (PARTITION BY department_id ORDER BY salary DESC) AS quartile

?FROM employees

?

PERCENT_RANK

功能描述：和CUME_DIST（累積分配）函數(shù)類似，對(duì)于一個(gè)組中給定的行來(lái)說(shuō)，在計(jì)算那行的序號(hào)時(shí)，先減1，然后除以n-1（n為組中所有的行數(shù)）。該函數(shù)總是返回0～1（包括1）之間的數(shù)。

SAMPLE：下例中如果Khoo的salary為2900，則pr值為0.6，因?yàn)?/span>RANK函數(shù)對(duì)于等值的返回序列值是一樣的

?

SELECT??

?department_id,

?first_name||' '||last_name employee_name,

?salary,

?PERCENT_RANK() OVER (PARTITION BY department_id ORDER BY salary) AS pr

FROM employees

ORDER BY department_id,salary;

?

PERCENTILE_DISC

功能描述：返回一個(gè)與輸入的分布百分比值相對(duì)應(yīng)的數(shù)據(jù)值，分布百分比的計(jì)算方法見(jiàn)函數(shù)CUME_DIST，如果沒(méi)有正好對(duì)應(yīng)的數(shù)據(jù)值，就取大于該分布值的下一個(gè)值。

注意：本函數(shù)與PERCENTILE_CONT的區(qū)別在找不到對(duì)應(yīng)的分布值時(shí)返回的替代值的計(jì)算方法不同

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SAMPLE：下例中0.7的分布值在部門30中沒(méi)有對(duì)應(yīng)的Cume_Dist值，所以就取下一個(gè)分布值0.83333333所對(duì)應(yīng)的SALARY來(lái)替代

?

SELECT

?department_id,

?first_name||' '||last_name employee_name,

?salary,

?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<!--[if !vml]--><!--[endif]-->

PERCENTILE_CONT

功能描述：返回一個(gè)與輸入的分布百分比值相對(duì)應(yīng)的數(shù)據(jù)值，分布百分比的計(jì)算方法見(jiàn)函數(shù)PERCENT_RANK，如果沒(méi)有正好對(duì)應(yīng)的數(shù)據(jù)值，就通過(guò)下面算法來(lái)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(nèi)的行數(shù)

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(shù)與PERCENTILE_DISC的區(qū)別在找不到對(duì)應(yīng)的分布值時(shí)返回的替代值的計(jì)算方法不同

算法太復(fù)雜，看不懂了L

SAMPLE：在下例中，對(duì)于部門60的Percentile_Cont值計(jì)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

?department_id,

?first_name||' '||last_name employee_name,

?salary,??

?PERCENTILE_DISC(0.7) WITHIN GROUP (ORDER BY salary) OVER (PARTITION BY department_id) "Percentile_Disc",

?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

總案例

SELECT

?department_id,

?first_name||' '||last_name employee_name,

?salary,

?CUME_DIST() OVER (PARTITION BY department_id ORDER BY salary) AS cume_dist, --數(shù)據(jù)分布百分比

?NTILE(4) OVER (PARTITION BY department_id ORDER BY salary) AS quartile,????--數(shù)據(jù)分布，以NTILE中的exp來(lái)計(jì)算

?PERCENT_RANK() OVER (PARTITION BY department_id ORDER BY salary) AS pr,????--數(shù)據(jù)分布百分比，從0開(kāi)始計(jì)

?PERCENTILE_DISC(0.7) WITHIN GROUP (ORDER BY salary ) OVER (PARTITION BY department_id) "Percentile_Disc",?--輸入的分布百分比值相對(duì)應(yīng)的數(shù)據(jù)值

?PERCENTILE_CONT(0.7) WITHIN GROUP (ORDER BY salary) OVER (PARTITION BY department_id) "Percentile_Cont"???--表達(dá)式太復(fù)雜了，...

FROM employees

?

RATIO_TO_REPORT

功能描述：該函數(shù)計(jì)算expression/(sum(expression))的值，它給出相對(duì)于總數(shù)的百分比，即當(dāng)前行對(duì)sum(expression)的貢獻(xiàn)。

SAMPLE：下例計(jì)算每個(gè)員工的工資占該類員工總工資的百分比

SELECT

?department_id,

?first_name||' '||last_name employee_name,

?salary,

?RATIO_TO_REPORT(salary) OVER () AS rr

FROM employees

WHERE job_id = 'PU_CLERK';

REGR_ (Linear Regression) Functions

功能描述：這些線性回歸函數(shù)適合最小二乘法回歸線，有9個(gè)不同的回歸函數(shù)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(shù)字對(duì)的數(shù)目

REGR_R2：返回回歸線的決定系數(shù)，計(jì)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(jì)算回歸線的自變量(expr2)的平均值，去掉了空對(duì)(expr1, expr2)后，等于AVG(expr2)

REGR_AVGY：計(jì)算回歸線的應(yīng)變量(expr1)的平均值，去掉了空對(duì)(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)

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（下面的例子都是在SH用戶下完成的）

SAMPLE 1：下例計(jì)算1998年最后三個(gè)星期中兩種產(chǎn)品（260和270）在周末的銷售量中已開(kāi)發(fā)票數(shù)量和總數(shù)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;

?

SAMPLE 2：下例計(jì)算1998年4月每天的累積交易數(shù)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;

?

SAMPLE 3：下例計(jì)算1998年每月銷售量中已開(kāi)發(fā)票數(shù)量和總數(shù)量的累積回歸線決定系數(shù)

?

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;

?

SAMPLE 4：下例計(jì)算1998年12月最后兩周產(chǎn)品260的銷售量中已開(kāi)發(fā)票數(shù)量和總數(shù)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;

?

SAMPLE 5：下例計(jì)算產(chǎn)品260和270在1998年2月周末銷售量中已開(kāi)發(fā)票數(shù)量和總數(shù)量的累積REGR_SXY, REGR_SXX, and REGR_SYY統(tǒng)計(jì)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;

轉(zhuǎn)載于:https://www.cnblogs.com/huozhicheng/archive/2010/09/03/2533172.html

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