行与客户和月

Question

最新值我有一个跟踪客户分布中的变化的表。 Here's a simplified version：

CREATE TABLE HISTORY (
    CUSTOMER_ID NUMBER(9,0), 
    DATE_CHANGED DATE, 
    ACCOUNT_TYPE VARCHAR2(20), 

    CONSTRAINT HISTORY_PK PRIMARY KEY (CUSTOMER_ID, DATE_CHANGED) 
); 

INSERT INTO HISTORY (CUSTOMER_ID, DATE_CHANGED, ACCOUNT_TYPE) VALUES (200, TO_DATE('05/01/2013 00:00:00','DD/MM/RRRR HH24:MI:SS'), 'Premium'); 
INSERT INTO HISTORY (CUSTOMER_ID, DATE_CHANGED, ACCOUNT_TYPE) VALUES (300, TO_DATE('17/02/2013 00:00:00','DD/MM/RRRR HH24:MI:SS'), 'Free'); 
INSERT INTO HISTORY (CUSTOMER_ID, DATE_CHANGED, ACCOUNT_TYPE) VALUES (100, TO_DATE('05/03/2013 00:00:00','DD/MM/RRRR HH24:MI:SS'), 'Free'); 
INSERT INTO HISTORY (CUSTOMER_ID, DATE_CHANGED, ACCOUNT_TYPE) VALUES (100, TO_DATE('12/03/2013 00:00:00','DD/MM/RRRR HH24:MI:SS'), 'Standard'); 
INSERT INTO HISTORY (CUSTOMER_ID, DATE_CHANGED, ACCOUNT_TYPE) VALUES (200, TO_DATE('22/03/2013 00:00:00','DD/MM/RRRR HH24:MI:SS'), 'Standard'); 
INSERT INTO HISTORY (CUSTOMER_ID, DATE_CHANGED, ACCOUNT_TYPE) VALUES (100, TO_DATE('29/03/2013 00:00:00','DD/MM/RRRR HH24:MI:SS'), 'Premium'); 

该数据由第三方维护。我的最终目标是在给定的时间范围内获得每个帐户类型和月份的客户总数，但现在，我想从简单的事情开始 - 显示记录更改时每个月/客户组合的最新帐户类型：

YEAR MONTH CUSTOMER_ID ACCOUNT_TYPE 
==== ===== =========== ============ 
2013  1   200 Premium 
2013  2   300 Free 
2013  3   100 Premium 
2013  3   200 Standard 

在这里，客户100在3月份做了三次更改;我们显示“高级”，因为它有3月份的最新日期。

查询获得所有行会是这样：

SELECT EXTRACT(YEAR FROM DATE_CHANGED) AS YEAR, 
EXTRACT(MONTH FROM DATE_CHANGED) AS MONTH, 
CUSTOMER_ID, ACCOUNT_TYPE 
FROM HISTORY 
ORDER BY YEAR, MONTH, CUSTOMER_ID, DATE_CHANGED 

是否可以过滤掉使用聚合函数不需要行？使用分析函数更有意义吗？

（并且，在任何一种情况下，这将是足够的功能？）

编辑：我一直在问不需要的行的例子。还有三月是3行客户100：

'05/03/2013 00:00:00', 'Free' 
'12/03/2013 00:00:00', 'Standard' 
'29/03/2013 00:00:00', 'Premium' 

不需要的行是'Free'和'Standard'，因为他们不是在当月的最新产品。

Answer 1

SELECT YEAR 
     ,MONTH 
     ,customer_id 
     ,max(ACCOUNT_TYPE) keep(dense_rank FIRST ORDER BY date_changed DESC) LAST_ACC 
FROM (
    SELECT EXTRACT(YEAR FROM DATE_CHANGED) AS YEAR, 
     EXTRACT(MONTH FROM DATE_CHANGED) AS MONTH, 
     CUSTOMER_ID, 
     date_changed, 
     account_type 
    FROM HISTORY 
) 
GROUP BY YEAR, MONTH, customer_id 
ORDER BY YEAR, MONTH, CUSTOMER_ID 


| YEAR | MONTH | CUSTOMER_ID | LAST_ACC | 
----------------------------------------- 
| 2013 |  1 |   200 | Premium | 
| 2013 |  2 |   300 |  Free | 
| 2013 |  3 |   100 | Premium | 
| 2013 |  3 |   200 | Standard | 

http://sqlfiddle.com/#!4/e493a/15

Answer 2

SELECT YEAR, MONTH, CUSTOMER_ID, ACCOUNT_TYPE 
FROM 
(
SELECT EXTRACT(YEAR FROM DATE_CHANGED) AS YEAR, 
     EXTRACT(MONTH FROM DATE_CHANGED) AS MONTH, 
     CUSTOMER_ID, 
     ACCOUNT_TYPE, 
     ROW_NUMBER() OVER (PARTITION BY CUSTOMER_ID, 
             EXTRACT(YEAR FROM DATE_CHANGED), 
             EXTRACT(MONTH FROM DATE_CHANGED) 
          ORDER BY EXTRACT(YEAR FROM DATE_CHANGED) DESC, 
            EXTRACT(MONTH FROM DATE_CHANGED) DESC, 
            DATE_CHANGED DESC) RN 
FROM HISTORY 
) 
WHERE RN = 1 
ORDER BY YEAR, MONTH, CUSTOMER_ID 

• SQLFiddle Demo

OUTPUT

╔══════╦═══════╦═════════════╦══════════════╗ 
║ YEAR ║ MONTH ║ CUSTOMER_ID ║ ACCOUNT_TYPE ║ 
╠══════╬═══════╬═════════════╬══════════════╣ 
║ 2013 ║  1 ║   200 ║ Premium  ║ 
║ 2013 ║  2 ║   300 ║ Free   ║ 
║ 2013 ║  3 ║   100 ║ Premium  ║ 
║ 2013 ║  3 ║   200 ║ Standard  ║ 
╚══════╩═══════╩═════════════╩══════════════╝ 

Answer 3

SELECT DISTINCT 
CUSTOMER_ID, 
EXTRACT(YEAR FROM DATE_CHANGED) AS YEAR, 
EXTRACT(MONTH FROM DATE_CHANGED) AS MONTH, 
LAST_VALUE(ACCOUNT_TYPE) 
OVER(PARTITION BY CUSTOMER_ID,TO_CHAR(DATE_CHANGED,'YYYY-MM') ORDER BY DATE_CHANGED ROWS BETWEEN UNBOUNDED PRECEDING AND UNBOUNDED FOLLOWING) AS ACCOUNT_TYPE 
FROM HISTORY 



CUSTOMER_ID YEAR MONTH ACCOUNT_TYPE 
200   2013 1 Premium 
300   2013 2 Free 
100   2013 3 Premium 
200   2013 3 Standard 

http://www.sqlfiddle.com/#!4/fab60/13