重写查询以使用分析函数

Question

我有一个 Table 事件记录 Insert、Update 和 D 事件元素。见MWE她：http://sqlfiddle.com/#!4/6c2cb1/1

DDL 语句

CREATE TABLE "EVENTS" 
   (
    "EVENT_ID" VARCHAR2(30 CHAR), --Name of the Event
    "EVENT_LOCATION" VARCHAR2(60 CHAR), --Location on which the event occured
    "EVENT_TRIGGER" VARCHAR2(2 CHAR),  --Trigger which protocolled the event (I,U or D)
    "EVENT_CHANGE_ID" NUMBER,  --Unique Sequence Number
    "EVENT_CHANGE_DATE" DATE DEFAULT SYSTIMESTAMP
   );

INSERT INTO EVENTS (EVENT_ID,EVENT_LOCATION,EVENT_TRIGGER,EVENT_CHANGE_ID,EVENT_CHANGE_DATE) 
VALUES ('EVENT1','LOC1','I',1,SYSTIMESTAMP-1);
INSERT INTO EVENTS (EVENT_ID,EVENT_LOCATION,EVENT_TRIGGER,EVENT_CHANGE_ID,EVENT_CHANGE_DATE) 
VALUES ('EVENT1','LOC2','U',11,SYSTIMESTAMP-1);
INSERT INTO EVENTS (EVENT_ID,EVENT_LOCATION,EVENT_TRIGGER,EVENT_CHANGE_ID,EVENT_CHANGE_DATE) 
VALUES ('EVENT1','LOC4','U',117,SYSTIMESTAMP-1);
INSERT INTO EVENTS (EVENT_ID,EVENT_LOCATION,EVENT_TRIGGER,EVENT_CHANGE_ID,EVENT_CHANGE_DATE) 
VALUES ('EVENT1','LOC7','D',1430,SYSTIMESTAMP-1);

INSERT INTO EVENTS (EVENT_ID,EVENT_LOCATION,EVENT_TRIGGER,EVENT_CHANGE_ID,EVENT_CHANGE_DATE) 
VALUES ('EVENT2','LOC1','I',2,SYSTIMESTAMP-1/48);
INSERT INTO EVENTS (EVENT_ID,EVENT_LOCATION,EVENT_TRIGGER,EVENT_CHANGE_ID,EVENT_CHANGE_DATE) 
VALUES ('EVENT2','LOC2','U',131,SYSTIMESTAMP-1/48);
INSERT INTO EVENTS (EVENT_ID,EVENT_LOCATION,EVENT_TRIGGER,EVENT_CHANGE_ID,EVENT_CHANGE_DATE) 
VALUES ('EVENT2','LOC5','D',11337,SYSTIMESTAMP-1/48);
INSERT INTO EVENTS (EVENT_ID,EVENT_LOCATION,EVENT_TRIGGER,EVENT_CHANGE_ID,EVENT_CHANGE_DATE) 
VALUES ('EVENT2','LOC7','D',14430,SYSTIMESTAMP-1/48);

我想确定 I在 LOC1 插入和 D在 LOC7 删除而没有任何 [=23] 的事件数量=]D之间的元素。

SELECT COUNT(*) AS QTY, TRUNC(A.EVENT_CHANGE_DATE) AS DAY
FROM (
    SELECT EVENT_ID, EVENT_CHANGE_ID, EVENT_CHANGE_DATE FROM EVENTS WHERE EVENT_TRIGGER = 'I' AND EVENT_LOCATION = 'LOC1'
    ) A,
    (SELECT EVENT_ID, EVENT_CHANGE_ID, EVENT_CHANGE_DATE FROM EVENTS WHERE EVENT_TRIGGER = 'D' AND EVENT_LOCATION = 'LOC7')
    B
WHERE B.EVENT_CHANGE_ID > A.EVENT_CHANGE_ID AND A.EVENT_ID = B.EVENT_ID
    AND not exists (SELECT EVENT_ID, EVENT_CHANGE_ID, EVENT_CHANGE_DATE FROM EVENTS WHERE EVENT_TRIGGER = 'D' AND EVENT_CHANGE_ID > A.EVENT_CHANGE_ID AND EVENT_CHANGE_ID < B.EVENT_CHANGE_ID and EVENT_ID = A.EVENT_ID) 
group by TRUNC(A.EVENT_CHANGE_DATE)
ORDER BY TRUNC(A.EVENT_CHANGE_DATE);

我天真的方法可行，但我想知道是否可以使用分析函数重写此查询。原始 Tables 包含多达 100 万条记录，3 次完整 Table 扫描在执行时间和性能方面毫无意义。

是否可以使用分析函数使此查询更高效？

Answer 1

这看起来很适合 SQL 模式匹配：

select * from events
match_recognize (
  partition by event_id
  order by event_change_date
  measures 
    count ( ins.* ) ins_count,
    min ( event_change_date ) dt
  pattern ( ins upd* del )
  define 
    ins as event_trigger = 'I' and event_location = 'LOC1',
    upd as event_trigger = 'U',
    del as event_trigger = 'D' and event_location = 'LOC7'
);

INS_COUNT    DT                     
           1 16-MAR-2020 12:33:58

这会在 LOC1 处搜索 I(nserts)，然后在 LOC7 处搜索 D(elete)，中间有任意数量的 U(pdates)。

Answer 2

仅使用经典解析函数。

仅过滤相关事件

(EVENT_TRIGGER = 'I' AND EVENT_LOCATION = 'LOC1')  OR  -- only LOC1 inserts
 EVENT_TRIGGER = 'D')                                  -- all deletes

然后LEAD下一个D删除并检查位置

with evnt as
(
  select EVENT_ID, EVENT_LOCATION, EVENT_TRIGGER, EVENT_CHANGE_DATE,
    lead(EVENT_TRIGGER) over (PARTITION BY EVENT_ID 
                                  order by EVENT_CHANGE_DATE, EVENT_LOCATION)
      as EVENT_TRIGGER_LEAD,
    lead(EVENT_LOCATION) over (PARTITION BY EVENT_ID
                                   order by EVENT_CHANGE_DATE, EVENT_LOCATION)
      as EVENT_LOCATION_LEAD
  from EVENTS
  where (EVENT_TRIGGER = 'I' AND EVENT_LOCATION = 'LOC1') OR EVENT_TRIGGER = 'D'
)
select 
  EVENT_ID, EVENT_LOCATION, EVENT_TRIGGER, EVENT_CHANGE_DATE,
  EVENT_TRIGGER_LEAD, EVENT_LOCATION_LEAD
from evnt
where EVENT_TRIGGER = 'I'
  and EVENT_TRIGGER_LEAD = 'D' 
  and EVENT_LOCATION_LEAD = 'LOC7'
order by EVENT_ID, EVENT_CHANGE_DATE, EVENT_LOCATION;

Answer 3

你可以用解析函数SUM在结果LOC1和I时加1，在[=15=时加-1 ]，则最终结果将是具有 sum = 0 和 location as LOC7.

的记录

查看答案：

SQL> SELECT EVENT_ID FROM
  2      ( SELECT SUM(CASE
  3                  WHEN EVENT_LOCATION = 'LOC1' AND EVENT_TRIGGER = 'I' THEN 1
  4                  WHEN EVENT_TRIGGER = 'D' THEN - 1
  5               END) OVER( PARTITION BY EVENT_ID ORDER BY EVENT_CHANGE_DATE ) AS SM,
  6               T.*
  7          FROM EVENTS T
  8      ) T
  9  WHERE EVENT_LOCATION = 'LOC7' AND SM = 0;

EVENT_ID
------------
EVENT1

SQL>

干杯！！

Answer 4

使用 LEAD 分析函数：

SELECT COUNT(*) as qty,
       TRUNC(event_change_date)day  
       FROM(
            SELECT
                event_location,
                event_trigger,
                event_change_date,
                lead(event_trigger) 
                  OVER(PARTITION BY trunc(event_change_date) 
                       ORDER BY to_number(substr(event_location, - 1, 1))) rn 
            FROM events
) WHERE event_trigger <> 'D'
AND rn <> 'D'
AND event_trigger = rn
GROUP BY trunc(event_change_date);

QTY        DAY     
---------- --------
         1 16-03-20

逻辑：

将每天的事件分组，并使用 SUBSTR 根据从 1 到 7 的位置对它们进行排序，并从字符串的反面获取数字。
使用 LEAD 比较 event_trigger 和它的铅。
每个日期的PARTITIONED组中的event_trigger不应该有1到7的DELETE。

重写查询以使用分析函数

Rewrite query to use Analytic Functions

sql

oracle

analytics