Oracle：优化两次自联接查询
[英]Oracle: Optimizing twice self-join query
问题描述
我正在努力使过去两天的查询效率更高。 我已经了解了有关Oracle索引行为的更多信息，我认为在这一点上我感到困惑，哪些应该起作用，哪些不起作用。
基本上，查询是对值求和并与昨天和上周的值进行比较。
我一直在努力分解它，在脑海里玩弄分析查询和更改索引顺序，但是似乎没有任何效果。 我所有的测试都是在具有50万行的表上进行的，一旦我在具有2000万行的表上进行了测试，那将永远花光。
任何帮助是极大的赞赏。
我修改了原始帖子以帮助您。 :)
CREATE TABLE TABLE_1
(ORDER_LINE_ID NUMBER, OFFSET NUMBER, BREAK_ID NUMBER, ZONE NUMBER, NETWORK NUMBER, HOUR_OF_DAY NUMBER, START_TIME DATE, END_TIME DATE, SUCCESS NUMBER
CONSTRAINT "TABLE_1_PK" PRIMARY KEY (ORDER_LINE_ID, OFFSET, BREAK_ID, ZONE, HOUR_OF_DAY))
-- SUCCESS is already aggregated during the insert
-- These are last week's records
INSERT INTO TABLE_1 (ORDER_LINE_ID, OFFSET, BREAK_ID, ZONE, NETWORK, HOUR_OF_DAY, START_TIME, END_TIME, SUCCESS)
VALUES (1,0,1, 1, 1, 2016042001,'04/20/2016 00:00:00', '04/20/2016 02:00:00', 1);
INSERT INTO TABLE_1 (ORDER_LINE_ID, OFFSET, BREAK_ID, ZONE, NETWORK, HOUR_OF_DAY, START_TIME, END_TIME, SUCCESS)
VALUES (1,30,1, 1, 1, 2016042001,'04/20/2016 00:00:00', '04/20/2016 02:00:00', 2);
INSERT INTO TABLE_1 (ORDER_LINE_ID, OFFSET, BREAK_ID, ZONE, NETWORK, HOUR_OF_DAY, START_TIME, END_TIME, SUCCESS)
VALUES (2,0,1, 1, 1, 2016042001,'04/20/2016 00:00:00', '04/20/2016 02:00:00', 1);
INSERT INTO TABLE_1 (ORDER_LINE_ID, OFFSET, BREAK_ID, ZONE, NETWORK, HOUR_OF_DAY, START_TIME, END_TIME, SUCCESS)
VALUES (2,30,1, 1, 1, 2016042001,'04/20/2016 00:00:00', '04/20/2016 02:00:00', 1);
-- These are yesterday's records
INSERT INTO TABLE_1 (ORDER_LINE_ID, OFFSET, BREAK_ID, ZONE, NETWORK, HOUR_OF_DAY, START_TIME, END_TIME, SUCCESS)
VALUES (3,0,1, 1, 1, 2016042601,'04/26/2016 00:00:00', '04/26/2016 02:00:00', 1);
INSERT INTO TABLE_1 (ORDER_LINE_ID, OFFSET, BREAK_ID, ZONE, NETWORK, HOUR_OF_DAY, START_TIME, END_TIME, SUCCESS)
VALUES (3,30,1, 1, 1, 2016042601,'04/26/2016 00:00:00', '04/26/2016 02:00:00', 2);
INSERT INTO TABLE_1 (ORDER_LINE_ID, OFFSET, BREAK_ID, ZONE, NETWORK, HOUR_OF_DAY, START_TIME, END_TIME, SUCCESS)
VALUES (4,0,1, 1, 1, 2016042601,'04/26/2016 00:00:00', '04/26/2016 02:00:00', 1);
INSERT INTO TABLE_1 (ORDER_LINE_ID, OFFSET, BREAK_ID, ZONE, NETWORK, HOUR_OF_DAY, START_TIME, END_TIME, SUCCESS)
VALUES (4,30,1, 1, 1, 2016042601,'04/26/2016 00:00:00', '04/26/2016 02:00:00', 1);
-- This is today's records
INSERT INTO TABLE_1 (ORDER_LINE_ID, OFFSET, BREAK_ID, ZONE, NETWORK, HOUR_OF_DAY, START_TIME, END_TIME, SUCCESS)
VALUES (5,0,1, 1, 1, 2016042701,'04/27/2016 00:00:00', '04/27/2016 02:00:00', 1);
INSERT INTO TABLE_1 (ORDER_LINE_ID, OFFSET, BREAK_ID, ZONE, NETWORK, HOUR_OF_DAY, START_TIME, END_TIME, SUCCESS)
VALUES (5,30,1, 1, 1, 2016042701,'04/27/2016 00:00:00', '04/27/2016 02:00:00', 1);
-- Original twice join query
SELECT BREAK_ID, ORDER_LINE_ID, HOUR_OF_DAY, OFFSET, ZONE, NETWORK, START_TIME, END_TIME, SUM(SUCCESS), SUM(YESTERDAY_SUCCESS), SUM(LAST_WEEK_SUCCESS)
FROM TABLE_1 CURRENT_DAY
LEFT OUTER JOIN (
SELECT SUM(SUCCESS) YESTERDAY_SUCCESS, ZONE, NETWORK, HOUR_OF_DAY, START_TIME, END_TIME FROM TABLE_1
GROUP BY ZONE, NETWORK, HOUR_OF_DAY, START_TIME, END_TIME
) YESTERDAY
ON YESTERDAY.START_TIME + 1 = CURRENT_DAY.START_TIME
AND YESTERDAY.END_TIME + 1 = CURRENT_DAY.END_TIME
AND YESTERDAY.HOUR_OF_DAY = CURRENT_DAY.HOUR_OF_DAY
AND YESTERDAY.NETWORK = CURRENT_DAY.NETWORK
AND YESTERDAY.ZONE = CURRENT_DAY.ZONE
LEFT OUTER JOIN (
SELECT SUM(SUCCESS) LAST_WEEK_SUCCESS, ZONE, NETWORK, HOUR_OF_DAY, START_TIME, END_TIME FROM TABLE_1
GROUP BY ZONE, NETWORK, HOUR_OF_DAY, START_TIME, END_TIME
) LAST_WEEK
ON YESTERDAY.START_TIME + 7 = CURRENT_DAY.START_TIME
AND YESTERDAY.END_TIME + 7 = CURRENT_DAY.END_TIME
AND YESTERDAY.HOUR_OF_DAY = CURRENT_DAY.HOUR_OF_DAY
AND YESTERDAY.NETWORK = CURRENT_DAY.NETWORK
AND YESTERDAY.ZONE = CURRENT_DAY.ZONE
GROUP BY BREAK_ID, ORDER_LINE_ID, HOUR_OF_DAY, OFFSET, ZONE, NETWORK, START_TIME, END_TIME;
-- Using Analytic Query (thank you to MT0)
SELECT BREAK_ID, ORDER_LINE_ID, HOUR_OF_DAY, OFFSET, ZONE, NETWORK, START_TIME, END_TIME, SUM(SUCCESS), SUM(YESTERDAY_SUCCESS), SUM(LAST_WEEK_SUCCESS)
FROM (
SUM( SUCCESS )
OVER ( PARTITION BY ZONE, NETWORK, HOUR_OF_DAY, TO_CHAR(START_TIME, 'HH24:MI:SS'), TO_CHAR(END_TIME, 'HH24:MI:SS')
ORDER BY START_TIME
RANGE BETWEEN INTERVAL '1' DAY PRECDEDING AND INTERVAL '1' DAY PRECEDING
) AS YESTERDAY_SUCCESS,
SUM ( SUCCESS )
OVER ( PARTITION BY ZONE, NETWORK, HOUR_OF_DAY, TO_CHAR(START_TIME, 'HH24:MI:SS'), TO_CHAR(END_TIME, 'HH24:MI:SS')
ORDER BY START_TIME
RANGE BETWEEN INTERVAL '7' DAY PRECDEDING AND INTERVAL '7' DAY PRECEDING
) AS LAST_WEEK_SUCCESS
FROM TABLE_1
) T1
WHERE SYSDATE - INTERVAL '12' HOUR <= START_TIME
AND START_TIME < SYSDATE - INTERVAL '1' HOUR
GROUP BY BREAK_ID, ORDER_LINE_ID, HOUR_OF_DAY, OFFSET, ZONE, NETWORK, START_TIME, END_TIME;
我必须说谢谢您为将这个问题提出我希望可以理解的问题所提供的帮助。 一切正常，但性能可能需要一些调整。
在具有500K行的表上需要1.8秒
拥有2000万行的表格400秒
我还想添加Oracle提供的一些执行计划。 我在调整性能时遇到问题。
-- using twice self join
--------------------------------------------------------------------------------------------------------------------------------------------------------------------
| Id | Operation | Name | Starts | E-Rows | A-Rows | A-Time | Buffers | Reads | Writes | OMem | 1Mem | O/1/M |
--------------------------------------------------------------------------------------------------------------------------------------------------------------------
| 0 | SELECT STATEMENT | | 1 | | 50 |00:00:00.84 | 99875 | 217 | 1705 | | | |
| 1 | HASH GROUP BY | | 1 | 6711 | 50 |00:00:00.84 | 99875 | 217 | 1705 | 1616K| 995K| |
|* 2 | FILTER | | 1 | | 119K|00:00:00.65 | 99875 | 0 | 0 | | | |
| 3 | NESTED LOOPS OUTER | | 1 | 54M| 119K|00:00:00.64 | 99875 | 0 | 0 | | | |
|* 4 | HASH JOIN OUTER | | 1 | 109 | 119K|00:00:00.52 | 99875 | 0 | 0 | 13M| 2093K| 1/0/0|
| 5 | TABLE ACCESS BY INDEX ROWID| TABLE_1_IDX | 1 | 109 | 119K|00:00:00.14 | 85908 | 0 | 0 | | | |
|* 6 | INDEX RANGE SCAN | START_TIME_IDX | 1 | 109 | 119K|00:00:00.02 | 320 | 0 | 0 | | | |
| 7 | VIEW | | 1 | 1250 | 29311 |00:00:00.23 | 13967 | 0 | 0 | | | |
| 8 | HASH GROUP BY | | 1 | 1250 | 29311 |00:00:00.22 | 13967 | 0 | 0 | 3008K| 1094K| 1/0/0|
|* 9 | FILTER | | 1 | | 88627 |00:00:00.20 | 13967 | 0 | 0 | | | |
|* 10 | TABLE ACCESS FULL | TABLE_1 | 1 | 1250 | 88627 |00:00:00.19 | 13967 | 0 | 0 | | | |
| 11 | VIEW | | 119K| 499K| 0 |00:00:00.10 | 0 | 0 | 0 | | | |
| 12 | SORT GROUP BY | | 119K| 499K| 0 |00:00:00.08 | 0 | 0 | 0 | 1024 | 1024 | 1/0/0|
|* 13 | FILTER | | 119K| | 0 |00:00:00.02 | 0 | 0 | 0 | | | |
| 14 | TABLE ACCESS FULL | TABLE_1 | 0 | 499K| 0 |00:00:00.01 | 0 | 0 | 0 | | | |
--------------------------------------------------------------------------------------------------------------------------------------------------------------------
Predicate Information (identified by operation id):
---------------------------------------------------
2 - filter(SYSDATE@!-17<SYSDATE@!-16)
4 - access("YESTERDAY"."ZONE"="T1"."ZONE" AND "YESTERDAY"."NETWORK"="T1"."NETWORK" AND "YESTERDAY"."HOUR_OF_DAY"="T1"."HOUR_OF_DAY"
AND "T1"."END_TIME"=INTERNAL_FUNCTION("YESTERDAY"."END_TIME")+1 AND
"T1"."START_TIME"=INTERNAL_FUNCTION("YESTERDAY"."START_TIME")+1)
6 - access("T1"."START_TIME">=SYSDATE@!-17 AND "T1"."START_TIME"<SYSDATE@!-16)
9 - filter(SYSDATE@!-17<SYSDATE@!-16)
10 - filter((INTERNAL_FUNCTION("START_TIME")+1>=SYSDATE@!-17 AND INTERNAL_FUNCTION("START_TIME")+1<SYSDATE@!-16))
13 - filter(("YESTERDAY"."ZONE"="T1"."ZONE" AND "YESTERDAY"."NETWORK"="T1"."NETWORK" AND "YESTERDAY"."HOUR_OF_DAY"="T1"."HOUR_OF_DAY"
AND "T1"."END_TIME"=INTERNAL_FUNCTION("YESTERDAY"."END_TIME")+7 AND
"T1"."START_TIME"=INTERNAL_FUNCTION("YESTERDAY"."START_TIME")+7))
使用分析查询的另一个执行计划（再次感谢MT0）
-- using analytic query
-------------------------------------------------------------------------------------------------------------------------------
| Id | Operation | Name | Starts | E-Rows | A-Rows | A-Time | Buffers | OMem | 1Mem | O/1/M |
-------------------------------------------------------------------------------------------------------------------------------
| 0 | SELECT STATEMENT | | 1 | | 50 |00:00:01.51 | 13967 | | | |
| 1 | HASH GROUP BY | | 1 | 499K| 50 |00:00:01.51 | 13967 | 98M| 7788K| |
|* 2 | VIEW | | 1 | 499K| 119K|00:00:01.15 | 13967 | | | |
| 3 | WINDOW SORT | | 1 | 499K| 499K|00:00:01.43 | 13967 | 66M| 2823K| 1/0/0|
|* 4 | FILTER | | 1 | | 499K|00:00:00.16 | 13967 | | | |
| 5 | TABLE ACCESS FULL| TABLE_1 | 1 | 499K| 499K|00:00:00.12 | 13967 | | | |
-------------------------------------------------------------------------------------------------------------------------------
Predicate Information (identified by operation id):
---------------------------------------------------
2 - filter(("T1"."START_TIME">=SYSDATE@!-INTERVAL'+17 00:00:00' DAY(2) TO SECOND(0) AND
"T1"."START_TIME"<SYSDATE@!-INTERVAL'+16 00:00:00' DAY(2) TO SECOND(0)))
4 - filter(SYSDATE@!-INTERVAL'+17 00:00:00' DAY(2) TO SECOND(0)<SYSDATE@!-INTERVAL'+16 00:00:00' DAY(2) TO
SECOND(0))
如您所见，我在start_time上添加了一个索引，自联接查询可从中受益，但估计与实际情况不符。 Analytic Query仅决定它与索引无关。 任何想法，参考点或帮助将不胜感激。 预先感谢大家。
1 个解决方案
解决方案1
1 已采纳 2016-04-27 08:29:48
目前尚不清楚为什么仅在今天和昨天（或上周）的行完全相同的情况下才加入，但是如果您只想在特定时间之间存在行，则可以消除所有自联接并执行以下操作：
SELECT order_line,
zone,
network,
sum(
CASE WHEN SYSDATE - INTERVAL '12' HOUR <= start_time
AND start_time < SYSDATE - INTERVAL '1' HOUR
THEN success
END
) AS total_successes_today,
sum(
CASE WHEN SYSDATE - INTERVAL '12' HOUR <= start_time
AND start_time < SYSDATE - INTERVAL '1' HOUR
THEN error
END
) AS total_errors_today,
sum(
CASE WHEN SYSDATE - INTERVAL '36' HOUR <= start_time
AND start_time < SYSDATE - INTERVAL '25' HOUR
THEN success
END
) AS total_successes_yesterday,
sum(
CASE WHEN SYSDATE - INTERVAL '180' HOUR <= start_time
AND start_time < SYSDATE - INTERVAL '169' HOUR
THEN success
END
) AS total_successes_last_week
FROM table_1
WHERE ( SYSDATE - INTERVAL '12' HOUR <= start_time
AND start_time < SYSDATE - INTERVAL '1' HOUR ) -- today
OR ( SYSDATE - INTERVAL '36' HOUR <= start_time
AND start_time < SYSDATE - INTERVAL '25' HOUR ) -- yesterday = today + 24 hours
OR ( SYSDATE - INTERVAL '180' HOUR <= start_time
AND start_time < SYSDATE - INTERVAL '169' HOUR ) -- last week = today + 7*24 hours
但是，如果您确实希望保持连接的开始时间和结束时间，则可以使用分析查询：
SELECT order_line,
zone,
network,
SUM( success ),
SUM( error ),
SUM( yesterday_success ),
SUM( last_week_success )
FROM (
SELECT t.*,
SUM( success )
OVER ( PARTITION BY id,
TO_CHAR( start_time, 'HH24:MI:SS' ),
TO_CHAR( end_time, 'HH24:MI:SS' )
ORDER BY start_time
RANGE BETWEEN INTERVAL '1' DAY PRECEDING AND INTERVAL '1' DAY PRECEDING
) AS yesterday_success,
SUM( success )
OVER ( PARTITION BY id,
TO_CHAR( start_time, 'HH24:MI:SS' ),
TO_CHAR( end_time, 'HH24:MI:SS' )
ORDER BY start_time
RANGE BETWEEN INTERVAL '7' DAY PRECEDING AND INTERVAL '7' DAY PRECEDING
) AS last_week_success
FROM TABLE_1 t
)
WHERE SYSDATE - INTERVAL '12' HOUR <= start_time
AND start_time < SYSDATE - INTERVAL '1' HOUR
GROUP BY
order_line,
zone,
network
ORDER BY
order_line,
zone,
network
您可以查看是否可以通过在TO_CHAR( start_time, 'HH24:MI:SS' )和TO_CHAR( end_time, 'HH24:MI:SS' )上使用基于函数的索引来提高速度。
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