本文介绍了一种高性能的每组最大值SQL查询方法的处理方法,对大家解决问题具有一定的参考价值,需要的朋友们下面随着小编来一起学习吧!
问题描述
我正在尝试构建一个基础结构,用于按需快速运行回归,从包含我们的Web服务器上所有历史活动的数据库中提取Apache请求。为了通过确保我们仍然递减来自较小客户端的请求来提高覆盖率,我希望通过为每个客户端检索至多n个(对于这个问题,假设10个)请求来确保请求的分布。 我在这里找到了许多类似问题的答案,其中最接近的似乎是SQL query to return top N rows per ID across a range of IDs,但答案大多是与性能无关的解决方案 我已经试过了。例如,ROW_NUMBER()分析函数为我们提供了所需的数据:
SELECT
*
FROM
(
SELECT
dailylogdata.*,
row_number() over (partition by dailylogdata.contextid order by occurrencedate) rn
FROM
dailylogdata
WHERE
shorturl in (?)
)
WHERE
rn <= 10;
但是,假设该表包含给定一天的数百万个条目,并且这种方法需要从索引中读取与我们的选择标准匹配的所有行,以便应用ROW_NUMBER分析函数,则性能非常糟糕。我们最终选择了近一百万行,却因为它们的row_number超过10而丢弃了其中的绝大多数。
|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
|| Id | Operation | Name | Starts | E-Rows | A-Rows | A-Time | Buffers | Reads | Writes | OMem | 1Mem | Used-Mem | Used-Tmp||
|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
|| 0 | SELECT STATEMENT | | 1 | | 12222 |00:09:08.94 | 895K| 584K| 301 | | | | ||
||* 1 | VIEW | | 1 | 4427K| 12222 |00:09:08.94 | 895K| 584K| 301 | | | | ||
||* 2 | WINDOW SORT PUSHED RANK | | 1 | 4427K| 13536 |00:09:08.94 | 895K| 584K| 301 | 2709K| 743K| 97M (1)| 4096 ||
|| 3 | PARTITION RANGE SINGLE | | 1 | 4427K| 932K|00:22:27.90 | 895K| 584K| 0 | | | | ||
|| 4 | TABLE ACCESS BY LOCAL INDEX ROWID| DAILYLOGDATA | 1 | 4427K| 932K|00:22:27.61 | 895K| 584K| 0 | | | | ||
||* 5 | INDEX RANGE SCAN | DAILYLOGDATA_URLCONTEXT | 1 | 17345 | 932K|00:00:00.75 | 1448 | 0 | 0 | | | | ||
|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| |
|Predicate Information (identified by operation id): |
|--------------------------------------------------- |
| |
| 1 - filter("RN"<=:SYS_B_2) |
| 2 - filter(ROW_NUMBER() OVER ( PARTITION BY "DAILYLOGDATA"."CONTEXTID" ORDER BY "OCCURRENCEDATE")<=:SYS_B_2) |
| 5 - access("SHORTURL"=:P1) |
| |
+---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
但是,如果我们只查询特定上下文ID的前10个结果,则可以大大加快执行速度:
SELECT
*
FROM
(
SELECT
dailylogdata.*
FROM
dailylogdata
WHERE
shorturl in (?)
and contextid = ?
)
WHERE
rownum <= 10;
运行此查询的统计信息:
|-------------------------------------------------------------------------------------------------------------------------|
|| Id | Operation | Name | Starts | E-Rows | A-Rows | A-Time | Buffers ||
|-------------------------------------------------------------------------------------------------------------------------|
|| 0 | SELECT STATEMENT | | 1 | | 10 |00:00:00.01 | 14 ||
||* 1 | COUNT STOPKEY | | 1 | | 10 |00:00:00.01 | 14 ||
|| 2 | PARTITION RANGE SINGLE | | 1 | 10 | 10 |00:00:00.01 | 14 ||
|| 3 | TABLE ACCESS BY LOCAL INDEX ROWID| DAILYLOGDATA | 1 | 10 | 10 |00:00:00.01 | 14 ||
||* 4 | INDEX RANGE SCAN | DAILYLOGDATA_URLCONTEXT | 1 | 1 | 10 |00:00:00.01 | 5 ||
|-------------------------------------------------------------------------------------------------------------------------|
| |
|Predicate Information (identified by operation id): |
|--------------------------------------------------- |
| |
| 1 - filter(ROWNUM<=10) |
| 4 - access("SHORTURL"=:P1 AND "CONTEXTID"=TO_NUMBER(:P2)) |
| |
+-------------------------------------------------------------------------------------------------------------------------+
在本例中,Oracle足够聪明,可以在获得10个结果后停止检索数据。我可以收集一组完整的上下文ID并以编程方式生成一个查询,该查询由每个上下文ID的一个查询实例和union all
整个查询组成,但是考虑到上下文ID的绝对数量,我们可能会遇到Oracle内部的限制,即使不是这样,这种方法也充满了笨拙的味道。
有没有人知道有一种方法可以保持第一个查询的简单性,同时保持与第二个查询相称的性能?还要注意,我实际上并不关心检索一组稳定的行;只要它们满足我的标准,它们就可以用于回归。
编辑:Adam Musch的建议奏效了。我在这里附加了他的更改的性能结果,因为我无法将它们放在对他的答案的评论回应中。这次我还使用了一个更大的数据集进行测试,以下是来自我最初的ROW_NUMBER方法的(缓存)统计数据以供比较:
|-------------------------------------------------------------------------------------------------------------------------------------------------|
|| Id | Operation | Name | Starts | E-Rows | A-Rows | A-Time | Buffers | Reads | OMem | 1Mem | Used-Mem ||
|-------------------------------------------------------------------------------------------------------------------------------------------------|
|| 0 | SELECT STATEMENT | | 1 | | 12624 |00:00:22.34 | 1186K| 931K| | | ||
||* 1 | VIEW | | 1 | 1163K| 12624 |00:00:22.34 | 1186K| 931K| | | ||
||* 2 | WINDOW NOSORT | | 1 | 1163K| 1213K|00:00:21.82 | 1186K| 931K| 3036M| 17M| ||
|| 3 | TABLE ACCESS BY INDEX ROWID| TWTEST | 1 | 1163K| 1213K|00:00:20.41 | 1186K| 931K| | | ||
||* 4 | INDEX RANGE SCAN | TWTEST_URLCONTEXT | 1 | 1163K| 1213K|00:00:00.81 | 8568 | 0 | | | ||
|-------------------------------------------------------------------------------------------------------------------------------------------------|
| |
|Predicate Information (identified by operation id): |
|--------------------------------------------------- |
| |
| 1 - filter("RN"<=10) |
| 2 - filter(ROW_NUMBER() OVER ( PARTITION BY "CONTEXTID" ORDER BY NULL )<=10) |
| 4 - access("SHORTURL"=:P1) |
+-------------------------------------------------------------------------------------------------------------------------------------------------+
我冒昧地略微简化了Adam的建议;以下是修改后的查询...
select
*
from
twtest
where
rowid in (
select
rowid
from (
select
rowid,
shorturl,
row_number() over (partition by shorturl, contextid
order by null) rn
from
twtest
)
where rn <= 10
and shorturl in (?)
);
...及其(缓存)评估的统计信息:
|--------------------------------------------------------------------------------------------------------------------------------------|
|| Id | Operation | Name | Starts | E-Rows | A-Rows | A-Time | Buffers | OMem | 1Mem | Used-Mem ||
|--------------------------------------------------------------------------------------------------------------------------------------|
|| 0 | SELECT STATEMENT | | 1 | | 12624 |00:00:01.33 | 19391 | | | ||
|| 1 | NESTED LOOPS | | 1 | 1 | 12624 |00:00:01.33 | 19391 | | | ||
|| 2 | VIEW | VW_NSO_1 | 1 | 1163K| 12624 |00:00:01.27 | 6770 | | | ||
|| 3 | HASH UNIQUE | | 1 | 1 | 12624 |00:00:01.27 | 6770 | 1377K| 1377K| 5065K (0)||
||* 4 | VIEW | | 1 | 1163K| 12624 |00:00:01.25 | 6770 | | | ||
||* 5 | WINDOW NOSORT | | 1 | 1163K| 1213K|00:00:01.09 | 6770 | 283M| 5598K| ||
||* 6 | INDEX RANGE SCAN | TWTEST_URLCONTEXT | 1 | 1163K| 1213K|00:00:00.40 | 6770 | | | ||
|| 7 | TABLE ACCESS BY USER ROWID| TWTEST | 12624 | 1 | 12624 |00:00:00.04 | 12621 | | | ||
|--------------------------------------------------------------------------------------------------------------------------------------|
| |
|Predicate Information (identified by operation id): |
|--------------------------------------------------- |
| |
| 4 - filter("RN"<=10) |
| 5 - filter(ROW_NUMBER() OVER ( PARTITION BY "SHORTURL","CONTEXTID" ORDER BY NULL NULL )<=10) |
| 6 - access("SHORTURL"=:P1) |
| |
|Note |
|----- |
| - dynamic sampling used for this statement (level=2) |
| |
+--------------------------------------------------------------------------------------------------------------------------------------+
正如所宣传的,我们只访问经过完全筛选的行的dailylogdata表。我担心似乎仍在根据它声称正在选择的行数(1213K)对urlContext索引进行完全扫描,但考虑到它只使用6770个缓冲区(即使我增加了上下文特定结果的数量,这个数字也保持不变),这可能具有误导性。
推荐答案
这是一个不太好的解决方案,但似乎做了您想做的事情:尽快缩短索引扫描,并在通过筛选条件和top-n查询条件限定数据之前不读取数据。
请注意,测试时使用的是shorturl =
条件,而不是shorturl IN
条件。
with rowid_list as
(select rowid
from (select *
from (select rowid,
row_number() over (partition by shorturl, contextid
order by null) rn
from dailylogdata
)
where rn <= 10
)
where shorturl = ?
)
select *
from dailylogdata
where rowid in (select rowid from rowid_list)
with
子句获取前10个ROID,为满足您的条件的shorturl
和contextid
的每个唯一组合筛选一个窗口NOSORT。然后,它循环遍历这组roid,按rowid获取每个roid。
----------------------------------------------------------------------------------------------------
| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time |
----------------------------------------------------------------------------------------------------
| 0 | SELECT STATEMENT | | 1 | 286 | 1536 (1)| 00:00:19 |
| 1 | NESTED LOOPS | | 1 | 286 | 1536 (1)| 00:00:19 |
| 2 | VIEW | VW_NSO_1 | 136K| 1596K| 910 (1)| 00:00:11 |
| 3 | HASH UNIQUE | | 1 | 3326K| | |
|* 4 | VIEW | | 136K| 3326K| 910 (1)| 00:00:11 |
|* 5 | WINDOW NOSORT | | 136K| 2794K| 910 (1)| 00:00:11 |
|* 6 | INDEX RANGE SCAN | TABLE_REDACTED_INDEX | 136K| 2794K| 910 (1)| 00:00:11 |
| 7 | TABLE ACCESS BY USER ROWID| TABLE_REDACTED | 1 | 274 | 1 (0)| 00:00:01 |
----------------------------------------------------------------------------------------------------
Predicate Information (identified by operation id):
---------------------------------------------------
4 - filter("RN"<=10)
5 - filter(ROW_NUMBER() OVER ( PARTITION BY "CLIENT_ID","SCE_ID" ORDER BY NULL NULL
)<=10)
6 - access("TABLE_REDACTED"."SHORTURL"=:b1)
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