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MySQL優(yōu)化案例系列-mysql分頁(yè)優(yōu)化

 更新時(shí)間:2016年08月31日 11:54:52   投稿:mdxy-dxy  
這篇文章主要介紹了MySQL優(yōu)化案例系列-mysql分頁(yè)優(yōu)化,需要的朋友可以參考下

通常,我們會(huì)采用ORDER BY LIMIT start, offset 的方式來(lái)進(jìn)行分頁(yè)查詢。例如下面這個(gè)SQL:

SELECT * FROM `t1` WHERE ftype=1 ORDER BY id DESC LIMIT 100, 10;

或者像下面這個(gè)不帶任何條件的分頁(yè)SQL:

SELECT * FROM `t1` ORDER BY id DESC LIMIT 100, 10;

一般而言,分頁(yè)SQL的耗時(shí)隨著 start 值的增加而急劇增加,我們來(lái)看下面這2個(gè)不同起始值的分頁(yè)SQL執(zhí)行耗時(shí):

yejr@imysql.com> SELECT * FROM `t1` WHERE ftype=1 ORDER BY id DESC LIMIT 500, 10;
…
10 rows in set (0.05 sec)
yejr@imysql.com> SELECT * FROM `t1` WHERE ftype=6 ORDER BY id DESC LIMIT 935500, 10;
…
10 rows in set (2.39 sec)

可以看到,隨著分頁(yè)數(shù)量的增加,SQL查詢耗時(shí)也有數(shù)十倍增加,顯然不科學(xué)。今天我們就來(lái)分析下,如何能優(yōu)化這個(gè)分頁(yè)方案。 一般滴,想要優(yōu)化分頁(yè)的終極方案就是:沒(méi)有分頁(yè),哈哈哈~~~,不要說(shuō)我講廢話,確實(shí)如此,可以把分頁(yè)算法交給Sphinx、Lucence等第三方解決方案,沒(méi)必要讓MySQL來(lái)做它不擅長(zhǎng)的事情。 當(dāng)然了,有小伙伴說(shuō),用第三方太麻煩了,我們就想用MySQL來(lái)做這個(gè)分頁(yè),咋辦呢?莫急,且待我們慢慢分析,先看下表DDL、數(shù)據(jù)量、查詢SQL的執(zhí)行計(jì)劃等信息:

yejr@imysql.com> SHOW CREATE TABLE `t1`;
CREATE TABLE `t1` (
 `id` int(10) unsigned NOT NULL AUTO_INCREMENT,
...
 `ftype` tinyint(3) unsigned NOT NULL,
...
 PRIMARY KEY (`id`)
) ENGINE=InnoDB DEFAULT CHARSET=utf8;

yejr@imysql.com> select count(*) from t1;
+----------+
| count(*) |
+----------+
| 994584 |
+----------+

yejr@imysql.com> EXPLAIN SELECT * FROM `t1` WHERE ftype=1 ORDER BY id DESC LIMIT 500, 10\G
*************************** 1. row ***************************
 id: 1
 select_type: SIMPLE
 table: t1
 type: index
possible_keys: NULL
 key: PRIMARY
 key_len: 4
 ref: NULL
 rows: 510
 Extra: Using where

yejr@imysql.com> EXPLAIN SELECT * FROM `t1` WHERE ftype=1 ORDER BY id DESC LIMIT 935500, 10\G
*************************** 1. row ***************************
 id: 1
 select_type: SIMPLE
 table: t1
 type: index
possible_keys: NULL
 key: PRIMARY
 key_len: 4
 ref: NULL
 rows: 935510
 Extra: Using where

可以看到,雖然通過(guò)主鍵索引進(jìn)行掃描了,但第二個(gè)SQL需要掃描的記錄數(shù)太大了,而且需要先掃描約935510條記錄,然后再根據(jù)排序結(jié)果取10條記錄,這肯定是非常慢了。 針對(duì)這種情況,我們的優(yōu)化思路就比較清晰了,有兩點(diǎn):

1、盡可能從索引中直接獲取數(shù)據(jù),避免或減少直接掃描行數(shù)據(jù)的頻率
2、盡可能減少掃描的記錄數(shù),也就是先確定起始的范圍,再往后取N條記錄即可

據(jù)此,我們有兩種相應(yīng)的改寫(xiě)方法:子查詢、表連接,即下面這樣的:

#采用子查詢的方式優(yōu)化,在子查詢里先從索引獲取到最大id,然后倒序排,再取10行結(jié)果集
#注意這里采用了2次倒序排,因此在取LIMIT的start值時(shí),比原來(lái)的值加了10,即935510,否則結(jié)果將和原來(lái)的不一致

yejr@imysql.com> EXPLAIN SELECT * FROM (SELECT * FROM `t1` WHERE id > ( SELECT id FROM `t1` WHERE ftype=1 ORDER BY id DESC LIMIT 935510, 1) LIMIT 10) t ORDER BY id DESC\G
*************************** 1. row ***************************
 id: 1
 select_type: PRIMARY
 table: <derived2>
 type: ALL
possible_keys: NULL
 key: NULL
 key_len: NULL
 ref: NULL
 rows: 10
 Extra: Using filesort
*************************** 2. row ***************************
 id: 2
 select_type: DERIVED
 table: t1
 type: ALL
possible_keys: PRIMARY
 key: NULL
 key_len: NULL
 ref: NULL
 rows: 973192
 Extra: Using where
*************************** 3. row ***************************
 id: 3
 select_type: SUBQUERY
 table: t1
 type: index
possible_keys: NULL
 key: PRIMARY
 key_len: 4
 ref: NULL
 rows: 935511
 Extra: Using where

#采用INNER JOIN優(yōu)化,JOIN子句里也優(yōu)先從索引獲取ID列表,然后直接關(guān)聯(lián)查詢獲得最終結(jié)果,這里不需要加10
yejr@imysql.com> EXPLAIN SELECT * FROM `t1` INNER JOIN ( SELECT id FROM `t1` WHERE ftype=1 ORDER BY id DESC LIMIT 935500,10) t2 USING (id)\G
*************************** 1. row ***************************
 id: 1
 select_type: PRIMARY
 table: <derived2>
 type: ALL
possible_keys: NULL
 key: NULL
 key_len: NULL
 ref: NULL
 rows: 935510
 Extra: NULL
*************************** 2. row ***************************
 id: 1
 select_type: PRIMARY
 table: t1
 type: eq_ref
possible_keys: PRIMARY
 key: PRIMARY
 key_len: 4
 ref: t2.id
 rows: 1
 Extra: NULL
*************************** 3. row ***************************
 id: 2
 select_type: DERIVED
 table: t1
 type: index
possible_keys: NULL
 key: PRIMARY
 key_len: 4
 ref: NULL
 rows: 973192
 Extra: Using where

然后我們來(lái)對(duì)比下這2個(gè)優(yōu)化后的新SQL執(zhí)行時(shí)間:

yejr@imysql.com> SELECT * FROM (SELECT * FROM `t1` WHERE id > ( SELECT id FROM `t1` WHERE ftype=1 ORDER BY id DESC LIMIT 935510, 1) LIMIT 10) T ORDER BY id DESC;
...
rows in set (1.86 sec)
#采用子查詢優(yōu)化,從profiling的結(jié)果來(lái)看,相比原來(lái)的那個(gè)SQL快了:28.2%

yejr@imysql.com> SELECT * FROM `t1` INNER JOIN ( SELECT id FROM `t1` WHERE ftype=1 ORDER BY id DESC LIMIT 935500,10) t2 USING (id);
...
10 rows in set (1.83 sec)
#采用INNER JOIN優(yōu)化,從profiling的結(jié)果來(lái)看,相比原來(lái)的那個(gè)SQL快了:30.8%

我們?cè)賮?lái)看一個(gè)不帶過(guò)濾條件的分頁(yè)SQL對(duì)比:

#原始SQL
yejr@imysql.com> EXPLAIN SELECT * FROM `t1` ORDER BY id DESC LIMIT 935500, 10\G
*************************** 1. row ***************************
   id: 1
 select_type: SIMPLE
  table: t1
   type: index
possible_keys: NULL
   key: PRIMARY
  key_len: 4
   ref: NULL
   rows: 935510
  Extra: NULL

yejr@imysql.com> SELECT * FROM `t1` ORDER BY id DESC LIMIT 935500, 10;
...
10 rows in set (2.22 sec)

#采用子查詢優(yōu)化
yejr@imysql.com> EXPLAIN SELECT * FROM (SELECT * FROM `t1` WHERE id > ( SELECT id FROM `t1` ORDER BY id DESC LIMIT 935510, 1) LIMIT 10) t ORDER BY id DESC;
*************************** 1. row ***************************
   id: 1
 select_type: PRIMARY
  table: <derived2>
   type: ALL
possible_keys: NULL
   key: NULL
  key_len: NULL
   ref: NULL
   rows: 10
  Extra: Using filesort
*************************** 2. row ***************************
   id: 2
 select_type: DERIVED
  table: t1
   type: ALL
possible_keys: PRIMARY
   key: NULL
  key_len: NULL
   ref: NULL
   rows: 973192
  Extra: Using where
*************************** 3. row ***************************
   id: 3
 select_type: SUBQUERY
  table: t1
   type: index
possible_keys: NULL
   key: PRIMARY
  key_len: 4
   ref: NULL
   rows: 935511
  Extra: Using index

yejr@imysql.com> SELECT * FROM (SELECT * FROM `t1` WHERE id > ( SELECT id FROM `t1` ORDER BY id DESC LIMIT 935510, 1) LIMIT 10) t ORDER BY id DESC;
…
10 rows in set (2.01 sec)
#采用子查詢優(yōu)化,從profiling的結(jié)果來(lái)看,相比原來(lái)的那個(gè)SQL快了:10.6%


#采用INNER JOIN優(yōu)化
yejr@imysql.com> EXPLAIN SELECT * FROM `t1` INNER JOIN ( SELECT id FROM `t1`ORDER BY id DESC LIMIT 935500,10) t2 USING (id)\G
*************************** 1. row ***************************
   id: 1
 select_type: PRIMARY
  table: 
   type: ALL
possible_keys: NULL
   key: NULL
  key_len: NULL
   ref: NULL
   rows: 935510
  Extra: NULL
*************************** 2. row ***************************
   id: 1
 select_type: PRIMARY
  table: t1
   type: eq_ref
possible_keys: PRIMARY
   key: PRIMARY
  key_len: 4
   ref: t1.id
   rows: 1
  Extra: NULL
*************************** 3. row ***************************
   id: 2
 select_type: DERIVED
  table: t1
   type: index
possible_keys: NULL
   key: PRIMARY
  key_len: 4
   ref: NULL
   rows: 973192
  Extra: Using index

yejr@imysql.com> SELECT * FROM `t1` INNER JOIN ( SELECT id FROM `t1`ORDER BY id DESC LIMIT 935500,10) t2 USING (id);
…
10 rows in set (1.70 sec)
#采用INNER JOIN優(yōu)化,從profiling的結(jié)果來(lái)看,相比原來(lái)的那個(gè)SQL快了:30.2%

至此,我們看到采用子查詢或者INNER JOIN進(jìn)行優(yōu)化后,都有大幅度的提升,這個(gè)方法也同樣適用于較小的分頁(yè),雖然LIMIT開(kāi)始的 start 位置小了很多,SQL執(zhí)行時(shí)間也快了很多,但采用這種方法后,帶WHERE條件的分頁(yè)分別能提高查詢效率:24.9%、156.5%,不帶WHERE條件的分頁(yè)分別提高查詢效率:554.5%、11.7%,各位可以自行進(jìn)行測(cè)試驗(yàn)證。單從提升比例說(shuō),還是挺可觀的,確保這些優(yōu)化方法可以適用于各種分頁(yè)模式,就可以從一開(kāi)始就是用。 我們來(lái)看下各種場(chǎng)景相應(yīng)的提升比例是多少:

大分頁(yè),帶WHERE 大分頁(yè),不帶WHERE 大分頁(yè)平均提升比例 小分頁(yè),帶WHERE 小分頁(yè),不帶WHERE 總體平均提升比例
子查詢優(yōu)化 28.20% 10.60% 19.40% 24.90% 554.40% 154.53%
INNER JOIN優(yōu)化 30.80% 30.20% 30.50% 156.50% 11.70% 57.30%

結(jié)論:這樣看就和明顯了,尤其是針對(duì)大分頁(yè)的情況,因此我們優(yōu)先推薦使用INNER JOIN方式優(yōu)化分頁(yè)算法。

上述每次測(cè)試都重啟mysqld實(shí)例,并且加了SQL_NO_CACHE,以保證每次都是直接數(shù)據(jù)文件或索引文件中讀取。如果數(shù)據(jù)經(jīng)過(guò)預(yù)熱后,查詢效率會(huì)一定程度提升,但但上述相應(yīng)的效率提升比例還是基本一致的。

2014/07/28后記更新:

其實(shí)如果是不帶任何條件的分頁(yè),就沒(méi)必要用這么麻煩的方法了,可以采用對(duì)主鍵采用范圍檢索的方法,例如參考這篇:Advance for MySQL Pagination

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