《Mysql學(xué)習(xí)MySQL中分頁優(yōu)化的實(shí)例詳解》要點(diǎn):
本文介紹了Mysql學(xué)習(xí)MySQL中分頁優(yōu)化的實(shí)例詳解,希望對您有用。如果有疑問,可以聯(lián)系我們。
通常,我們會采用ORDER BY LIMIT start, offset 的方式來進(jìn)行分頁查詢.例如下面這個SQL:MYSQL教程
SELECT * FROM `t1` WHERE ftype=1 ORDER BY id DESC LIMIT 100, 10;
或者像下面這個不帶任何條件的分頁SQL:MYSQL教程
SELECT * FROM `t1` ORDER BY id DESC LIMIT 100, 10;
一般而言,分頁SQL的耗時隨著 start 值的增加而急劇增加,我們來看下面這2個不同起始值的分頁SQL執(zhí)行耗時:MYSQL教程
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,隨著分頁數(shù)量的增加,SQL查詢耗時也有數(shù)十倍增加,顯然不科學(xué).今天我們就來分析下,如何能優(yōu)化這個分頁方案. 一般滴,想要優(yōu)化分頁的終極方案就是:沒有分頁,哈哈哈~~~,不要說我講廢話,確實(shí)如此,可以把分頁算法交給Sphinx、Lucence等第三方解決方案,沒必要讓MySQL來做它不擅長的事情. 當(dāng)然了,有小伙伴說,用第三方太麻煩了,我們就想用MySQL來做這個分頁,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)行計劃等信息:MYSQL教程
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,雖然通過主鍵索引進(jìn)行掃描了,但第二個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. 針對這種情況,我們的優(yōu)化思路就比較清晰了,有兩點(diǎn):MYSQL教程
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MYSQL教程
據(jù)此,我們有兩種相應(yīng)的改寫方法:子查詢、表連接,即下面這樣的:MYSQL教程
#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,比原來的值加了10,即935510,否則結(jié)果將和原來的不一致
MYSQL教程
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
然后我們來對比下這2個優(yōu)化后的新SQL執(zhí)行時間:MYSQL教程
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)果來看,相比原來的那個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)果來看,相比原來的那個SQL快了:30.8%
我們再來看一個不帶過濾條件的分頁SQL對比:MYSQL教程
#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)果來看,相比原來的那個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)果來看,相比原來的那個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,這個方法也同樣適用于較小的分頁,雖然LIMIT開始的 start 位置小了很多,SQL執(zhí)行時間也快了很多,但采用這種方法后,帶WHERE條件的分頁分別能提高查詢效率:24.9%、156.5%,不帶WHERE條件的分頁分別提高查詢效率:554.5%、11.7%,各位可以自行進(jìn)行測試驗(yàn)證.單從提升比例說,還是挺可觀的,確保這些優(yōu)化方法可以適用于各種分頁模式,就可以從一開始就是用. 我們來看下各種場景相應(yīng)的提升比例是多少:
MYSQL教程
MYSQL教程
結(jié)論:這樣看就和明顯了,尤其是針對大分頁的情況,因此我們優(yōu)先推薦使用INNER JOIN方式優(yōu)化分頁算法.MYSQL教程
上述每次測試都重啟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)過預(yù)熱后,查詢效率會一定程度提升,但但上述相應(yīng)的效率提升比例還是基本一致的.
MYSQL教程
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