10 個提高效率的Linux小技巧
一、LIMIT 語句
分頁查詢是最經常使用的場景之一，但也一般也是最容易出問題的地方。好比對於下面簡單的語句，通常 DBA 想到的辦法是在 type, name, create_time 字段上加組合索引。這樣條件排序都能有效的利用到索引，性能迅速提高。前端
SELECT *
FROM operation
WHERE type = 'SQLStats'
AND name = 'SlowLog'
ORDER BY create_time
LIMIT 1000, 10;
好吧，可能 90% 以上的 DBA 解決該問題就到此爲止。但當 LIMIT 子句變成 「LIMIT 1000000,10」 時，程序員仍然會抱怨：我只取 10 條記錄爲何仍是慢？mysql
要知道數據庫也並不知道第 1000000 條記錄從什麼地方開始，即便有索引也須要從頭計算一次。出現這種性能問題，多數情形下是程序員偷懶了。程序員
在前端數據瀏覽翻頁，或者大數據分批導出等場景下，是能夠將上一頁的最大值當成參數做爲查詢條件的。SQL 從新設計以下：面試
SELECT * FROM operation WHERE type = 'SQLStats' AND name = 'SlowLog' AND create_time > '2017-03-16 14:00:00' ORDER BY create_time limit 10;
在新設計下查詢時間基本固定，不會隨着數據量的增加而發生變化。算法
二、隱式轉換
SQL 語句中查詢變量和字段定義類型不匹配是另外一個常見的錯誤。好比下面的語句：sql
mysql> explain extended SELECT *
> FROM my_balance b
> WHERE b.bpn = 14000000123
> AND b.isverified IS NULL ;
mysql> show warnings;
| Warning | 1739 | Cannot use ref access on index 'bpn' due to type or collation conversion on field 'bpn'
其中字段 bpn 的定義爲 varchar(20)，MySQL 的策略是將字符串轉換爲數字以後再比較。函數做用於表字段，索引失效。數據庫
上述狀況多是應用程序框架自動填入的參數，而不是程序員的原意。如今應用框架不少很繁雜，使用方便的同時也當心它可能給本身挖坑。app
三、關聯更新、刪除
雖然 MySQL5.6 引入了物化特性，但須要特別注意它目前僅僅針對查詢語句的優化。對於更新或刪除須要手工重寫成 JOIN。框架
好比下面 UPDATE 語句，MySQL 實際執行的是循環 / 嵌套子查詢（DEPENDENT SUBQUERY)，其執行時間可想而知。函數
UPDATE operation o
SET status = 'applying'
WHERE o.id IN (SELECT id
FROM (SELECT o.id,
o.status
FROM operation o
WHERE o.group = 123
AND o.status NOT IN ( 'done' )
ORDER BY o.parent,
o.id
LIMIT 1) t);
執行計劃：
+----+--------------------+-------+-------+---------------+---------+---------+-------+------+-----------------------------------------------------+ | id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra | +----+--------------------+-------+-------+---------------+---------+---------+-------+------+-----------------------------------------------------+ | 1 | PRIMARY | o | index | | PRIMARY | 8 | | 24 | Using where; Using temporary | | 2 | DEPENDENT SUBQUERY | | | | | | | | Impossible WHERE noticed after reading const tables | | 3 | DERIVED | o | ref | idx_2,idx_5 | idx_5 | 8 | const | 1 | Using where; Using filesort | +----+--------------------+-------+-------+---------------+---------+---------+-------+------+-----------------------------------------------------+
重寫爲 JOIN 以後，子查詢的選擇模式從 DEPENDENT SUBQUERY 變成 DERIVED，執行速度大大加快，從 7 秒下降到 2 毫秒
UPDATE operation o
JOIN (SELECT o.id,
o.status
FROM operation o
WHERE o.group = 123
AND o.status NOT IN ( 'done' )
ORDER BY o.parent,
o.id
LIMIT 1) t
ON o.id = t.id
SET status = 'applying'
執行計劃簡化爲：
+----+-------------+-------+------+---------------+-------+---------+-------+------+-----------------------------------------------------+ | id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra | +----+-------------+-------+------+---------------+-------+---------+-------+------+-----------------------------------------------------+ | 1 | PRIMARY | | | | | | | | Impossible WHERE noticed after reading const tables | | 2 | DERIVED | o | ref | idx_2,idx_5 | idx_5 | 8 | const | 1 | Using where; Using filesort | +----+-------------+-------+------+---------------+-------+---------+-------+------+-----------------------------------------------------+
四、混合排序
MySQL 不能利用索引進行混合排序。但在某些場景，仍是有機會使用特殊方法提高性能的。
SELECT *
FROM my_order o
INNER JOIN my_appraise a ON a.orderid = o.id
ORDER BY a.is_reply ASC,
a.appraise_time DESC
LIMIT 0, 20
執行計劃顯示爲全表掃描：
+----+-------------+-------+--------+-------------+---------+---------+---------------+---------+-+ | id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra +----+-------------+-------+--------+-------------+---------+---------+---------------+---------+-+ | 1 | SIMPLE | a | ALL | idx_orderid | NULL | NULL | NULL | 1967647 | Using filesort | | 1 | SIMPLE | o | eq_ref | PRIMARY | PRIMARY | 122 | a.orderid | 1 | NULL | +----+-------------+-------+--------+---------+---------+---------+-----------------+---------+-+
因爲 is_reply 只有 0 和 1 兩種狀態，咱們按照下面的方法重寫後，執行時間從 1.58 秒下降到 2 毫秒。
SELECT *
FROM ((SELECT *
FROM my_order o
INNER JOIN my_appraise a
ON a.orderid = o.id
AND is_reply = 0
ORDER BY appraise_time DESC
LIMIT 0, 20)
UNION ALL
(SELECT *
FROM my_order o
INNER JOIN my_appraise a
ON a.orderid = o.id
AND is_reply = 1
ORDER BY appraise_time DESC
LIMIT 0, 20)) t
ORDER BY is_reply ASC,
appraisetime DESC
LIMIT 20;
五、EXISTS語句
MySQL 對待 EXISTS 子句時，仍然採用嵌套子查詢的執行方式。以下面的 SQL 語句：
SELECT *
FROM my_neighbor n
LEFT JOIN my_neighbor_apply sra
ON n.id = sra.neighbor_id
AND sra.user_id = 'xxx'
WHERE n.topic_status < 4
AND EXISTS(SELECT 1
FROM message_info m
WHERE n.id = m.neighbor_id
AND m.inuser = 'xxx')
AND n.topic_type <> 5
執行計劃爲：
+----+--------------------+-------+------+-----+------------------------------------------+---------+-------+---------+ -----+ | id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra | +----+--------------------+-------+------+ -----+------------------------------------------+---------+-------+---------+ -----+ | 1 | PRIMARY | n | ALL | | NULL | NULL | NULL | 1086041 | Using where | | 1 | PRIMARY | sra | ref | | idx_user_id | 123 | const | 1 | Using where | | 2 | DEPENDENT SUBQUERY | m | ref | | idx_message_info | 122 | const | 1 | Using index condition; Using where | +----+--------------------+-------+------+ -----+------------------------------------------+---------+-------+---------+ -----+
去掉 exists 更改成 join，可以避免嵌套子查詢，將執行時間從 1.93 秒下降爲 1 毫秒。
SELECT *
FROM my_neighbor n
INNER JOIN message_info m
ON n.id = m.neighbor_id
AND m.inuser = 'xxx'
LEFT JOIN my_neighbor_apply sra
ON n.id = sra.neighbor_id
AND sra.user_id = 'xxx'
WHERE n.topic_status < 4
AND n.topic_type <> 5
新的執行計劃：
+----+-------------+-------+--------+ -----+------------------------------------------+---------+ -----+------+ -----+ | id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra | +----+-------------+-------+--------+ -----+------------------------------------------+---------+ -----+------+ -----+ | 1 | SIMPLE | m | ref | | idx_message_info | 122 | const | 1 | Using index condition | | 1 | SIMPLE | n | eq_ref | | PRIMARY | 122 | ighbor_id | 1 | Using where | | 1 | SIMPLE | sra | ref | | idx_user_id | 123 | const | 1 | Using where | +----+-------------+-------+--------+ -----+------------------------------------------+---------+ -----+------+ -----+
六、條件下推
外部查詢條件不可以下推到複雜的視圖或子查詢的狀況有：
聚合子查詢；
含有 LIMIT 的子查詢；
UNION 或 UNION ALL 子查詢；
輸出字段中的子查詢；
以下面的語句，從執行計劃能夠看出其條件做用於聚合子查詢以後
SELECT *
FROM (SELECT target,
Count(*)
FROM operation
GROUP BY target) t
WHERE target = 'rm-xxxx'
+----+-------------+------------+-------+---------------+-------------+---------+-------+------+-------------+ | id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra | +----+-------------+------------+-------+---------------+-------------+---------+-------+------+-------------+ | 1 | PRIMARY | <derived2> | ref | <auto_key0> | <auto_key0> | 514 | const | 2 | Using where | | 2 | DERIVED | operation | index | idx_4 | idx_4 | 519 | NULL | 20 | Using index | +----+-------------+------------+-------+---------------+-------------+---------+-------+------+-------------+
肯定從語義上查詢條件能夠直接下推後，重寫以下：
SELECT target,
Count(*)
FROM operation
WHERE target = 'rm-xxxx'
GROUP BY target
執行計劃變爲：
+----+-------------+-----------+------+---------------+-------+---------+-------+------+--------------------+ | id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra | +----+-------------+-----------+------+---------------+-------+---------+-------+------+--------------------+ | 1 | SIMPLE | operation | ref | idx_4 | idx_4 | 514 | const | 1 | Using where; Using index | +----+-------------+-----------+------+---------------+-------+---------+-------+------+--------------------+
七、提早縮小範圍
先上初始 SQL 語句：
SELECT *
FROM my_order o
LEFT JOIN my_userinfo u
ON o.uid = u.uid
LEFT JOIN my_productinfo p
ON o.pid = p.pid
WHERE ( o.display = 0 )
AND ( o.ostaus = 1 )
ORDER BY o.selltime DESC
LIMIT 0, 15
該 SQL 語句原意是：先作一系列的左鏈接，而後排序取前 15 條記錄。從執行計劃也能夠看出，最後一步估算排序記錄數爲 90 萬，時間消耗爲 12 秒。
+----+-------------+-------+--------+---------------+---------+---------+-----------------+--------+----------------------------------------------------+ | id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra | +----+-------------+-------+--------+---------------+---------+---------+-----------------+--------+----------------------------------------------------+ | 1 | SIMPLE | o | ALL | NULL | NULL | NULL | NULL | 909119 | Using where; Using temporary; Using filesort | | 1 | SIMPLE | u | eq_ref | PRIMARY | PRIMARY | 4 | o.uid | 1 | NULL | | 1 | SIMPLE | p | ALL | PRIMARY | NULL | NULL | NULL | 6 | Using where; Using join buffer (Block Nested Loop) | +----+-------------+-------+--------+---------------+---------+---------+-----------------+--------+----------------------------------------------------+
因爲最後 WHERE 條件以及排序均針對最左主表，所以能夠先對 my_order 排序提早縮小數據量再作左鏈接。SQL 重寫後以下，執行時間縮小爲 1 毫秒左右。
SELECT *
FROM (
SELECT *
FROM my_order o
WHERE ( o.display = 0 )
AND ( o.ostaus = 1 )
ORDER BY o.selltime DESC
LIMIT 0, 15
) o
LEFT JOIN my_userinfo u
ON o.uid = u.uid
LEFT JOIN my_productinfo p
ON o.pid = p.pid
ORDER BY o.selltime DESC
limit 0, 15
再檢查執行計劃：子查詢物化後（select_type=DERIVED) 參與 JOIN。雖然估算行掃描仍然爲 90 萬，可是利用了索引以及 LIMIT 子句後，實際執行時間變得很小。
+----+-------------+------------+--------+---------------+---------+---------+-------+--------+----------------------------------------------------+ | id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra | +----+-------------+------------+--------+---------------+---------+---------+-------+--------+----------------------------------------------------+ | 1 | PRIMARY | <derived2> | ALL | NULL | NULL | NULL | NULL | 15 | Using temporary; Using filesort | | 1 | PRIMARY | u | eq_ref | PRIMARY | PRIMARY | 4 | o.uid | 1 | NULL | | 1 | PRIMARY | p | ALL | PRIMARY | NULL | NULL | NULL | 6 | Using where; Using join buffer (Block Nested Loop) | | 2 | DERIVED | o | index | NULL | idx_1 | 5 | NULL | 909112 | Using where | +----+-------------+------------+--------+---------------+---------+---------+-------+--------+----------------------------------------------------+
八、中間結果集下推
再來看下面這個已經初步優化過的例子 (左鏈接中的主表優先做用查詢條件)：
SELECT a.*,
c.allocated
FROM (
SELECT resourceid
FROM my_distribute d
WHERE isdelete = 0
AND cusmanagercode = '1234567'
ORDER BY salecode limit 20) a
LEFT JOIN
(
SELECT resourcesid， sum(ifnull(allocation, 0) * 12345) allocated
FROM my_resources
GROUP BY resourcesid) c
ON a.resourceid = c.resourcesid
那麼該語句還存在其它問題嗎？不難看出子查詢 c 是全表聚合查詢，在表數量特別大的狀況下會致使整個語句的性能降低。
其實對於子查詢 c，左鏈接最後結果集只關心能和主表 resourceid 能匹配的數據。所以咱們能夠重寫語句以下，執行時間從原來的 2 秒降低到 2 毫秒。
SELECT a.*,
c.allocated
FROM (
SELECT resourceid
FROM my_distribute d
WHERE isdelete = 0
AND cusmanagercode = '1234567'
ORDER BY salecode limit 20) a
LEFT JOIN
(
SELECT resourcesid， sum(ifnull(allocation, 0) * 12345) allocated
FROM my_resources r,
(
SELECT resourceid
FROM my_distribute d
WHERE isdelete = 0
AND cusmanagercode = '1234567'
ORDER BY salecode limit 20) a
WHERE r.resourcesid = a.resourcesid
GROUP BY resourcesid) c
ON a.resourceid = c.resourcesid
可是子查詢 a 在咱們的 SQL 語句中出現了屢次。這種寫法不只存在額外的開銷，還使得整個語句顯的繁雜。使用 WITH 語句再次重寫：
WITH a AS
(
SELECT resourceid
FROM my_distribute d
WHERE isdelete = 0
AND cusmanagercode = '1234567'
ORDER BY salecode limit 20)
SELECT a.*,
c.allocated
FROM a
LEFT JOIN
(
SELECT resourcesid， sum(ifnull(allocation, 0) * 12345) allocated
FROM my_resources r,
a
WHERE r.resourcesid = a.resourcesid
GROUP BY resourcesid) c
ON a.resourceid = c.resourcesid
數據庫編譯器產生執行計劃，決定着 SQL 的實際執行方式。可是編譯器只是盡力服務，全部數據庫的編譯器都不是盡善盡美的。
上述提到的多數場景，在其它數據庫中也存在性能問題。瞭解數據庫編譯器的特性，才能避規其短處，寫出高性能的 SQL 語句。
程序員在設計數據模型以及編寫 SQL 語句時，要把算法的思想或意識帶進來。
編寫複雜 SQL 語句要養成使用 WITH 語句的習慣。簡潔且思路清晰的 SQL 語句也能減少數據庫的負擔 。
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