常見SQL錯誤用法
1. 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;
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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。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：程序員
SELECT *
FROM operation
WHERE type = 'SQLStats'
AND name = 'SlowLog'
AND create_time > '2019-10-19 14:00:00'
ORDER BY create_time limit 10;
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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
2. 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'
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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。後端
3. 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。ruby
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。性能優化
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);
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執行計劃：微信
+----+--------------------+-------+-------+---------------+---------+---------+-------+------+-----------------------------------------------------+
| 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 |
+----+--------------------+-------+-------+---------------+---------+---------+-------+------+-----------------------------------------------------+
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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'
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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 | +----+-------------+-------+------+---------------+-------+---------+-------+------+-----------------------------------------------------+ 複製代碼
4. 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
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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 |
+----+-------------+-------+--------+---------+---------+---------+-----------------+---------+-+
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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;
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5. 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
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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 |
+----+--------------------+-------+------+ -----+------------------------------------------+---------+-------+---------+ -----+
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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
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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 |
+----+-------------+-------+--------+ -----+------------------------------------------+---------+ -----+------+ -----+
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6. 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'
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+----+-------------+------------+-------+---------------+-------------+---------+-------+------+-------------+
| 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 | +----+-------------+------------+-------+---------------+-------------+---------+-------+------+-------------+ 複製代碼
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
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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 |
+----+-------------+-----------+------+---------------+-------+---------+-------+------+--------------------+
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關於MySQL外部條件不能下推的詳細解釋說明請參考之前文章：MySQL · 性能優化 · 條件下推到物化表
7. 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
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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) |
+----+-------------+-------+--------+---------------+---------+---------+-----------------+--------+----------------------------------------------------+
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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
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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 | +----+-------------+------------+--------+---------------+---------+---------+-------+--------+----------------------------------------------------+ 複製代碼
8. 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
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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
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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
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總結
- 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 ^^。
