Java教程

日常问题: SQL优化

本文主要是介绍日常问题: SQL优化,对大家解决编程问题具有一定的参考价值,需要的程序猿们随着小编来一起学习吧!

日常开发中,除了开辟新项目,业务需求开发,一般还要做负责系统的日常运维。比如线上告警了,出bug了,必须及时修复。这天,运维反馈mysql cpu告警了,然后抓了该时间节点的慢sql日志,要开发分析解决。

拿到的慢sql日志:

# Query 1: 1.16 QPS, 1.96x concurrency, ID 0x338A0AEE1CFE3C1D at byte 7687104
# This item is included in the report because it matches --limit.
# Scores: V/M = 0.02
# Time range: 2022-08-12T16:30:00 to 2022-08-12T17:11:32
# Attribute    pct   total     min     max     avg     95%  stddev  median
# ============ === ======= ======= ======= ======= ======= ======= =======
# Count         99    2880
# Exec time     99   4893s      1s      2s      2s      2s   172ms      2s
# Lock time     99   187ms    52us   343us    64us    84us    11us    60us
# Rows sent     97     248       0       1    0.09    0.99    0.28       0
# Rows examine  96 871.46M 308.56k 311.13k 309.85k 298.06k       0 298.06k
# Query size    99 812.81k     289     289     289     289       0     289
# String:
# Hosts        10.22.9.183 (742/25%), 10.26.9.126 (730/25%)... 2 more
# Users        order
# Query_time distribution
#   1us
#  10us
# 100us
#   1ms
#  10ms
# 100ms
#    1s  ################################################################
#  10s+
# Tables
#    SHOW TABLE STATUS LIKE 'serial_number_store'\G
#    SHOW CREATE TABLE `serial_number_store`\G
# EXPLAIN /*!50100 PARTITIONS*/
select *
        from serial_number_store sn
        where 1=1
          and company_code = '8511378117' 
          and warehouse_code = '851' 
          and sku_no = '6902952880' 
          and (serial_no = '5007894' or sub_serial_no = 'v')\G

查询数据库定义,发现定义了几个index

  PRIMARY KEY (`ID`),
  KEY `IDX_SERIAL_NUMBER_2` (`WAREHOUSE_CODE`),
  KEY `IDX_SERIAL_NUMBER_3` (`SKU_NO`),
  KEY `IDX_SERIAL_NUMBER_4` (`SERIAL_NO`),
  KEY `IDX_SERIAL_NUMBER_5` (`SUB_SERIAL_NO`),
  KEY `IDX_SERIAL_NUMBER_6` (`SKU_NAME`),
  KEY `IDX_SERIAL_NUMBER_1` (`COMPANY_CODE`,`WAREHOUSE_CODE`,`SKU_NO`,`SERIAL_NO`) USING BTREE

按最左匹配原则,这条sql应该只会命中一个索引。因为or的另一半无法match。

explain发现实际执行计划:

key: IDX_SERIAL_NUMBER_3
key_len: 259
ref: const
rows: 45864
filtered:  0.95
Extra: Using where

表总数量: 13658763

or的优化技巧之一就是拆成2个可以命中索引的sql, 然后union all.

优化为union all

 explain select *
        from  serial_number_store sn
        where  company_code = '9311046897' 
          and warehouse_code = '931DCA' 
          and sku_no = '6935117818696' 
          and serial_no = '862517054251459'
		  
		  union all
		  
		  select *
        from  serial_number_store sn
        where  company_code = '9311046897' 
          and warehouse_code = '931DCA' 
          and sku_no = '6935117818696' 
          and sub_serial_no = '862517054251459';

最终explain

key:  IDX_SERIAL_NUMBER_4  IDX_SERIAL_NUMBER_5
ref: const        const
rows: 1     1
filtered: 5.0    5.0
extra: using where 

正常到这里,找到解决方案,就算完事了。但作为线上问题的处理,你得分析为啥以前没事,现在出问题了。

查询对应的链路追踪情况:

和猜测一致,短时间内批量查询。几乎每条sql2s多耗时。虽然是后台任务,但数据量太大导致cpu 100%.

定位实际的代码,mybatis是这么写:

    <sql id="servialNumberStoreEntityParams">
    	<if test="id!=null and id!=''"> and ID = #{id}</if>
        <if test="companyCode!=null and companyCode!=''"> and company_code = #{companyCode}</if>
        <if test="warehouseCode!=null and warehouseCode!=''"> and warehouse_code = #{warehouseCode}</if>
        <if test="sku!=null and sku!=''"> and sku_no = #{sku}</if>
        <if test="serialNo!=null and serialNo!=''"> and (serial_no = #{serialNo} or sub_serial_no = #{serialNo})</if>
        <if test="lotNum!=null and lotNum!=''"> and lot_num = #{lotNum}</if>
    </sql>

这个查询片段有多个sql引用了。比如

select *
from serial_number_store sn
where 1=1
<include refid="servialNumberStoreEntityParams" />

改造成union也不是不行,比如

select *
        from  serial_number_store sn
        where 1=1
        <include refid="servialNumberStoreEntityParams" />
        <if test="serialNo!=null and serialNo!=''">
            and serial_no = #{serialNo}
            union all
            select *
            from cwsp_tb_serial_number_store sn
            where 1=1
            <include refid="servialNumberStoreEntityParams" />
            and sub_serial_no = #{serialNo}
        </if>

但前面说了多个片段引用了,对应多个sql查询方法,然后这多个sql查询方法又会对应多个业务调用。那问题来了,如果改完要测的话,业务场景该怎么测?一时犹豫了,要不要再花额外的时间去搞回归测试,验证。

和运维小哥说,反正是个后台任务,先不改吧。运维看没影响到业务(没人投诉)也就不管了。

然后第二天上班又收到了告警。逃不掉了。

定位代码的时候,发现有个update

<update id="update">
        update serial_number_store
        <set>
            <if test="companyCode!=null and companyCode!=''">  COMPANY_CODE = #{companyCode},</if>
            <if test="warehouseCode!=null and warehouseCode!=''">  WAREHOUSE_CODE = #{warehouseCode},</if>
            <if test="sku!=null and sku!=''">  SKU_NO = #{sku},</if>
            <if test="serialNo!=null and serialNo!=''">  SERIAL_NO = #{serialNo},</if>
            <if test="subSerialNo!=null and subSerialNo!=''">  SUB_SERIAL_NO = #{subSerialNo},</if>
            <if test="erpno!=null and erpno!=''">  ERP_ORDER = #{erpno},</if>
            <if test="docType!=null and docType!=''">  DOCTYPE = #{docType},</if>
            <if test="editTime!=null and editTime!=''">  EDITTM = #{editTime},</if>
            <if test="editWho!=null and editWho!=''">  EDITEMP = #{editWho},</if>
           </set>
        where 1=1
        <include refid="servialNumberStoreEntityParams" />
    </update>

这种sql,假如参数没传,岂不是全表被覆盖? 当然,也能改。前提是梳理调用链路,把这些sql引用的业务场景梳理一遍,确定入参场景,然后修改,然后再模拟场景做测试。想想整个流程,1天不知道搞不搞的定,测试上线等等,还有更长的流程。

这种在设计之初就应该做好优化设计而不是出了问题再改,但当接手古老系统的时候,开发可能换了一波又一波了,这时候除了吐槽之外,只能填坑。与此同时,自己所开发的代码,在若干时间后,也许会被另外一个人吐槽(如果自己发现的坑是自己挖的,自然不会吐槽自己)

这篇关于日常问题: SQL优化的文章就介绍到这儿,希望我们推荐的文章对大家有所帮助,也希望大家多多支持为之网!