日常问题: SQL优化

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。

日常问题: SQL优化

日常问题: SQL优化

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:

日常问题: SQL优化

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)

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