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背景
近期凌晨经常收到 MySQL 一套实例（一主一从）告警。
告警的原因是存在一定程度的主从延迟。主从延迟过大会影响故障切换，因为若发生切换，需要长时间才可以完成切换，要追延迟来保证主从数据的一致性。
这套 MySQL 实例上的慢查询数量也多，原因是应用每天晚上跑批，在做删除三个月前数据的任务。
分析
使用 pt-query-digest 工具分析一周的慢日志：
pt-query-digest --since=148h mysql-slow.log | less
结果一：
最近的一周时间里，所有记录的慢查询总共消耗了 25403s，其中，执行时间最长的 SQL 耗时 266s，平均每个慢 SQL 执行时间 5s，平均扫描的行数为 1766 万。
结果二：
大多数慢查询都集中在 select arrival_record 操作上，平均响应时间为 4s，delete arrival_record 记录了 6 次，平均响应时间 258s。最多扫描的行数为 5600 万、平均扫描的行数为 172 万，推断由于扫描的行数多导致的执行时间长。
执行计划：
explain select count(*) from arrival_record where product_id=26 and receive_time between '2024-03-25 14:00:00' and '2024-03-25 15:00:00' and receive_spend_ms>=0\G;
*************************** 1. row ***************************
id: 1
select_type: SIMPLE
table: arrival_record
partitions: NULL
type: ref
possible_keys: IXFK_arrival_record
key: IXFK_arrival_record
key_len: 8
ref: const
rows: 32261320
filtered: 3.70
Extra: Using index condition; Using where
1 row in set, 1 warning (0.00 sec)
执行计划走了索引 IXFK_arrival_record，但预估扫描的行数依然很高，有 3000 多万行：
show index from arrival_record;
+----------------+------------+---------------------+--------------+--------------+-----------+-------------+----------+--------+------+------------+---------+---------------+
| Table | Non_unique | Key_name | Seq_in_index | Column_name | Collation | Cardinality | Sub_part | Packed | Null | Index_type | Comment | Index_comment |
+----------------+------------+---------------------+--------------+--------------+-----------+-------------+----------+--------+------+------------+---------+---------------+
| arrival_record | 0 | PRIMARY | 1 | id | A | 107990720 | NULL | NULL | | BTREE | | |
| arrival_record | 1 | IXFK_arrival_record | 1 | product_id | A | 1344 | NULL | NULL | | BTREE | | |
| arrival_record | 1 | IXFK_arrival_record | 2 | station_no | A | 22161 | NULL | NULL | YES | BTREE | | |
| arrival_record | 1 | IXFK_arrival_record | 3 | sequence | A | 77233384 | NULL | NULL | | BTREE | | |
| arrival_record | 1 | IXFK_arrival_record | 4 | receive_time | A | 65854652 | NULL | NULL | YES | BTREE | | |
| arrival_record | 1 | IXFK_arrival_record | 5 | arrival_time | A | 73861904 | NULL | NULL | YES | BTREE | | |
+----------------+------------+---------------------+--------------+--------------+-----------+-------------+----------+--------+------+------------+---------+---------------+
show create table arrival_record;
..........
arrival_spend_ms bigint(20) DEFAULT NULL,
total_spend_ms bigint(20) DEFAULT NULL,
PRIMARY KEY (id),
KEY IXFK_arrival_record (product_id,station_no,sequence,receive_time,arrival_time) USING BTREE,
CONSTRAINT FK_arrival_record_product FOREIGN KEY (product_id) REFERENCES product (id) ON DELETE NO ACTION ON UPDATE NO ACTION
) ENGINE=InnoDB AUTO_INCREMENT=614538979 DEFAULT CHARSET=utf8 COLLATE=utf8_bin |
该表是典型的大表，总记录数约1亿条，表上只有一个复合索引，且product_id 选择性不好。
分析过滤条件，根据最左前缀原则，只用到了复合索引 IXFK_arrival_record 的第一个字段 product_id，而该字段选择性很差，导致扫描的行数很多，执行时间长。
receive_time 字段的基数大，选择性好，可考虑对该字段单独建立索引。
使用 tcpdump 抓包一段时间对该表的 select 语句：
tcpdump -i bond0 -s 0 -l -w - dst port 3316 | strings | grep select | egrep -i 'arrival_record' >/tmp/select_arri.log
获取 select 语句中 from 后面的 where 条件语句：
IFS_OLD=$IFS
IFS=$'\n'
for i in `cat /tmp/select_arri.log `;do echo ${i#*'from'}; done | less
IFS=$IFS_OLD
arrival_record arrivalrec0_ where arrivalrec0_.sequence='2024-03-27 08:40' and arrivalrec0_.product_id=17 and arrivalrec0_.station_no='56742'
arrival_record arrivalrec0_ where arrivalrec0_.sequence='2024-03-27 08:40' and arrivalrec0_.product_id=22 and arrivalrec0_.station_no='S7100'
arrival_record arrivalrec0_ where arrivalrec0_.sequence='2024-03-27 08:40' and arrivalrec0_.product_id=24 and arrivalrec0_.station_no='V4631'
arrival_record arrivalrec0_ where arrivalrec0_.sequence='2024-03-27 08:40' and arrivalrec0_.product_id=22 and arrivalrec0_.station_no='S9466'
arrival_record arrivalrec0_ where arrivalrec0_.sequence='2024-03-27 08:40' and arrivalrec0_.product_id=24 and arrivalrec0_.station_no='V4205'
arrival_record arrivalrec0_ where arrivalrec0_.sequence='2024-03-27 08:40' and arrivalrec0_.product_id=24 and arrivalrec0_.station_no='V4105'
arrival_record arrivalrec0_ where arrivalrec0_.sequence='2024-03-27 08:40' and arrivalrec0_.product_id=24 and arrivalrec0_.station_no='V4506'
arrival_record arrivalrec0_ where arrivalrec0_.sequence='2024-03-27 08:40' and arrivalrec0_.product_id=24 and arrivalrec0_.station_no='V4617'
arrival_record arrivalrec0_ where arrivalrec0_.sequence='2024-03-27 08:40' and arrivalrec0_.product_id=22 and arrivalrec0_.station_no='S8356'
arrival_record arrivalrec0_ where arrivalrec0_.sequence='2024-03-27 08:40' and arrivalrec0_.product_id=22 and arrivalrec0_.station_no='S8356'
过滤条件中有 product_id，station_no，sequence 字段，可以使用到复合索引 IXFK_arrival_record 的前三个字段。
综上，优化方法为：
删除复合索引 IXFK_arrival_record 建立复合索引 idx_sequence_station_no_product_id 建立单独索引 indx_receive_time
再分析 delete xxx_record 语句
该 delete 操作平均扫描行数为 1.1 亿行，平均执行时间是 262s。
执行计划：
explain select * from arrival_record where receive_time < STR_TO_DATE('2024-02-23', '%Y-%m-%d')\G
*************************** 1. row ***************************
id: 1
select_type: SIMPLE
table: arrival_record
partitions: NULL
type: ALL
possible_keys: NULL
key: NULL
key_len: NULL
ref: NULL
rows: 109501508
filtered: 33.33
Extra: Using where
1 row in set, 1 warning (0.00 sec)
该 delete 语句走的全表扫描。
优化方法：建立单独索引 indx_receive_time(receive_time)。
测试
测试方案在测试环境进行，测试删除重建索引操作。
分别使用 online DDL 和 pt-osc 工具来做删除重建索引操作。
先删除外键，不删除外键，无法删除复合索引，外键列属于复合索引中第一列：
nohup bash /tmp/ddl_index.sh &
2024-04-04-10:41:39 begin stop mysqld_3308
2024-04-04-10:41:41 begin rm -rf datadir and cp -rp datadir_bak
2024-04-04-10:46:53 start mysqld_3308
2024-04-04-10:46:59 online ddl begin
2024-04-04-11:20:34 onlie ddl stop
2024-04-04-11:20:34 begin stop mysqld_3308
2024-04-04-11:20:36 begin rm -rf datadir and cp -rp datadir_bak
2024-04-04-11:22:48 start mysqld_3308
2024-04-04-11:22:53 pt-osc begin
2024-04-04-12:19:15 pt-osc stop
online DDL 耗时约 34 分钟，pt-osc 耗时约 57 分钟，onlne DDL 效率更高。
线上变更
由于是一主一从架构，停止主从复制后，先在从实例上做（不记录 binlog），主从切换，再在新切换的从实例上做（不记录 binlog)：
function red_echo () {
local what="$*"
echo -e "$(date +%F-%T) ${what}"
}
function check_las_comm(){
if [ "$1" != "0" ];then
red_echo "$2"
echo "exit 1"
exit 1
fi
}
red_echo "stop slave"
mysql -uroot -p$passwd --socket=/datas/mysql/data/${port}/mysqld.sock -e"stop slave"
check_las_comm "$?" "stop slave failed"
red_echo "online ddl begin"
mysql -uroot -p$passwd --socket=/datas/mysql/data/${port}/mysqld.sock -e"set sql_log_bin=0;select now() as ddl_start;ALTER TABLE $db_.\`${table_name}\` DROP FOREIGN KEY FK_arrival_record_product,drop index IXFK_arrival_record,add index idx_product_id_sequence_station_no(product_id,sequence,station_no),add index idx_receive_time(receive_time);select now() as ddl_stop" >>${log_file} 2>& 1
red_echo "onlie ddl stop"
red_echo "add foreign key"
mysql -uroot -p$passwd --socket=/datas/mysql/data/${port}/mysqld.sock -e"set sql_log_bin=0;ALTER TABLE $db_.${table_name} ADD CONSTRAINT _FK_${table_name}_product FOREIGN KEY (product_id) REFERENCES cq_new_cimiss.product (id) ON DELETE NO ACTION ON UPDATE NO ACTION;" >>${log_file} 2>& 1
check_las_comm "$?" "add foreign key error"
red_echo "add foreign key stop"
red_echo "start slave"
mysql -uroot -p$passwd --socket=/datas/mysql/data/${port}/mysqld.sock -e"start slave"
check_las_comm "$?" "start slave failed"
执行时间：
2024-04-08-11:17:36 stop slave
mysql: [Warning] Using a password on the command line interface can be insecure.
ddl_start
2024-04-08 11:17:36
ddl_stop
2024-04-08 11:45:13
2024-04-08-11:45:13 onlie ddl stop
2024-04-08-11:45:13 add foreign key
mysql: [Warning] Using a password on the command line interface can be insecure.
2024-04-08-12:33:48 add foreign key stop
2024-04-08-12:33:48 start slave
删除重建索引耗时 28 分钟，添加外键耗时 48 分钟。
再次查看执行计划：
explain select count(*) from arrival_record where receive_time < STR_TO_DATE('2024-03-10', '%Y-%m-%d')\G
*************************** 1. row ***************************
id: 1
select_type: SIMPLE
table: arrival_record
partitions: NULL
type: range
possible_keys: idx_receive_time
key: idx_receive_time
key_len: 6
ref: NULL
rows: 7540948
filtered: 100.00
Extra: Using where; Using index
explain select count(*) from arrival_record where product_id=26 and receive_time between '2024-03-25 14:00:00' and '2024-03-25 15:00:00' and receive_spend_ms>=0\G;
*************************** 1. row ***************************
id: 1
select_type: SIMPLE
table: arrival_record
partitions: NULL
type: range
possible_keys: idx_product_id_sequence_station_no,idx_receive_time
key: idx_receive_time
key_len: 6
ref: NULL
rows: 291448
filtered: 16.66
Extra: Using index condition; Using where
执行计划良好，行扫描大大降低。
后续
delete 操作还是花费了 77s 时间，效率不尽如人意：
建议应用端小批量多次删除，后续没有再出现主从延迟告警。
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