目录
背景
xx实例(一主一从)xxx告警中每天凌晨在报sla报警,该报警的意思是存在一定的主从延迟(若在此时发生主从切换,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)
xx实例的慢查询数量最多(执行时间超过1s的sql会被记录),xx应用那方每天晚上在做删除一个月前数据的任务
分析
使用pt-query-digest工具分析最近一周的mysql-slow.log
pt-query-digest –since=148h mysql-slow.log | less
结果第一部分
最近一个星期内,总共记录的慢查询执行花费时间为25403s,最大的慢sql执行时间为266s,平均每个慢sql执行时间5s,平均扫描的行数为1766万
结果第二部分
select arrival_record操作记录的慢查询数量最多有4万多次,平均响应时间为4s,delete arrival_record记录了6次,平均响应时间258s
select xxx_record语句
select arrival_record 慢查询语句都类似于如下所示,where语句中的参数字段是一样的,传入的参数值不一样
select count(*) from arrival_record where product_id=26 and receive_time between ‘2019-03-25 14:00:00’ and ‘2019-03-25 15:00:00’ and receive_spend_ms>=0g
select arrival_record 语句在mysql中最多扫描的行数为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
查看执行计划
explain select count() from arrival_record where product_id=26 and receive_time between ‘2019-03-25 14:00:00’ and ‘2019-03-25 15:00:00’ and receive_spend_ms>=0g;
************************** 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)
用到了索引ixfk_arrival_record,但预计扫描的行数很多有3000多w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
),
keyixfk_arrival_record
(product_id
,station_no
,sequence
,receive_time
,arrival_time
) using btree,
constraintfk_arrival_record_product
foreign key (product_id
) referencesproduct
(id
) on delete no action on update no action
) engine=innodb auto_increment=614538979 default charset=utf8 collate=utf8_bin |
—
- 该表总记录数约1亿多条,表上只有一个复合索引,product_id字段基数很小,选择性不好
- 传入的过滤条件 where product_id=26 and receive_time between ‘2019-03-25 14:00:00’ and ‘2019-03-25 15:00:00’ and receive_spend_ms>=0 没有station_nu字段,使用不到复合索引 ixfk_arrival_record的
product_id
,station_no
,sequence
,receive_time
这几个字段- 根据最左前缀原则,select arrival_record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,可对该字段单独建立索引,select arrival_record sql就会使用到该索引
现在已经知道了在慢查询中记录的select arrival_record where语句传入的参数字段有 product_id,receive_time,receive_spend_ms,还想知道对该表的访问有没有通过其它字段来过滤了?
神器tcpdump出场的时候到了
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=’2019-03-27 08:40′ and arrivalrec0_.product_id=17 and arrivalrec0_.station_no=’56742′
arrival_record arrivalrec0_ where arrivalrec0_.sequence=’2019-03-27 08:40′ and arrivalrec0_.product_id=22 and arrivalrec0_.station_no=’s7100′
arrival_record arrivalrec0_ where arrivalrec0_.sequence=’2019-03-27 08:40′ and arrivalrec0_.product_id=24 and arrivalrec0_.station_no=’v4631′
arrival_record arrivalrec0_ where arrivalrec0_.sequence=’2019-03-27 08:40′ and arrivalrec0_.product_id=22 and arrivalrec0_.station_no=’s9466′
arrival_record arrivalrec0_ where arrivalrec0_.sequence=’2019-03-27 08:40′ and arrivalrec0_.product_id=24 and arrivalrec0_.station_no=’v4205′
arrival_record arrivalrec0_ where arrivalrec0_.sequence=’2019-03-27 08:40′ and arrivalrec0_.product_id=24 and arrivalrec0_.station_no=’v4105′
arrival_record arrivalrec0_ where arrivalrec0_.sequence=’2019-03-27 08:40′ and arrivalrec0_.product_id=24 and arrivalrec0_.station_no=’v4506′
arrival_record arrivalrec0_ where arrivalrec0_.sequence=’2019-03-27 08:40′ and arrivalrec0_.product_id=24 and arrivalrec0_.station_no=’v4617′
arrival_record arrivalrec0_ where arrivalrec0_.sequence=’2019-03-27 08:40′ and arrivalrec0_.product_id=22 and arrivalrec0_.station_no=’s8356′
arrival_record arrivalrec0_ where arrivalrec0_.sequence=’2019-03-27 08:40′ and arrivalrec0_.product_id=22 and arrivalrec0_.station_no=’s8356′
- select 该表 where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
—
综上所示,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,并建立单独索引indx_receive_time
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
delete语句如下所示,每次记录的慢查询传入的参数值不一样
delete from arrival_record where receive_time < str_to_date(‘2019-02-23’, ‘%y-%m-%d’)g
执行计划
explain select * from arrival_record where receive_time < str_to_date(‘2019-02-23’, ‘%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语句没有使用索引(没有合适的索引可用),走的全表扫描,导致执行时间长
- 优化方法也是 建立单独索引indx_receive_time(receive_time)
测试
拷贝arrival_record表到测试实例上进行删除重新索引操作
xx实例arrival_record表信息
du -sh /datas/mysql/data/3316/cq_new_cimiss/arrival_record*
12k /datas/mysql/data/3316/cq_new_cimiss/arrival_record.frm
48g /datas/mysql/data/3316/cq_new_cimiss/arrival_record.ibd
select count() from
cq_new_cimiss
.arrival_record
;
+———–+
| count() |
+———–+
| 112294946 |
+———–+
1亿多记录数
select
table_name,
concat(format(sum(data_length) / 1024 / 1024,2),’m’) as dbdata_size,
concat(format(sum(index_length) / 1024 / 1024,2),’m’) as dbindex_size,
concat(format(sum(data_length + index_length) / 1024 / 1024 / 1024,2),’g’) astable_size(g)
,
avg_row_length,table_rows,update_time
from
information_schema.tables
where table_schema = ‘cq_new_cimiss’ and table_name=’arrival_record’;
+—————-+————-+————–+————+—————-+————+———————+
| table_name | dbdata_size | dbindex_size | table_size(g) | avg_row_length | table_rows | update_time |
+—————-+————-+————–+————+—————-+————+———————+
| arrival_record | 18,268.02m | 13,868.05m | 31.38g | 175 | 109155053 | 2019-03-26 12:40:17 |
+—————-+————-+————–+————+—————-+————+———————+
磁盘占用空间48g,mysql中该表大小为31g,存在17g左右的碎片,大多由于删除操作造成的(记录被删除了,空间没有回收)
备份还原该表到新的实例中,删除原来的复合索引,重新添加索引进行测试
mydumper并行压缩备份
user=root passwd=xxxx socket=/datas/mysql/data/3316/mysqld.sock db=cq_new_cimiss table_name=arrival_record backupdir=/datas/dump_$table_name mkdir -p $backupdir nohup echo `date +%t` && mydumper -u $user -p $passwd -s $socket -b $db -c -t $table_name -o $backupdir -t 32 -r 2000000 && echo `date +%t` &
并行压缩备份所花时间(52s)和占用空间(1.2g,实际该表占用磁盘空间为48g,mydumper并行压缩备份压缩比相当高!)
started dump at: 2019-03-26 12:46:04 ........ finished dump at: 2019-03-26 12:46:56 du -sh /datas/dump_arrival_record/ 1.2g /datas/dump_arrival_record/
拷贝dump数据到测试节点
scp -rp /datas/dump_arrival_record root@10.230.124.19:/datas
多线程导入数据
time myloader -u root -s /datas/mysql/data/3308/mysqld.sock -p 3308 -p root -b test -d /datas/dump_arrival_record -t 32
real 126m42.885s
user 1m4.543s
sys 0m4.267s
逻辑导入该表后磁盘占用空间
du -h -d 1 /datas/mysql/data/3308/test/arrival_record.
12k /datas/mysql/data/3308/test/arrival_record.frm
30g /datas/mysql/data/3308/test/arrival_record.ibd
没有碎片,和mysql的该表的大小一致*
cp -rp /datas/mysql/data/3308 /datas
分别使用online ddl和 pt-osc工具来做删除重建索引操作
先删除外键,不删除外键,无法删除复合索引,外键列属于复合索引中第一列
nohup bash /tmp/ddl_index.sh &
2019-04-04-10:41:39 begin stop mysqld_3308
2019-04-04-10:41:41 begin rm -rf datadir and cp -rp datadir_bak
2019-04-04-10:46:53 start mysqld_3308
2019-04-04-10:46:59 online ddl begin
2019-04-04-11:20:34 onlie ddl stop
2019-04-04-11:20:34 begin stop mysqld_3308
2019-04-04-11:20:36 begin rm -rf datadir and cp -rp datadir_bak
2019-04-04-11:22:48 start mysqld_3308
2019-04-04-11:22:53 pt-osc begin
2019-04-04-12:19:15 pt-osc stop
online ddl 花费时间为34 分钟,pt-osc花费时间为57 分钟,使用onlne ddl时间约为pt-osc工具时间的一半
做ddl 参考
实施
由于是一主一从实例,应用是连接的vip,删除重建索引采用online ddl来做。停止主从复制后,先在从实例上做(不记录binlog),主从切换,再在新切换的从实例上做(不记录binlog)
function red_echo () { local what="$*" 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
2019-04-08-11:17:36 stop slave
mysql: [warning] using a password on the command line interface can be insecure.
ddl_start
2019-04-08 11:17:36
ddl_stop
2019-04-08 11:45:13
2019-04-08-11:45:13 onlie ddl stop
2019-04-08-11:45:13 add foreign key
mysql: [warning] using a password on the command line interface can be insecure.
2019-04-08-12:33:48 add foreign key stop
2019-04-08-12:33:48 start slave
删除重建索引花费时间为28分钟,添加外键约束时间为48分钟
再次查看delete 和select语句的执行计划
explain select count() from arrival_record where receive_time < str_to_date(‘2019-03-10’, ‘%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 ‘2019-03-25 14:00:00’ and ‘2019-03-25 15:00:00’ and receive_spend_ms>=0g;
************************** 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
都使用到了idx_receive_time 索引,扫描的行数大大降低
索引优化后
delete 还是花费了77s时间
delete from arrival_record where receive_time < str_to_date('2019-03-10', '%y-%m-%d')g
delete 语句通过receive_time的索引删除300多万的记录花费77s时间*
delete大表优化为小批量删除
应用端已优化成每次删除10分钟的数据(每次执行时间1s左右),xxx中没在出现sla(主从延迟告警)
另一个方法是通过主键的顺序每次删除20000条记录
需要了解更多数据库技术:MySQL 上亿大表优化实践,都可以关注数据库技术分享栏目—计算机技术网(www.ctvol.com)!
#得到满足时间条件的最大主键id #通过按照主键的顺序去 顺序扫描小批量删除数据 #先执行一次以下语句 select max(id) into @need_delete_max_id from `arrival_record` where receive_time<'2019-03-01' ; delete from arrival_record where id<@need_delete_max_id limit 20000; select row_count(); #返回20000 #执行小批量delete后会返回row_count(), 删除的行数 #程序判断返回的row_count()是否为0,不为0执行以下循环,为0退出循环,删除操作完成 delete from arrival_record where id<@need_delete_max_id limit 20000; select row_count(); #程序睡眠0.5s
总结
- 表数据量太大时,除了关注访问该表的响应时间外,还要关注对该表的维护成本(如做ddl表更时间太长,delete历史数据)
- 对大表进行ddl操作时,要考虑表的实际情况(如对该表的并发表,是否有外键)来选择合适的ddl变更方式
- 对大数据量表进行delete,用小批量删除的方式,减少对主实例的压力和主从延迟
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