MySQL 上億大表優化實踐

時間 2019-12-11

標籤 mysql 優化實踐欄目 MySQL 简体版

原文原文鏈接

目錄mysql

背景

XX實例（一主一從）xxx告警中天天凌晨在報SLA報警，該報警的意思是存在必定的主從延遲（若在此時發生主從切換，須要長時間才能夠完成切換，要追延遲來保證主從數據的一致性）sql

XX實例的慢查詢數量最多（執行時間超過1s的sql會被記錄），XX應用那方天天晚上在作刪除一個月前數據的任務bash

分析

使用pt-query-digest工具分析最近一週的mysql-slow.log
pt-query-digest --since=148h mysql-slow.log | less
結果第一部分
多線程

最近一個星期內，總共記錄的慢查詢執行花費時間爲25403s，最大的慢sql執行時間爲266s，平均每一個慢sql執行時間5s，平均掃描的行數爲1766萬併發

結果第二部分
less

select arrival_record操做記錄的慢查詢數量最多有4萬屢次，平均響應時間爲4s，delete arrival_record記錄了6次，平均響應時間258ssocket

select xxx_record語句

select arrival_record 慢查詢語句都相似於以下所示，where語句中的參數字段是同樣的，傳入的參數值不同
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>=0\Gtcp

select arrival_record 語句在mysql中最多掃描的行數爲5600萬、平均掃描的行數爲172萬，推斷因爲掃描的行數多致使的執行時間長工具

查看執行計劃測試

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>=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)

用到了索引IXFK_arrival_record，但預計掃描的行數不少有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),
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 |
---

該表總記錄數約1億多條，表上只有一個複合索引，product_id字段基數很小，選擇性很差

傳入的過濾條件 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 沒有station_nu字段，使用不到複合索引 IXFK_arrival_record的 product_id,station_no,sequence,receive_time 這幾個字段

根據最左前綴原則，select arrival_record只用到了複合索引IXFK_arrival_record的第一個字段product_id，而該字段選擇性不好，致使掃描的行數不少，執行時間長

receive_time字段的基數大，選擇性好，可對該字段單獨創建索引，select arrival_record sql就會使用到該索引

如今已經知道了在慢查詢中記錄的select arrival_record where語句傳入的參數字段有 product_id，receive_time，receive_spend_ms，還想知道對該表的訪問有沒有經過其它字段來過濾了？

神器tcpdump出場的時候到了

使用tcpdump抓包一段時間對該表的select語句

tcpdump -i bond0 -s 0 -l -w - dst port 3316 | strings | grep select | egrep -i 'arrival_record' >/tmp/select_arri.log

獲取select 語句中from 後面的where條件語句

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 該表 where條件中有product_id,station_no,sequence字段，可使用到複合索引IXFK_arrival_record的前三個字段
---

綜上所示，優化方法爲，刪除複合索引IXFK_arrival_record，創建複合索引idx_sequence_station_no_product_id，並創建單獨索引indx_receive_time

delete xxx_record語句

該delete操做平均掃描行數爲1.1億行，平均執行時間是262s

delete語句以下所示，每次記錄的慢查詢傳入的參數值不同

delete from arrival_record where receive_time < STR_TO_DATE('2019-02-23', '%Y-%m-%d')\G

執行計劃

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)

該delete語句沒有使用索引（沒有合適的索引可用），走的全表掃描，致使執行時間長

優化方法也是創建單獨索引indx_receive_time(receive_time)

測試

拷貝arrival_record表到測試實例上進行刪除從新索引操做
XX實例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 |
+-----------+
1億多記錄數

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') AS table_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 |
+----------------+-------------+--------------+------------+----------------+------------+---------------------+

磁盤佔用空間48G，mysql中該表大小爲31G，存在17G左右的碎片，大多因爲刪除操做形成的（記錄被刪除了，空間沒有回收)

備份還原該表到新的實例中，刪除原來的複合索引，從新添加索引進行測試

mydumper並行壓縮備份

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` &

並行壓縮備份所花時間（52s）和佔用空間（1.2G，實際該表佔用磁盤空間爲48G，mydumper並行壓縮備份壓縮比至關高！）

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/

拷貝dump數據到測試節點
scp -rp /datas/dump_arrival_record root@10.230.124.19:/datas

多線程導入數據

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

邏輯導入該表後磁盤佔用空間

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
沒有碎片，和mysql的該表的大小一致*

cp -rp /datas/mysql/data/3308 /datas

分別使用online DDL和 pt-osc工具來作刪除重建索引操做
先刪除外鍵，不刪除外鍵，沒法刪除複合索引，外鍵列屬於複合索引中第一列

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 花費時間爲34 分鐘，pt-osc花費時間爲57 分鐘，使用onlne ddl時間約爲pt-osc工具時間的一半

作DDL 參考

實施

因爲是一主一從實例，應用是鏈接的vip，刪除重建索引採用online ddl來作。中止主從複製後，先在從實例上作（不記錄binlog），主從切換，再在新切換的從實例上作（不記錄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"

執行時間

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
刪除重建索引花費時間爲28分鐘，添加外鍵約束時間爲48分鐘

再次查看delete 和select語句的執行計劃

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>=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
都使用到了idx_receive_time 索引，掃描的行數大大下降

索引優化後

delete 仍是花費了77s時間

delete from arrival_record where receive_time < STR_TO_DATE('2019-03-10', '%Y-%m-%d')\G

delete 語句經過receive_time的索引刪除300多萬的記錄花費77s時間*

delete大表優化爲小批量刪除

應用端已優化成每次刪除10分鐘的數據（每次執行時間1s左右），xxx中沒在出現SLA（主從延遲告警）

另外一個方法是經過主鍵的順序每次刪除20000條記錄

#獲得知足時間條件的最大主鍵ID
#經過按照主鍵的順序去 順序掃描小批量刪除數據
#先執行一次如下語句
 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


#執行小批量delete後會返回row_count(), 刪除的行數
#程序判斷返回的row_count()是否爲0，不爲0執行如下循環，爲0退出循環，刪除操做完成
 DELETE FROM arrival_record WHERE id<@need_delete_max_id LIMIT 20000;
 select ROW_COUNT();
#程序睡眠0.5s