面試官：MySQL 上億大表，如何深度優(yōu)化？
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·
2024-04-22 09:43
來源：cnblogs.com/YangJiaXin/p/10828244.html
-
背景 -
分析 -
測試 -
實施 -
索引優(yōu)化后 -
delete大表優(yōu)化為小批量刪除 -
總結(jié)
前段時間剛?cè)肼氁患夜荆陀錾线@事！
背景
XX實例（一主一從）xxx告警中每天凌晨在報SLA報警，該報警的意思是存在一定的主從延遲（若在此時發(fā)生主從切換，需要長時間才可以完成切換，要追延遲來保證主從數(shù)據(jù)的一致性）
XX實例的慢查詢數(shù)量最多（執(zhí)行時間超過1s的sql會被記錄），XX應(yīng)用那方每天晚上在做刪除一個月前數(shù)據(jù)的任務(wù)
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
結(jié)果第一部分
最近一個星期內(nèi)，總共記錄的慢查詢執(zhí)行花費時間為25403s，最大的慢sql執(zhí)行時間為266s，平均每個慢sql執(zhí)行時間5s，平均掃描的行數(shù)為1766萬
結(jié)果第二部分
select arrival_record操作記錄的慢查詢數(shù)量最多有4萬多次，平均響應(yīng)時間為4s，delete arrival_record記錄了6次，平均響應(yīng)時間258s。
select xxx_record語句
select arrival_record 慢查詢語句都類似于如下所示，where語句中的參數(shù)字段是一樣的，傳入的參數(shù)值不一樣 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
select arrival_record 語句在mysql中最多掃描的行數(shù)為5600萬、平均掃描的行數(shù)為172萬，推斷由于掃描的行數(shù)多導(dǎo)致的執(zhí)行時間長
查看執(zhí)行計劃
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(yù)計掃描的行數(shù)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),
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(shù)約1億多條，表上只有一個復(fù)合索引，product_id字段基數(shù)很小，選擇性不好 -
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，使用不到復(fù)合索引 IXFK_arrival_record的 product_id,station_no,sequence,receive_time這幾個字段 -
根據(jù)最左前綴原則，select arrival_record只用到了復(fù)合索引IXFK_arrival_record的第一個字段product_id，而該字段選擇性很差，導(dǎo)致掃描的行數(shù)很多，執(zhí)行時間長 -
receive_time字段的基數(shù)大，選擇性好，可對該字段單獨建立索引，select arrival_record sql就會使用到該索引
現(xiàn)在已經(jīng)知道了在慢查詢中記錄的select arrival_record where語句傳入的參數(shù)字段有 product_id，receive_time，receive_spend_ms，還想知道對該表的訪問有沒有通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 后面的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，可以使用到復(fù)合索引IXFK_arrival_record的前三個字段
綜上所示，優(yōu)化方法為，刪除復(fù)合索引IXFK_arrival_record，建立復(fù)合索引idx_sequence_station_no_product_id，并建立單獨索引indx_receive_time
delete xxx_record語句
該delete操作平均掃描行數(shù)為1.1億行，平均執(zhí)行時間是262s
delete語句如下所示，每次記錄的慢查詢傳入的參數(shù)值不一樣
delete from arrival_record where receive_time < STR_TO_DATE('2019-02-23', '%Y-%m-%d')\G
執(zhí)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，導(dǎo)致執(zhí)行時間長
優(yōu)化方法也是 建立單獨索引indx_receive_time(receive_time)
測試
拷貝arrival_record表到測試實例上進行刪除重新索引操作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(shù)
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 |
+----------------+-------------+--------------+------------+----------------+------------+---------------------+
磁盤占用空間48G，mysql中該表大小為31G，存在17G左右的碎片，大多由于刪除操作造成的（記錄被刪除了，空間沒有回收)
備份還原該表到新的實例中，刪除原來的復(fù)合索引，重新添加索引進行測試
mydumper并行壓縮備份
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 $backupdir -t 32 -r 2000000 && echo `date +%T` &
并行壓縮備份所花時間（52s）和占用空間（1.2G，實際該表占用磁盤空間為48G，mydumper并行壓縮備份壓縮比相當(dāng)高！）
Started dump at: 2019-03-26 12:46:04
........
Finished dump at: 2019-03-26 12:46:56
du -sh /datas/dump_arrival_record/
1.2G /datas/dump_arrival_record/
拷貝dump數(shù)據(jù)到測試節(jié)點
scp -rp /datas/dump_arrival_record [email protected]:/datas
多線程導(dǎo)入數(shù)據(jù)
time myloader -u root -S /datas/mysql/data/3308/mysqld.sock -P 3308 -p root -B test -d /datas/dump_arrival_record -t 32
real 126m42.885s user 1m4.543s sys 0m4.267s
邏輯導(dǎo)入該表后磁盤占用空間
du -h -d 1 /datas/mysql/data/3308/test/arrival_record.*
12K /datas/mysql/data/3308/test/arrival_record.frm
30G /datas/mysql/data/3308/test/arrival_record.ibd
沒有碎片，和mysql的該表的大小一致
cp -rp /datas/mysql/data/3308 /datas
分別使用online DDL和 pt-osc工具來做刪除重建索引操作 先刪除外鍵，不刪除外鍵，無法刪除復(fù)合索引，外鍵列屬于復(fù)合索引中第一列
nohup bash /tmp/ddl_index.sh &
2019-04-04-10:41:39 begin stop mysqld_3308
2019-04-04-10:41:41 begin rm -rf datadir and cp -rp datadir_bak
2019-04-04-10:46:53 start mysqld_3308
2019-04-04-10:46:59 online ddl begin
2019-04-04-11:20:34 onlie ddl stop
2019-04-04-11:20:34 begin stop mysqld_3308
2019-04-04-11:20:36 begin rm -rf datadir and cp -rp datadir_bak
2019-04-04-11:22:48 start mysqld_3308
2019-04-04-11:22:53 pt-osc begin
2019-04-04-12:19:15 pt-osc stop
online ddl 花費時間為34 分鐘，pt-osc花費時間為57 分鐘，使用onlne ddl時間約為pt-osc工具時間的一半
*做DDL 參考 *
實施
由于是一主一從實例，應(yīng)用是連接的vip，刪除重建索引采用online ddl來做。停止主從復(fù)制后，先在從實例上做（不記錄binlog），主從切換，再在新切換的從實例上做（不記錄binlog)
function red_echo () {
local what="$*"
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(zhí)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 11:17:36ddl_stop 2019-04-08 11:45:132019-04-08-11:45:13 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
*再次查看delete 和select語句的執(zhí)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(shù)大大降低
索引優(yōu)化后
delete 還是花費了77s時間
delete from arrival_record where receive_time < STR_TO_DATE('2019-03-10', '%Y-%m-%d')\G
delete 語句通過receive_time的索引刪除300多萬的記錄花費77s時間*
delete大表優(yōu)化為小批量刪除
*應(yīng)用端已優(yōu)化成每次刪除10分鐘的數(shù)據(jù)（每次執(zhí)行時間1s左右），xxx中沒在出現(xiàn)SLA（主從延遲告警） *
*另一個方法是通過主鍵的順序每次刪除20000條記錄 *
#得到滿足時間條件的最大主鍵ID
#通過按照主鍵的順序去 順序掃描小批量刪除數(shù)據(jù)
#先執(zhí)行一次以下語句
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(zhí)行小批量delete后會返回row_count(), 刪除的行數(shù)
#程序判斷返回的row_count()是否為0，不為0執(zhí)行以下循環(huán)，為0退出循環(huán)，刪除操作完成
DELETE FROM arrival_record WHERE id<@need_delete_max_id LIMIT 20000;
select ROW_COUNT();
#程序睡眠0.5s
總結(jié)
-
表數(shù)據(jù)量太大時，除了關(guān)注訪問該表的響應(yīng)時間外，還要關(guān)注對該表的維護成本（如做DDL表更時間太長，delete歷史數(shù)據(jù)）。 -
對大表進行DDL操作時，要考慮表的實際情況（如對該表的并發(fā)表，是否有外鍵）來選擇合適的DDL變更方式。 -
對大數(shù)據(jù)量表進行delete，用小批量刪除的方式，減少對主實例的壓力和主從延遲。