上億條數(shù)據(jù)的 MySQL 大表優(yōu)化....
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作者：jiaxin_12
來源：www.cnblogs.com/YangJiaXin/
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_OLDarrival_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(jìn)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)，《MySQL數(shù)據(jù)庫開發(fā)的 36 條軍規(guī)！》這篇推薦看一下。
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 $backupdir -t?32?-r?2000000?&& echo?`date +%T`?&并行壓縮備份所花時間（52s）和占用空間（1.2G，實際該表占用磁盤空間為48G，mydumper并行壓縮備份壓縮比相當(dāng)高！）
Started?dump?at:?2019-03-26?12:46:04
........
Finished?dump?at:?2019-03-26?12:46:56
du?-sh???/datas/dump_arrival_record/
1.2G??/datas/dump_arrival_record/拷貝dump數(shù)據(jù)到測試節(jié)點
scp -rp /datas/dump_arrival_record root@10.230.124.19:/datas多線程導(dǎo)入數(shù)據(jù)
time myloader -u root -S /datas/mysql/data/3308/mysqld.sock -P 3308 -p root -B?test?-d /datas/dump_arrival_record -t 32real 126m42.885s
user 1m4.543s
sys 0m4.267s
邏輯導(dǎo)入該表后磁盤占用空間
du -h -d 1 /datas/mysql/data/3308/test/arrival_record.*
12K /datas/mysql/data/3308/test/arrival_record.frm
30G /datas/mysql/data/3308/test/arrival_record.ibd
沒有碎片，和mysql的該表的大小一致cp?-rp /datas/mysql/data/3308?/datas分別使用online DDL和 pt-osc工具來做刪除重建索引操作
先刪除外鍵，不刪除外鍵，無法刪除復(fù)合索引，外鍵列屬于復(fù)合索引中第一列
nohup bash /tmp/ddl_index.sh &
2019-04-04-10:41:39?begin?stop?mysqld_3308
2019-04-04-10:41:41?begin?rm -rf datadir?and?cp -rp datadir_bak
2019-04-04-10:46:53?start?mysqld_3308
2019-04-04-10:46:59?online?ddl?begin
2019-04-04-11:20:34?onlie?ddl?stop
2019-04-04-11:20:34?begin?stop?mysqld_3308
2019-04-04-11:20:36?begin?rm -rf datadir?and?cp -rp datadir_bak
2019-04-04-11:22:48?start?mysqld_3308
2019-04-04-11:22:53?pt-osc?begin
2019-04-04-12:19:15?pt-osc?stop
online?ddl?花費時間為34?分鐘，pt-osc花費時間為57?分鐘，使用onlne?ddl時間約為pt-osc工具時間的一半做DDL 參考
實施
由于是一主一從實例，應(yīng)用是連接的vip，刪除重建索引采用online ddl來做。停止主從復(fù)制后，先在從實例上做（不記錄binlog），主從切換，再在新切換的從實例上做（不記錄binlog)
function?red_echo?()?{
????????local?what="$*"
????????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
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
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(hù)成本（如做DDL表更時間太長，delete歷史數(shù)據(jù)）。
對大表進(jìn)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(jìn)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。
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