本篇內(nèi)容介紹了“MySQL刪除數(shù)據(jù)時(shí)為什么不用delete”的有關(guān)知識,在實(shí)際案例的操作過程中,不少人都會遇到這樣的困境,接下來就讓小編帶領(lǐng)大家學(xué)習(xí)一下如何處理這些情況吧!希望大家仔細(xì)閱讀,能夠?qū)W有所成!
創(chuàng)新互聯(lián)公司一直在為企業(yè)提供服務(wù),多年的磨煉,使我們在創(chuàng)意設(shè)計(jì),全網(wǎng)整合營銷推廣到技術(shù)研發(fā)擁有了開發(fā)經(jīng)驗(yàn)。我們擅長傾聽企業(yè)需求,挖掘用戶對產(chǎn)品需求服務(wù)價(jià)值,為企業(yè)制作有用的創(chuàng)意設(shè)計(jì)體驗(yàn)。核心團(tuán)隊(duì)擁有超過十年以上行業(yè)經(jīng)驗(yàn),涵蓋創(chuàng)意,策化,開發(fā)等專業(yè)領(lǐng)域,公司涉及領(lǐng)域有基礎(chǔ)互聯(lián)網(wǎng)服務(wù)雙線服務(wù)器托管、成都app軟件開發(fā)、手機(jī)移動建站、網(wǎng)頁設(shè)計(jì)、網(wǎng)絡(luò)整合營銷。
有些表的數(shù)據(jù)量增長很快,對應(yīng)SQL掃描了很多無效數(shù)據(jù),導(dǎo)致SQL慢了下來,通過確認(rèn)之后,這些大表都是一些流水、記錄、日志類型數(shù)據(jù),只需要保留1到3個(gè)月,此時(shí)需要對表做數(shù)據(jù)清理實(shí)現(xiàn)瘦身。
這篇文章我會從InnoDB存儲空間分布,delete對性能的影響,以及優(yōu)化建議方面解釋為什么不建議delete刪除數(shù)據(jù)。
從這張圖可以看到,InnoDB存儲結(jié)構(gòu)主要包括兩部分:邏輯存儲結(jié)構(gòu)和物理存儲結(jié)構(gòu)。
邏輯上是由表空間tablespace —> 段segment或者inode —> 區(qū)Extent ——>數(shù)據(jù)頁P(yáng)age構(gòu)成,Innodb邏輯管理單位是segment,空間分配的最小單位是extent,每個(gè)segment都會從表空間FREE_PAGE中分配32個(gè)page,當(dāng)這32個(gè)page不夠用時(shí),會按照以下原則進(jìn)行擴(kuò)展:如果當(dāng)前小于1個(gè)extent,則擴(kuò)展到1個(gè)extent;當(dāng)表空間小于32MB時(shí),每次擴(kuò)展一個(gè)extent;表空間大于32MB,每次擴(kuò)展4個(gè)extent。
物理上主要由系統(tǒng)用戶數(shù)據(jù)文件,日志文件組成,數(shù)據(jù)文件主要存儲MySQL字典數(shù)據(jù)和用戶數(shù)據(jù),日志文件記錄的是data page的變更記錄,用于MySQL Crash時(shí)的恢復(fù)。
InnoDB存儲包括三類表空間:系統(tǒng)表空間,用戶表空間,Undo表空間。
系統(tǒng)表空間:主要存儲MySQL內(nèi)部的數(shù)據(jù)字典數(shù)據(jù),如information_schema下的數(shù)據(jù)。
用戶表空間:當(dāng)開啟innodb_file_per_table=1時(shí),數(shù)據(jù)表從系統(tǒng)表空間獨(dú)立出來存儲在以table_name.ibd命令的數(shù)據(jù)文件中,結(jié)構(gòu)信息存儲在table_name.frm文件中。
Undo表空間:存儲Undo信息,如快照一致讀和flashback都是利用undo信息。
從MySQL 8.0開始允許用戶自定義表空間,具體語法如下:
CREATE TABLESPACE tablespace_name ADD DATAFILE 'file_name' #數(shù)據(jù)文件名 USE LOGFILE GROUP logfile_group #自定義日志文件組,一般每組2個(gè)logfile。 [EXTENT_SIZE [=] extent_size] #區(qū)大小 [INITIAL_SIZE [=] initial_size] #初始化大小 [AUTOEXTEND_SIZE [=] autoextend_size] #自動擴(kuò)寬尺寸 [MAX_SIZE [=] max_size] #單個(gè)文件最大size,最大是32G。 [NODEGROUP [=] nodegroup_id] #節(jié)點(diǎn)組 [WAIT] [COMMENT [=] comment_text] ENGINE [=] engine_name
這樣的好處是可以做到數(shù)據(jù)的冷熱分離,分別用HDD和SSD來存儲,既能實(shí)現(xiàn)數(shù)據(jù)的高效訪問,又能節(jié)約成本,比如可以添加兩塊500G硬盤,經(jīng)過創(chuàng)建卷組vg,劃分邏輯卷lv,創(chuàng)建數(shù)據(jù)目錄并mount相應(yīng)的lv,假設(shè)劃分的兩個(gè)目錄分別是/hot_data 和 /cold_data。
這樣就可以將核心的業(yè)務(wù)表如用戶表,訂單表存儲在高性能SSD盤上,一些日志,流水表存儲在普通的HDD上,主要的操作步驟如下:
#創(chuàng)建熱數(shù)據(jù)表空間 create tablespace tbs_data_hot add datafile '/hot_data/tbs_data_hot01.dbf' max_size 20G; #創(chuàng)建核心業(yè)務(wù)表存儲在熱數(shù)據(jù)表空間 create table booking(id bigint not null primary key auto_increment, …… ) tablespace tbs_data_hot; #創(chuàng)建冷數(shù)據(jù)表空間 create tablespace tbs_data_cold add datafile '/hot_data/tbs_data_cold01.dbf' max_size 20G; #創(chuàng)建日志,流水,備份類的表存儲在冷數(shù)據(jù)表空間 create table payment_log(id bigint not null primary key auto_increment, …… ) tablespace tbs_data_cold; #可以移動表到另一個(gè)表空間 alter table payment_log tablespace tbs_data_hot;
mysql> create table user(id bigint not null primary key auto_increment, -> name varchar(20) not null default '' comment '姓名', -> age tinyint not null default 0 comment 'age', -> gender char(1) not null default 'M' comment '性別', -> phone varchar(16) not null default '' comment '手機(jī)號', -> create_time datetime NOT NULL DEFAULT CURRENT_TIMESTAMP COMMENT '創(chuàng)建時(shí)間', -> update_time datetime NOT NULL DEFAULT CURRENT_TIMESTAMP ON UPDATE CURRENT_TIMESTAMP COMMENT '修改時(shí)間' -> ) engine = InnoDB DEFAULT CHARSET=utf8mb4 COMMENT '用戶信息表'; Query OK, 0 rows affected (0.26 sec)
# ls -lh user1.ibd -rw-r----- 1 mysql mysql 96K Nov 6 12:48 user.ibd
設(shè)置參數(shù)innodb_file_per_table=1時(shí),創(chuàng)建表時(shí)會自動創(chuàng)建一個(gè)segment,同時(shí)分配一個(gè)extent,包含32個(gè)data page的來存儲數(shù)據(jù),這樣創(chuàng)建的空表默認(rèn)大小就是96KB,extent使用完之后會申請64個(gè)連接頁,這樣對于一些小表,或者undo segment,可以在開始時(shí)申請較少的空間,節(jié)省磁盤容量的開銷。
# python2 py_innodb_page_info.py -v /data2/mysql/test/user.ibd page offset 00000000, page type <File Space Header> page offset 00000001, page type <Insert Buffer Bitmap> page offset 00000002, page type <File Segment inode> page offset 00000003, page type <B-tree Node>, page level <0000> page offset 00000000, page type <Freshly Allocated Page> page offset 00000000, page type <Freshly Allocated Page> Total number of page: 6: #總共分配的頁數(shù) Freshly Allocated Page: 2 #可用的數(shù)據(jù)頁 Insert Buffer Bitmap: 1 #插入緩沖頁 File Space Header: 1 #文件空間頭 B-tree Node: 1 #數(shù)據(jù)頁 File Segment inode: 1 #文件端inonde,如果是在ibdata1.ibd上會有多個(gè)inode。
mysql> DELIMITER $$ mysql> CREATE PROCEDURE insert_user_data(num INTEGER) -> BEGIN -> DECLARE v_i int unsigned DEFAULT 0; -> set autocommit= 0; -> WHILE v_i < num DO -> insert into user(`name`, age, gender, phone) values (CONCAT('lyn',v_i), mod(v_i,120), 'M', CONCAT('152',ROUND(RAND(1)*100000000))); -> SET v_i = v_i+1; -> END WHILE; -> commit; -> END $$ Query OK, 0 rows affected (0.01 sec) mysql> DELIMITER ; #插入10w數(shù)據(jù) mysql> call insert_user_data(100000); Query OK, 0 rows affected (6.69 sec)
# ls -lh user.ibd -rw-r----- 1 mysql mysql 14M Nov 6 10:58 /data2/mysql/test/user.ibd # python2 py_innodb_page_info.py -v /data2/mysql/test/user.ibd page offset 00000000, page type <File Space Header> page offset 00000001, page type <Insert Buffer Bitmap> page offset 00000002, page type <File Segment inode> page offset 00000003, page type <B-tree Node>, page level <0001> #增加了一個(gè)非葉子節(jié)點(diǎn),樹的高度從1變?yōu)?. ........................................................ page offset 00000000, page type <Freshly Allocated Page> Total number of page: 896: Freshly Allocated Page: 493 Insert Buffer Bitmap: 1 File Space Header: 1 B-tree Node: 400 File Segment inode: 1
mysql> select min(id),max(id),count(*) from user; +---------+---------+----------+ | min(id) | max(id) | count(*) | +---------+---------+----------+ | 1 | 100000 | 100000 | +---------+---------+----------+ 1 row in set (0.05 sec) #刪除50000條數(shù)據(jù),理論上空間應(yīng)該從14MB變長7MB左右。 mysql> delete from user limit 50000; Query OK, 50000 rows affected (0.25 sec) #數(shù)據(jù)文件大小依然是14MB,沒有縮小。 # ls -lh /data2/mysql/test/user1.ibd -rw-r----- 1 mysql mysql 14M Nov 6 13:22 /data2/mysql/test/user.ibd #數(shù)據(jù)頁沒有被回收。 # python2 py_innodb_page_info.py -v /data2/mysql/test/user.ibd page offset 00000000, page type <File Space Header> page offset 00000001, page type <Insert Buffer Bitmap> page offset 00000002, page type <File Segment inode> page offset 00000003, page type <B-tree Node>, page level <0001> ........................................................ page offset 00000000, page type <Freshly Allocated Page> Total number of page: 896: Freshly Allocated Page: 493 Insert Buffer Bitmap: 1 File Space Header: 1 B-tree Node: 400 File Segment inode: 1 #在MySQL內(nèi)部是標(biāo)記刪除,
mysql> use information_schema; Database changed mysql> SELECT A.SPACE AS TBL_SPACEID, A.TABLE_ID, A.NAME AS TABLE_NAME, FILE_FORMAT, ROW_FORMAT, SPACE_TYPE, B.INDEX_ID , B.NAME AS INDEX_NAME, PAGE_NO, B.TYPE AS INDEX_TYPE FROM INNODB_SYS_TABLES A LEFT JOIN INNODB_SYS_INDEXES B ON A.TABLE_ID =B.TABLE_ID WHERE A.NAME = 'test/user1'; +-------------+----------+------------+-------------+------------+------------+----------+------------+---------+------------+ | TBL_SPACEID | TABLE_ID | TABLE_NAME | FILE_FORMAT | ROW_FORMAT | SPACE_TYPE | INDEX_ID | INDEX_NAME | PAGE_NO | INDEX_TYPE | +-------------+----------+------------+-------------+------------+------------+----------+------------+---------+------------+ | 1283 | 1207 | test/user | Barracuda | Dynamic | Single | 2236 | PRIMARY | 3 | 3 | +-------------+----------+------------+-------------+------------+------------+----------+------------+---------+------------+ 1 row in set (0.01 sec) PAGE_NO = 3 標(biāo)識B-tree的root page是3號頁,INDEX_TYPE = 3是聚集索引。 INDEX_TYPE取值如下: 0 = nonunique secondary index; 1 = automatically generated clustered index (GEN_CLUST_INDEX); 2 = unique nonclustered index; 3 = clustered index; 32 = full-text index; #收縮空間再后進(jìn)行觀察
MySQL內(nèi)部不會真正刪除空間,而且做標(biāo)記刪除,即將delflag:N修改為delflag:Y,commit之后會會被purge進(jìn)入刪除鏈表,如果下一次insert更大的記錄,delete之后的空間不會被重用,如果插入的記錄小于等于delete的記錄空會被重用,這塊內(nèi)容可以通過知數(shù)堂的innblock工具進(jìn)行分析。
我們知道數(shù)據(jù)存儲在文件系統(tǒng)上的,總是不能100%利用分配給它的物理空間,刪除數(shù)據(jù)會在頁面上留下一些”空洞”,或者隨機(jī)寫入(聚集索引非線性增加)會導(dǎo)致頁分裂,頁分裂導(dǎo)致頁面的利用空間少于50%,另外對表進(jìn)行增刪改會引起對應(yīng)的二級索引值的隨機(jī)的增刪改,也會導(dǎo)致索引結(jié)構(gòu)中的數(shù)據(jù)頁面上留下一些"空洞",雖然這些空洞有可能會被重復(fù)利用,但終究會導(dǎo)致部分物理空間未被使用,也就是碎片。
同時(shí),即便是設(shè)置了填充因子為100%,Innodb也會主動留下page頁面1/16的空間作為預(yù)留使用(An innodb_fill_factor setting of 100 leaves 1/16 of the space in clustered index pages free for future index growth)防止update帶來的行溢出。
mysql> select table_schema, -> table_name,ENGINE, -> round(DATA_LENGTH/1024/1024+ INDEX_LENGTH/1024/1024) total_mb,TABLE_ROWS, -> round(DATA_LENGTH/1024/1024) data_mb, round(INDEX_LENGTH/1024/1024) index_mb, round(DATA_FREE/1024/1024) free_mb, round(DATA_FREE/DATA_LENGTH*100,2) free_ratio -> from information_schema.TABLES where TABLE_SCHEMA= 'test' -> and TABLE_NAME= 'user'; +--------------+------------+--------+----------+------------+---------+----------+---------+------------+ | table_schema | table_name | ENGINE | total_mb | TABLE_ROWS | data_mb | index_mb | free_mb | free_ratio | +--------------+------------+--------+----------+------------+---------+----------+---------+------------+ | test | user | InnoDB | 4 | 50000 | 4 | 0 | 6 | 149.42 | +--------------+------------+--------+----------+------------+---------+----------+---------+------------+ 1 row in set (0.00 sec)
其中data_free是分配了未使用的字節(jié)數(shù),并不能說明完全是碎片空間。
對于InnoDB的表,可以通過以下命令來回收碎片,釋放空間,這個(gè)是隨機(jī)讀IO操作,會比較耗時(shí),也會阻塞表上正常的DML運(yùn)行,同時(shí)需要占用額外更多的磁盤空間,對于RDS來說,可能會導(dǎo)致磁盤空間瞬間爆滿,實(shí)例瞬間被鎖定,應(yīng)用無法做DML操作,所以禁止在線上環(huán)境去執(zhí)行。
#執(zhí)行InnoDB的碎片回收 mysql> alter table user engine=InnoDB; Query OK, 0 rows affected (9.00 sec) Records: 0 Duplicates: 0 Warnings: 0 ##執(zhí)行完之后,數(shù)據(jù)文件大小從14MB降低到10M。 # ls -lh /data2/mysql/test/user1.ibd -rw-r----- 1 mysql mysql 10M Nov 6 16:18 /data2/mysql/test/user.ibd
mysql> select table_schema, ->table_name,ENGINE, ->round(DATA_LENGTH/1024/1024+ INDEX_LENGTH/1024/1024) total_mb,TABLE_ROWS, ->round(DATA_LENGTH/1024/1024) data_mb, ->round(INDEX_LENGTH/1024/1024) index_mb, ->round(DATA_FREE/1024/1024) free_mb, ->round(DATA_FREE/DATA_LENGTH*100,2) free_ratio from information_schema.TABLES where TABLE_SCHEMA= 'test' and TABLE_NAME= 'user'; +--------------+------------+--------+----------+------------+---------+----------+---------+------------+ | table_schema | table_name | ENGINE | total_mb | TABLE_ROWS | data_mb | index_mb | free_mb | free_ratio | +--------------+------------+--------+----------+------------+---------+----------+---------+------------+ | test | user | InnoDB | 5 | 50000 | 5 | 0 | 2 | 44.29 | +--------------+------------+--------+----------+------------+---------+----------+---------+------------+ 1 row in set (0.00 sec)
#插入100W數(shù)據(jù) mysql> call insert_user_data(1000000); Query OK, 0 rows affected (35.99 sec) #添加相關(guān)索引 mysql> alter table user add index idx_name(name), add index idx_phone(phone); Query OK, 0 rows affected (6.00 sec) Records: 0 Duplicates: 0 Warnings: 0 #表上索引統(tǒng)計(jì)信息 mysql> show index from user; +-------+------------+-----------+--------------+-------------+-----------+-------------+----------+--------+------+------------+---------+---------------+ | Table | Non_unique | Key_name | Seq_in_index | Column_name | Collation | Cardinality | Sub_part | Packed | Null | Index_type | Comment | Index_comment | +-------+------------+-----------+--------------+-------------+-----------+-------------+----------+--------+------+------------+---------+---------------+ | user | 0 | PRIMARY | 1 | id | A | 996757 | NULL | NULL | | BTREE | | | | user | 1 | idx_name | 1 | name | A | 996757 | NULL | NULL | | BTREE | | | | user | 1 | idx_phone | 1 | phone | A | 2 | NULL | NULL | | BTREE | | | +-------+------------+-----------+--------------+-------------+-----------+-------------+----------+--------+------+------------+---------+---------------+ 3 rows in set (0.00 sec) #重置狀態(tài)變量計(jì)數(shù) mysql> flush status; Query OK, 0 rows affected (0.00 sec) #執(zhí)行SQL語句 mysql> select id, age ,phone from user where name like 'lyn12%'; +--------+-----+-------------+ | id | age | phone | +--------+-----+-------------+ | 124 | 3 | 15240540354 | | 1231 | 30 | 15240540354 | | 12301 | 60 | 15240540354 | ............................. | 129998 | 37 | 15240540354 | | 129999 | 38 | 15240540354 | | 130000 | 39 | 15240540354 | +--------+-----+-------------+ 11111 rows in set (0.03 sec) mysql> explain select id, age ,phone from user where name like 'lyn12%'; +----+-------------+-------+-------+---------------+----------+---------+------+-------+-----------------------+ | id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra | +----+-------------+-------+-------+---------------+----------+---------+------+-------+-----------------------+ | 1 | SIMPLE | user | range | idx_name | idx_name | 82 | NULL | 22226 | Using index condition | +----+-------------+-------+-------+---------------+----------+---------+------+-------+-----------------------+ 1 row in set (0.00 sec) #查看相關(guān)狀態(tài)呢變量 mysql> select * from information_schema.session_status where variable_name in('Last_query_cost','Handler_read_next','Innodb_pages_read','Innodb_data_reads','Innodb_pages_read'); +-------------------+----------------+ | VARIABLE_NAME | VARIABLE_VALUE | +-------------------+----------------+ | HANDLER_READ_NEXT | 11111 | #請求讀的行數(shù) | INNODB_DATA_READS | 7868409 | #數(shù)據(jù)物理讀的總數(shù) | INNODB_PAGES_READ | 7855239 | #邏輯讀的總數(shù) | LAST_QUERY_COST | 10.499000 | #SQL語句的成本COST,主要包括IO_COST和CPU_COST。 +-------------------+----------------+ 4 rows in set (0.00 sec)
#刪除50w數(shù)據(jù) mysql> delete from user limit 500000; Query OK, 500000 rows affected (3.70 sec) #分析表統(tǒng)計(jì)信息 mysql> analyze table user; +-----------+---------+----------+----------+ | Table | Op | Msg_type | Msg_text | +-----------+---------+----------+----------+ | test.user | analyze | status | OK | +-----------+---------+----------+----------+ 1 row in set (0.01 sec) #重置狀態(tài)變量計(jì)數(shù) mysql> flush status; Query OK, 0 rows affected (0.01 sec) mysql> select id, age ,phone from user where name like 'lyn12%'; Empty set (0.05 sec) mysql> explain select id, age ,phone from user where name like 'lyn12%'; +----+-------------+-------+-------+---------------+----------+---------+------+-------+-----------------------+ | id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra | +----+-------------+-------+-------+---------------+----------+---------+------+-------+-----------------------+ | 1 | SIMPLE | user | range | idx_name | idx_name | 82 | NULL | 22226 | Using index condition | +----+-------------+-------+-------+---------------+----------+---------+------+-------+-----------------------+ 1 row in set (0.00 sec) mysql> select * from information_schema.session_status where variable_name in('Last_query_cost','Handler_read_next','Innodb_pages_read','Innodb_data_reads','Innodb_pages_read'); +-------------------+----------------+ | VARIABLE_NAME | VARIABLE_VALUE | +-------------------+----------------+ | HANDLER_READ_NEXT | 0 | | INNODB_DATA_READS | 7868409 | | INNODB_PAGES_READ | 7855239 | | LAST_QUERY_COST | 10.499000 | +-------------------+----------------+ 4 rows in set (0.00 sec)
操作 | COST | 物理讀次數(shù) | 邏輯讀次數(shù) | 掃描行數(shù) | 返回行數(shù) | 執(zhí)行時(shí)間 |
---|---|---|---|---|---|---|
初始化插入100W | 10.499000 | 7868409 | 7855239 | 22226 | 11111 | 30ms |
100W隨機(jī)刪除50W | 10.499000 | 7868409 | 7855239 | 22226 | 0 | 50ms |
這也說明對普通的大表,想要通過delete數(shù)據(jù)來對表進(jìn)行瘦身是不現(xiàn)實(shí)的,所以在任何時(shí)候不要用delete去刪除數(shù)據(jù),應(yīng)該使用優(yōu)雅的標(biāo)記刪除。
對于一個(gè)大的系統(tǒng)來說,需要根據(jù)業(yè)務(wù)特點(diǎn)去拆分子系統(tǒng),每個(gè)子系統(tǒng)可以看做是一個(gè)service,例如美團(tuán)APP,上面有很多服務(wù),核心的服務(wù)有用戶服務(wù)user-service,搜索服務(wù)search-service,商品product-service,位置服務(wù)location-service,價(jià)格服務(wù)price-service等。每個(gè)服務(wù)對應(yīng)一個(gè)數(shù)據(jù)庫,為該數(shù)據(jù)庫創(chuàng)建單獨(dú)賬號,同時(shí)只授予DML權(quán)限且沒有delete權(quán)限,同時(shí)禁止跨庫訪問。
#創(chuàng)建用戶數(shù)據(jù)庫并授權(quán) create database mt_user charset utf8mb4; grant USAGE, SELECT, INSERT, UPDATE ON mt_user.* to 'w_user'@'%' identified by 't$W*g@gaHTGi123456'; flush privileges;
在MySQL數(shù)據(jù)庫建模規(guī)范中有4個(gè)公共字段,基本上每個(gè)表必須有的,同時(shí)在create_time列要?jiǎng)?chuàng)建索引,有兩方面的好處:
一些查詢業(yè)務(wù)場景都會有一個(gè)默認(rèn)的時(shí)間段,比如7天或者一個(gè)月,都是通過create_time去過濾,走索引掃描更快。
一些核心的業(yè)務(wù)表需要以T +1的方式抽取數(shù)據(jù)倉庫中,比如每天晚上00:30抽取前一天的數(shù)據(jù),都是通過create_time過濾的。
`id` bigint(20) NOT NULL AUTO_INCREMENT COMMENT '主鍵id', `is_deleted` tinyint(4) NOT NULL DEFAULT '0' COMMENT '是否邏輯刪除:0:未刪除,1:已刪除', `create_time` timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP COMMENT '創(chuàng)建時(shí)間', `update_time` timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP ON UPDATE CURRENT_TIMESTAMP COMMENT '修改時(shí)間' #有了刪除標(biāo)記,業(yè)務(wù)接口的delete操作就可以轉(zhuǎn)換為update update user set is_deleted = 1 where user_id = 1213; #查詢的時(shí)候需要帶上is_deleted過濾 select id, age ,phone from user where is_deleted = 0 and name like 'lyn12%';
#1. 創(chuàng)建歸檔表,一般在原表名后面添加_bak。 CREATE TABLE `ota_order_bak` ( `id` bigint(11) NOT NULL AUTO_INCREMENT COMMENT '主鍵', `order_id` varchar(255) DEFAULT NULL COMMENT '訂單id', `ota_id` varchar(255) DEFAULT NULL COMMENT 'ota', `check_in_date` varchar(255) DEFAULT NULL COMMENT '入住日期', `check_out_date` varchar(255) DEFAULT NULL COMMENT '離店日期', `hotel_id` varchar(255) DEFAULT NULL COMMENT '酒店ID', `guest_name` varchar(255) DEFAULT NULL COMMENT '顧客', `purcharse_time` timestamp NULL DEFAULT NULL COMMENT '購買時(shí)間', `create_time` datetime DEFAULT NULL, `update_time` datetime DEFAULT NULL, `create_user` varchar(255) DEFAULT NULL, `update_user` varchar(255) DEFAULT NULL, `status` int(4) DEFAULT '1' COMMENT '狀態(tài) : 1 正常 , 0 刪除', `hotel_name` varchar(255) DEFAULT NULL, `price` decimal(10,0) DEFAULT NULL, `remark` longtext, PRIMARY KEY (`id`), KEY `IDX_order_id` (`order_id`) USING BTREE, KEY `hotel_name` (`hotel_name`) USING BTREE, KEY `ota_id` (`ota_id`) USING BTREE, KEY `IDX_purcharse_time` (`purcharse_time`) USING BTREE, KEY `IDX_create_time` (`create_time`) USING BTREE ) ENGINE=InnoDB DEFAULT CHARSET=utf8 PARTITION BY RANGE (to_days(create_time)) ( PARTITION p201808 VALUES LESS THAN (to_days('2018-09-01')), PARTITION p201809 VALUES LESS THAN (to_days('2018-10-01')), PARTITION p201810 VALUES LESS THAN (to_days('2018-11-01')), PARTITION p201811 VALUES LESS THAN (to_days('2018-12-01')), PARTITION p201812 VALUES LESS THAN (to_days('2019-01-01')), PARTITION p201901 VALUES LESS THAN (to_days('2019-02-01')), PARTITION p201902 VALUES LESS THAN (to_days('2019-03-01')), PARTITION p201903 VALUES LESS THAN (to_days('2019-04-01')), PARTITION p201904 VALUES LESS THAN (to_days('2019-05-01')), PARTITION p201905 VALUES LESS THAN (to_days('2019-06-01')), PARTITION p201906 VALUES LESS THAN (to_days('2019-07-01')), PARTITION p201907 VALUES LESS THAN (to_days('2019-08-01')), PARTITION p201908 VALUES LESS THAN (to_days('2019-09-01')), PARTITION p201909 VALUES LESS THAN (to_days('2019-10-01')), PARTITION p201910 VALUES LESS THAN (to_days('2019-11-01')), PARTITION p201911 VALUES LESS THAN (to_days('2019-12-01')), PARTITION p201912 VALUES LESS THAN (to_days('2020-01-01'))); #2. 插入原表中無效的數(shù)據(jù)(需要跟開發(fā)同學(xué)確認(rèn)數(shù)據(jù)保留范圍) create table tbl_p201808 as select * from ota_order where create_time between '2018-08-01 00:00:00' and '2018-08-31 23:59:59'; #3. 跟歸檔表分區(qū)做分區(qū)交換 alter table ota_order_bak exchange partition p201808 with table tbl_p201808; #4. 刪除原表中已經(jīng)規(guī)范的數(shù)據(jù) delete from ota_order where create_time between '2018-08-01 00:00:00' and '2018-08-31 23:59:59' limit 3000;
#1. 創(chuàng)建中間表 CREATE TABLE `ota_order_2020` (........) ENGINE=InnoDB DEFAULT CHARSET=utf8 PARTITION BY RANGE (to_days(create_time)) ( PARTITION p201808 VALUES LESS THAN (to_days('2018-09-01')), PARTITION p201809 VALUES LESS THAN (to_days('2018-10-01')), PARTITION p201810 VALUES LESS THAN (to_days('2018-11-01')), PARTITION p201811 VALUES LESS THAN (to_days('2018-12-01')), PARTITION p201812 VALUES LESS THAN (to_days('2019-01-01')), PARTITION p201901 VALUES LESS THAN (to_days('2019-02-01')), PARTITION p201902 VALUES LESS THAN (to_days('2019-03-01')), PARTITION p201903 VALUES LESS THAN (to_days('2019-04-01')), PARTITION p201904 VALUES LESS THAN (to_days('2019-05-01')), PARTITION p201905 VALUES LESS THAN (to_days('2019-06-01')), PARTITION p201906 VALUES LESS THAN (to_days('2019-07-01')), PARTITION p201907 VALUES LESS THAN (to_days('2019-08-01')), PARTITION p201908 VALUES LESS THAN (to_days('2019-09-01')), PARTITION p201909 VALUES LESS THAN (to_days('2019-10-01')), PARTITION p201910 VALUES LESS THAN (to_days('2019-11-01')), PARTITION p201911 VALUES LESS THAN (to_days('2019-12-01')), PARTITION p201912 VALUES LESS THAN (to_days('2020-01-01'))); #2. 插入原表中有效的數(shù)據(jù),如果數(shù)據(jù)量在100W左右可以在業(yè)務(wù)低峰期直接插入,如果比較大,建議采用dataX來做,可以控制頻率和大小,之前我這邊用Go封裝了dataX可以實(shí)現(xiàn)自動生成json文件,自定義大小去執(zhí)行。 insert into ota_order_2020 select * from ota_order where create_time between '2020-08-01 00:00:00' and '2020-08-31 23:59:59'; #3. 表重命名 alter table ota_order rename to ota_order_bak; alter table ota_order_2020 rename to ota_order; #4. 插入差異數(shù)據(jù) insert into ota_order select * from ota_order_bak a where not exists (select 1 from ota_order b where a.id = b.id); #5. ota_order_bak改造成分區(qū)表,如果表比較大不建議直接改造,可以先創(chuàng)建好分區(qū)表,通過dataX把導(dǎo)入進(jìn)去即可。 #6. 后續(xù)的歸檔方法 #創(chuàng)建中間普遍表 create table ota_order_mid like ota_order; #交換原表無效數(shù)據(jù)分區(qū)到普通表 alter table ota_order exchange partition p201808 with table ota_order_mid; ##交換普通表數(shù)據(jù)到歸檔表的相應(yīng)分區(qū) alter table ota_order_bak exchange partition p201808 with table ota_order_mid;
這樣原表和歸檔表都是按月的分區(qū)表,只需要?jiǎng)?chuàng)建一個(gè)中間普通表,在業(yè)務(wù)低峰期做兩次分區(qū)交換,既可以刪除無效數(shù)據(jù),又能回收空,而且沒有空間碎片,不會影響表上的索引及SQL的執(zhí)行計(jì)劃。
通過從InnoDB存儲空間分布,delete對性能的影響可以看到,delete物理刪除既不能釋放磁盤空間,而且會產(chǎn)生大量的碎片,導(dǎo)致索引頻繁分裂,影響SQL執(zhí)行計(jì)劃的穩(wěn)定性;
同時(shí)在碎片回收時(shí),會耗用大量的CPU,磁盤空間,影響表上正常的DML操作。
在業(yè)務(wù)代碼層面,應(yīng)該做邏輯標(biāo)記刪除,避免物理刪除;為了實(shí)現(xiàn)數(shù)據(jù)歸檔需求,可以用采用MySQL分區(qū)表特性來實(shí)現(xiàn),都是DDL操作,沒有碎片產(chǎn)生。
另外一個(gè)比較好的方案采用Clickhouse,對有生命周期的數(shù)據(jù)表可以使用Clickhouse存儲,利用其TTL特性實(shí)現(xiàn)無效數(shù)據(jù)自動清理。
“mysql刪除數(shù)據(jù)時(shí)為什么不用delete”的內(nèi)容就介紹到這里了,感謝大家的閱讀。如果想了解更多行業(yè)相關(guān)的知識可以關(guān)注創(chuàng)新互聯(lián)網(wǎng)站,小編將為大家輸出更多高質(zhì)量的實(shí)用文章!
本文標(biāo)題:mysql刪除數(shù)據(jù)時(shí)為什么不用delete
分享路徑:http://muchs.cn/article6/piheog.html
成都網(wǎng)站建設(shè)公司_創(chuàng)新互聯(lián),為您提供網(wǎng)站導(dǎo)航、App開發(fā)、搜索引擎優(yōu)化、自適應(yīng)網(wǎng)站、響應(yīng)式網(wǎng)站、定制網(wǎng)站
聲明:本網(wǎng)站發(fā)布的內(nèi)容(圖片、視頻和文字)以用戶投稿、用戶轉(zhuǎn)載內(nèi)容為主,如果涉及侵權(quán)請盡快告知,我們將會在第一時(shí)間刪除。文章觀點(diǎn)不代表本網(wǎng)站立場,如需處理請聯(lián)系客服。電話:028-86922220;郵箱:631063699@qq.com。內(nèi)容未經(jīng)允許不得轉(zhuǎn)載,或轉(zhuǎn)載時(shí)需注明來源: 創(chuàng)新互聯(lián)