Detailed process of comparing the advantages and disadvantages of using auto-incrementing ID primary key and UUID as primary key in MySQL (testing from one million to ten million table records)-Mysql Tutorial-php.cn

Reason for testing

# A development colleague made a framework in which the primary key is uuid. I suggested to him that mysql should not use uuid and use auto-incrementing primary key. Auto-incrementing primary key is more efficient. He said it is not necessarily high. I said that the index feature of innodb leads to auto-incrementing id. Making the primary key is the most efficient. In order to convince him with actual cases, I prepared to do a detailed test.

As an Internet company, there must be a user table, and the user table UC_USER basically has millions of records. Therefore, the test is carried out based on the quasi-test data based on this table.

The testing process is currently a multi-faceted test of several commonly used types of sql that I think of. Of course, it may not be perfect. Everyone is welcome to leave a message to propose a more complete test plan or test sql statement.

1, Prepare tables and data

UC_USER, auto-increment ID is the primary key, the table structure is similar to the following:

UC_USER_PK_VARCHAR table, string ID is the primary key, using uuid

##CREATE TABLE `UC_USER` (

`ID` bigint(20) NOT NULL AUTO_INCREMENT COMMENT 'Primary Key', `USER_NAME` varchar(100) DEFAULT NULL COMMENT 'Username',
`USER_PWD` varchar(200) DEFAULT NULL COMMENT 'Password',
`BIRTHDAY` datetime DEFAULT NULL COMMENT 'Birthday',
`NAME` varchar(200) DEFAULT NULL COMMENT 'Name',
`USER_ICON` varchar(500) DEFAULT NULL COMMENT 'Avatar picture',
`SEX` char(1 ) DEFAULT NULL COMMENT 'Gender, 1: Male, 2: Female, 3: Confidential',
`NICKNAME` varchar(200) DEFAULT NULL COMMENT 'Nickname',
`STAT` varchar(10) DEFAULT NULL COMMENT 'User status, 01: normal, 02: frozen',
`USER_MALL` bigint(20) DEFAULT NULL COMMENT 'Current MALL',
`LAST_LOGIN_DATE` datetime DEFAULT NULL COMMENT 'Last login time',
`LAST_LOGIN_IP` varchar(100) DEFAULT NULL COMMENT 'Last login IP',
`SRC_OPEN_USER_ID` bigint(20) DEFAULT NULL COMMENT 'Source of joint login',
`EMAIL` varchar(200) DEFAULT NULL COMMENT 'Mailbox',
`MOBILE` varchar(50) DEFAULT NULL COMMENT 'Mobile phone',
`IS_DEL` char(1) DEFAULT '0' COMMENT 'Whether to delete',
`IS_EMAIL_CONFIRMED` char(1 ) DEFAULT '0' COMMENT 'Whether to bind an email',
`IS_PHONE_CONFIRMED` char(1) DEFAULT '0' COMMENT 'Whether to bind a mobile phone',
`CREATER` bigint(20) DEFAULT NULL COMMENT 'Create People',
`CREATE_DATE` datetime DEFAULT CURRENT_TIMESTAMP COMMENT 'Registration time',
`UPDATE_DATE` datetime DEFAULT CURRENT_TIMESTAMP COMMENT 'Modification date',
`PWD_INTENSITY` char(1) DEFAULT NULL COMMENT 'Password strength' ,
`MOBILE_TGC` char(64) DEFAULT NULL COMMENT 'Mobile phone login ID',
`MAC` char(64) DEFAULT NULL COMMENT 'mac address',
`SOURCE` char(1) DEFAULT ' 0' COMMENT '1:WEB,2:IOS,3:ANDROID,4:WIFI,5:Management system, 0:Unknown',
`ACTIVATE` char(1) DEFAULT '1' COMMENT 'Activate, 1: Activation, 0: Not activated',
`ACTIVATE_TYPE` char(1) DEFAULT '0' COMMENT 'Activation type, 0: automatic, 1: manual',
PRIMARY KEY (`ID`),
UNIQUE KEY `USER_NAME` (`USER_NAME`),
KEY `MOBILE` (`MOBILE`),
KEY `IDX_MOBILE_TGC` (`MOBILE_TGC`,`ID`),
KEY `IDX_EMAIL` (` EMAIL`,`ID`),
KEY `IDX_CREATE_DATE` (`CREATE_DATE`,`ID`),
KEY `IDX_UPDATE_DATE` (`UPDATE_DATE`)
) ENGINE=InnoDB AUTO_INCREMENT=7122681 DEFAULT CHARSET= utf8 COMMENT='User Table'

CREATE TABLE `UC_USER_PK_VARCHAR_1` (
`ID` varchar(36) CHARACTER SET utf8mb4 NOT NULL DEFAULT '0' COMMENT 'Primary Key' ,
`USER_NAME` varchar(100) DEFAULT NULL COMMENT 'Username',
`USER_PWD` varchar(200) DEFAULT NULL COMMENT 'Password',
`BIRTHDAY` datetime DEFAULT NULL COMMENT ' Birthday',
`NAME` varchar(200) DEFAULT NULL COMMENT 'Name',
`USER_ICON` varchar(500) DEFAULT NULL COMMENT 'Avatar picture',
`SEX` char(1) DEFAULT NULL COMMENT 'Gender, 1: Male, 2: Female, 3: Confidential',
`NICKNAME` varchar(200) DEFAULT NULL COMMENT 'Nickname',
`STAT` varchar(10) DEFAULT NULL COMMENT 'User status , 01: Normal, 02: Freeze',
`USER_MALL` bigint(20) DEFAULT NULL COMMENT 'Current MALL',
`LAST_LOGIN_DATE` datetime DEFAULT NULL COMMENT 'Last login time',
`LAST_LOGIN_IP `varchar(100) DEFAULT NULL COMMENT 'Last login IP',
`SRC_OPEN_USER_ID` bigint(20) DEFAULT NULL COMMENT 'Source of joint login',
`EMAIL` varchar(200) DEFAULT NULL COMMENT 'Mailbox' ,
`MOBILE` varchar(50) DEFAULT NULL COMMENT 'Mobile phone',
`IS_DEL` char(1) DEFAULT '0' COMMENT 'Whether to delete',
`IS_EMAIL_CONFIRMED` char(1) DEFAULT ' 0' COMMENT 'Whether to bind an email',
`IS_PHONE_CONFIRMED` char(1) DEFAULT '0' COMMENT 'Whether to bind a mobile phone',
`CREATER` bigint(20) DEFAULT NULL COMMENT 'Creator',
`CREATE_DATE` datetime DEFAULT CURRENT_TIMESTAMP COMMENT 'Registration time',
`UPDATE_DATE` datetime DEFAULT CURRENT_TIMESTAMP COMMENT 'Modification date',
`PWD_INTENSITY` char(1) DEFAULT NULL COMMENT 'Password strength',
`MOBILE_TGC` char(64) DEFAULT NULL COMMENT 'Mobile phone login ID',
`MAC` char(64) DEFAULT NULL COMMENT 'mac address',
`SOURCE` char(1) DEFAULT '0' COMMENT '1:WEB,2:IOS,3:ANDROID,4:WIFI,5:Management system, 0:Unknown',
`ACTIVATE` char(1) DEFAULT '1' COMMENT 'Activate, 1: Activate, 0 : Not activated',
`ACTIVATE_TYPE` char(1) DEFAULT '0' COMMENT 'Activation type, 0: automatic, 1: manual',
PRIMARY KEY (`ID`),
UNIQUE KEY ` USER_NAME` (`USER_NAME`),
KEY `MOBILE` (`MOBILE`),
KEY `IDX_MOBILE_TGC` (`MOBILE_TGC`,`ID`),
KEY `IDX_EMAIL` (`EMAIL`, `ID`),
KEY `IDX_CREATE_DATE` (`CREATE_DATE`,`ID`),
KEY `IDX_UPDATE_DATE` (`UPDATE_DATE`)
) ENGINE=InnoDB DEFAULT CHARSET=utf8 COMMENT='User table ';

2、500WData test

2.1 Enter 500W data, auto-increment ID Save half the disk Space

Determine the amount of data in the two tables

Table with auto-increment id as the primary key

mysql> select count(1) from UC_USER;

+----------+

| count(1) |

+----- -----+

| 5720112 |

+----------+

1 row in set (0.00 sec)

mysql>

# Table with uuid as primary key

mysql> select count(1) from UC_USER_PK_VARCHAR_1;

+----------+

| count(1) |

+----------+

| 5720112 |

+----------+

1 row in set (1.91 sec)

Judging from the space capacity occupied, the auto-increment ID is about half smaller than the UUID.

Primary key type	Data file size	Occupied capacity
Auto-increment ID	-rw-rw---- 1 mysql mysql 2.5G Aug 11 18:29 UC_USER.ibd	2.5 G
UUID	-rw-rw---- 1 mysql mysql 5.4G Aug 15 15:11 UC_USER_PK_VARCHAR_1.ibd	5.4 G

2.2 Single data index query , the self-increment id and uuid are not much different

##SELECT SQL_NO_CACHE t.* FROM test.`UC_USER` t WHERE t.`MOBILE` ='14782121512';##UUIDSELECT SQL_NO_CACHE t.* FROM test.`UC_USER` t WHERE t.`CREATE_DATE`='2013-11-24 10:26:36' ;0.139SELECT SQL_NO_CACHE t.* FROM test.`UC_USER_PK_VARCHAR_1` t WHERE t.`CREATE_DATE`='2013-11-24 10 :26:43' ;0.126

Primary key type

##SQL statement

Execution time ( Seconds)

Auto-increment ID

##0.118

SELECT SQL_NO_CACHE t .* FROM test.`UC_USER_PK_VARCHAR_1` t WHERE t.`MOBILE` ='14782121512';

0.117

##Auto-increment ID

SELECT SQL_NO_CACHE t.* FROM test.`UC_USER` t WHERE t.`MOBILE` IN( '14782121512','13761460105');

0.049

UUID

SELECT SQL_NO_CACHE t.* FROM test.`UC_USER_PK_VARCHAR_1` t WHERE t.`MOBILE` IN ('14782121512','13761460105');

0.040

##自increment ID

UUID

2.3 RangelikeQuery, self-incrementIDPerformance is better than UUID

##Auto-increment IDUUID (3) Range query 200 pieces of data, auto-increment ID performance is better than UUIDAuto-increment ID Range query total quantity, auto-increment ID is better than UUID

##Primary key type

SQL statement

Execution time (seconds)

(1) Fuzzy range query 1000 pieces of data, auto-increment ID performance is better than UUID

Auto-increment ID

SELECT SQL_NO_CACHE t.* FROM test.`UC_USER` t WHERE t.`MOBILE` LIKE '147%' LIMIT 1000;

1.784

UUID

SELECT SQL_NO_CACHE t.* FROM test.`UC_USER_PK_VARCHAR_1` t WHERE t.`MOBILE` LIKE '147%' LIMIT 1000;

3.196

#(2) Query 20 pieces of data in the date range. The auto-increment ID is slightly weaker than UUID

SELECT SQL_NO_CACHE t.* FROM test.`UC_USER` t WHERE t.`CREATE_DATE` > '2016-08-01 10:26:36' ORDER BY t.`UPDATE_DATE` DESC LIMIT 20;

0.601

SELECT SQL_NO_CACHE t.* FROM test.`UC_USER_PK_VARCHAR_1` t WHERE t.`CREATE_DATE` > '2016-08-01 10:26:36' ORDER BY t.`UPDATE_DATE` DESC LIMIT 20;

0.543

SELECT SQL_NO_CACHE t.* FROM test.`UC_USER` t WHERE t.`CREATE_DATE` > '2016-07-01 10:26:36' ORDER BY t.`UPDATE_DATE` DESC LIMIT 200;

2.314

##UUID

SELECT SQL_NO_CACHE t.* FROM test.`UC_USER_PK_VARCHAR_1` t WHERE t.`CREATE_DATE` > '2016-07-01 10:26:36' ORDER BY t.`UPDATE_DATE` DESC LIMIT 200;

3.229

Auto-increment ID

SELECT SQL_NO_CACHE COUNT(1) FROM test.`UC_USER` t WHERE t.`CREATE_DATE` > ' 2016-07-01 10:26:36' ;

0.514

UUID

SELECT SQL_NO_CACHE COUNT(1) FROM test.`UC_USER_PK_VARCHAR_1` t WHERE t.`CREATE_DATE` > '2016-07-01 10:26:36' ;

1.092

PS: In the presence of cache, there is no small difference in execution efficiency between the two.

2.4 Write test, auto-increment ID is 4 times

##Primary key type##UPDATE test.`UC_USER` t SET t.`MOBILE_TGC`='T2' WHERE t.`CREATE_DATE` > ' 2016-05-03 10:26:36' AND t.`CREATE_DATE` <'2016-05-04 00:00:00' ;UUID0.105

SQL statement	Execution Time (seconds)
		#Auto-increment ID
##1.419		##UPDATE test.`UC_USER_PK_VARCHAR_1` t SET t.`MOBILE_TGC`='T2' WHERE t.`CREATE_DATE` > ; '2016-05-03 10:26:36' AND t.`CREATE_DATE` <'2016-05-04 00:00:00' ;
5.639
	Increase ID	##INSERT INTO test.`UC_USER`( ID, `USER_NAME`, `USER_PWD`, `BIRTHDAY`, `NAME`, `USER_ICON `, `SEX`, `NICKNAME`, `STAT`, `USER_MALL`, `LAST_LOGIN_DATE`, `LAST_LOGIN_IP`, `SRC_OPEN_USER_ID`, `EMAIL`, `MOBILE`, `IS_DEL`, `IS_EMAIL _CONFIRMED`, `IS_PHONE_CONFIRMED`, `CREATER`, `CREATE_DATE`, `UPDATE_DATE`, `PWD_INTENSITY`, `MOBILE_TGC`, `MAC`, `SOURCE`, `ACTIVATE`, `ACTIVATE_TYPE` ) SELECT NULL, `USER_NAME `,8 ), `USER_PWD`, `BIRTHDAY`, `NAME`, `USER_ICON`, `SEX`, `NICKNAME`, `STAT`, `USER_MALL`, `LAST_LOGIN_DATE`, `LAST_LOGIN_IP`, `SRC_OPEN_USER_ ID`, `EMAIL`, CONCAT('110',TRIM(`MOBILE`)), `IS_DEL`, `IS_EMAIL_CONFIRMED`, `IS_PHONE_CONFIRMED`, `CREATER`, `CREATE_DATE`, `UPDATE_DATE`, `PWD_INTENSITY`, `MOBILE_TGC`, `MAC`, `SOURCE`, `ACTIVATE`, `ACTIVATE_TYPE` FROM `test`.`UC_USER_1` LIMIT 100;
	UUID	INSERT INTO test.`UC_USER_PK_VARCHAR_1`( ID, `USER_NAME`, `USER_PWD`, `BIRTHDAY`, `NAME`, `USER_ICON`, `SEX`, `NICKNAME`, `STAT`, `USER_MALL`, `LAST_LOGIN_DATE`, `LAST_LOGIN_IP`, `SRC_OPEN_USER_ID`, `EMAIL`, `MOBILE`, `IS_DEL`, `IS_EMAIL_CONFIRMED`, `IS_PHONE_CONFIRMED`, `CREATER`, `CREATE_DATE`, `UPDATE_DATE`, `PWD_INTENSITY`, `MOBILE_TGC`, `MAC`, `SOURCE`, `ACTIVATE`, `ACTIVATE_TYPE` ) SELECT UUID(), CONCAT('110',`USER_NAME`,8), `USER_PWD`, `BIRTHDAY`, `NAME`, `USER_ICON`, `SEX`, `NICKNAME`, `STAT`, `USER_MALL`, `LAST_LOGIN_DATE`, `LAST_LOGIN_IP`, `SRC_OPEN_USER_ID`, `EMAIL`, CONCAT('110',TRIM(`MOBILE`)), `IS_DEL`, `IS_EMAIL_CONFIRMED`, `IS_PHONE_CONFIRMED`, `CREATER`, `CREATE_DATE`, `UPDATE_DATE`, `PWD_INTENSITY`, `MOBILE_TGC`, `MAC`, `SOURCE`, `ACTIVATE`, `ACTIVATE_TYPE` FROM `test`.`UC_USER_1` LIMIT 100;	0.424

2.5、备份和恢复，自增ID性能优于UUID

主键类型	SQL语句	执行时间 (秒)
Mysqldump备份
自增ID	time mysqldump -utim -ptimgood -h192.168.121.63 test UC_USER_500> UC_USER_500.sql	28.59秒
UUID	time mysqldump -utim -ptimgood -h192.168.121.63 test UC_USER_PK_VARCHAR_500> UC_USER_PK_VARCHAR_500.sql	31.08秒
MySQL恢复
自增ID	time mysql -utim -ptimgood -h192.168.121.63 test < UC_USER_500.sql	7m36.601s
UUID	time mysql -utim -ptimgood -h192.168.121.63 test < UC_USER_PK_VARCHAR_500.sql	9m42.472s

3、500WSummary

Under the test of 500W record table:

(1) For ordinary single or about 20 record retrieval, the uuid is the primary key. The efficiency is almost the same;

(2) But for range queries, especially for hundreds or thousands of records, the efficiency of auto-incrementing ids is greater than uuid;

(3) In range queries When statistics are summarized, the efficiency of auto-incrementing id is greater than that of uuid;

(4) In terms of storage, the storage space occupied by auto-incrementing id is 1/2 of uuid;

(5 ) In terms of backup and recovery, the auto-incrementing ID primary key is slightly better than UUID.

4、1000WData test

4.1 Enter1000WData record, check the storage space

Auto-incrementidTable with primary key

mysql> use test;

Database changed

mysql> select count(1) from UC_USER_1;

+----------+

| count(1) |

+----------+

| 10698102 |

+--------- -+

1 row in set (27.42 sec)

# uuidTable with primary key

mysql> select count(1) from UC_USER_PK_VARCHAR_1;

+----------+

| count(1) |

+- ---------+

| 10698102 |

+----------+

1 row in set (0.00 sec )

mysql>

##occupied In terms of space capacity, auto-increment ID is about half smaller than UUID:

Auto-increment ID-rw-rw---- 1 mysql mysql 4.2G Aug 20 23:08 UC_USER_1.ibd 4.2 GUUID-rw-rw---- 1 mysql mysql 8.8G Aug 20 18:20 UC_USER_PK_VARCHAR_1.ibd8.8 G

4.2 Single data is indexed and incrementedid and uuidThe efficiency ratio is: (2~3):1

##Primary key type	Data file size	Occupied capacity

Auto-increment IDUUID#Small range querySELECT SQL_NO_CACHE t.* FROM test.`UC_USER_1` t WHERE t.`MOBILE` IN( '14782121512 ','13761460105');0.050SELECT SQL_NO_CACHE t.* FROM test.`UC_USER_PK_VARCHAR_1` t WHERE t.`MOBILE` IN('14782121512','13761460105');SELECT SQL_NO_CACHE t.* FROM test.`UC_USER_1` t WHERE t.`CREATE_DATE`='2013-11-24 10:26:36' ;SELECT SQL_NO_CACHE t.* FROM test.`UC_USER_PK_VARCHAR_1` t WHERE t.`CREATE_DATE`='2013 -11-24 10:26:43' ;

4.3 RangelikeQuery, self-incrementID performance is better than UUID, ratio(1.5~2):1

Primary key type	##SQL statement	Execution time ( Seconds)
##Single record query
##SELECT SQL_NO_CACHE t.* FROM test.`UC_USER_1` t WHERE t.`MOBILE` ='14782121512';	0.069
##SELECT SQL_NO_CACHE t.* FROM test.`UC_USER_PK_VARCHAR_1` t WHERE t.`MOBILE` ='14782121512';	##0.274
Auto-increment ID
		#UUID
0.151		Query based on date
Auto-increment ID
0.269		UUID
0.810

Auto-increment ID SELECT SQL_NO_CACHE t.* FROM test.`UC_USER_1` t WHERE t.`CREATE_DATE` > '2016-07-01 10:26:36' ORDER BY t.`UPDATE_DATE` DESC LIMIT 200;1.569##UUIDAuto-increment IDUUID

##Primary key type

SQL Statement

Execution time (seconds)

(1) Fuzzy range query 1000 pieces of data, auto-increment ID performance is better than UUID

Auto-increment ID

SELECT SQL_NO_CACHE t.* FROM test.`UC_USER` t WHERE t.`MOBILE` LIKE '147%' LIMIT 1000;

2.398

UUID

SELECT SQL_NO_CACHE t.* FROM test.`UC_USER_PK_VARCHAR_1` t WHERE t.`MOBILE` LIKE '147%' LIMIT 1000;

5.872

(2) Date range query 20 pieces of data, the auto-increment ID is slightly weaker than UUID

Auto-increment ID

SELECT SQL_NO_CACHE t.* FROM test.`UC_USER_1` t WHERE t.` CREATE_DATE` > '2016-08-01 10:26:36' ORDER BY t.`UPDATE_DATE` DESC LIMIT 20;

0.765

UUID

SELECT SQL_NO_CACHE t.* FROM test.`UC_USER_PK_VARCHAR_1` t WHERE t.`CREATE_DATE` > '2016-08-01 10:26 :36' ORDER BY t.`UPDATE_DATE` DESC LIMIT 20;

1.090

# #(3) Range query 200 pieces of data, auto-increment ID performance is better than UUID

SELECT SQL_NO_CACHE t.* FROM test.`UC_USER_PK_VARCHAR_1` t WHERE t.`CREATE_DATE` > '2016-07-01 10:26:36' ORDER BY t.`UPDATE_DATE` DESC LIMIT 200;

2.597

Range query total quantity, auto-increment ID is better than UUID

SELECT SQL_NO_CACHE COUNT(1) FROM test.`UC_USER_1` t WHERE t.`CREATE_DATE` > '2016-07-01 10:26:36' ;

1.129

SELECT SQL_NO_CACHE COUNT(1) FROM test.`UC_USER_PK_VARCHAR_1 ` t WHERE t.`CREATE_DATE` > '2016-07-01 10:26:36' ;

##2.302

4.4 Write test, auto-increment ID More efficient than UUID, ratio(3~10):1

Increase ID UPDATE test.`UC_USER_1` t SET t.`MOBILE_TGC`='T2' WHERE t.`CREATE_DATE` > '2016-05-03 10:26:36' AND t.`CREATE_DATE` <'2016-05- 04 00:00:00' ;2.685#UUID##Enter data

Primary key type	##SQL statement	Execution time (seconds)
##Modify one day’s record

UPDATE test.`UC_USER_PK_VARCHAR_1` t SET t.`MOBILE_TGC`='T2' WHERE t.`CREATE_DATE` > '2016-05-03 10:26:36' AND t.`CREATE_DATE` <'2016- 05-04 00:00:00' ;	##26.521
Increase ID
INSERT INTO test.`UC_USER_1`( ID, `USER_NAME`, `USER_PWD`, `BIRTHDAY`, `NAME`, `USER_ICON`, `SEX`, `NICKNAME`, `STAT`, `USER_MALL`, `LAST_LOGIN_DATE`, `LAST_LOGIN_IP`, `SRC_OPEN_USER_ID`, `EMAIL`, `MO BILE`, `IS_DEL `, `IS_EMAIL_CONFIRMED`, `IS_PHONE_CONFIRMED`, `CREATER`, `CREATE_DATE`, `UPDATE_DATE`, `PWD_INTENSITY`, `MOBILE_TGC`, `MAC`, `SOURCE`, `ACTIVATE`, `ACTIVATE _TYPE` ) SELECT NULL, CONCAT ; `Last_login_ip `, `SRC_OPEN_USER_ID`, `EMAIL`, CONCAT('110',TRIM(`MOBILE`)), `IS_DEL`, `IS_EMAIL_CONFIRMED`, `IS_PHONE_CONFIRMED`, `CREATER`, `CREATE_DATE`, `UPDATE_DATE`, `PWD_INTENSITY `, `MOBILE_TGC`, `MAC`, `SOURCE`, `ACTIVATE`, `ACTIVATE_TYPE` FROM `test`.`UC_USER_1` LIMIT 100;	0.534	UUID	INSERT INTO test.`UC_USER_PK_VARCHAR_1`( ID, `USER_NAME`, `USER_PWD`, `BIRTHDAY`, `NAME`, `USER_ICON`, `SEX`, `NICKNAME`, `STAT`, `USER_MALL`, `LAST_LOGIN_DATE`, `LAST_LOGIN_IP`, `SRC_OPEN_USER_ID`, `EMAIL`, `MOBILE`, `IS_DEL`, `IS_EMAIL_CONFIRMED`, `IS_PHONE_CONFIRMED`, `CREATER`, `CREATE_DATE`, `UPDATE_DATE`, `PWD_INTENSITY`, `MOBILE_TGC`, `MAC`, `SOURCE`, `ACTIVATE`, `ACTIVATE_TYPE` ) SELECT UUID(), CONCAT('110',`USER_NAME`,8), `USER_PWD`, `BIRTHDAY`, `NAME`, `USER_ICON`, `SEX`, `NICKNAME`, `STAT`, `USER_MALL`, `LAST_LOGIN_DATE`, `LAST_LOGIN_IP`, `SRC_OPEN_USER_ID`, `EMAIL`, CONCAT('110',TRIM(`MOBILE`)), `IS_DEL`, `IS_EMAIL_CONFIRMED`, `IS_PHONE_CONFIRMED`, `CREATER`, `CREATE_DATE`, `UPDATE_DATE`, `PWD_INTENSITY`, `MOBILE_TGC`, `MAC`, `SOURCE`, `ACTIVATE`, `ACTIVATE_TYPE` FROM `test`.`UC_USER_1` LIMIT 100;	1.716

4.5、备份和恢复，自增ID性能优于UUID

主键类型	SQL语句	执行时间 (秒)
Mysqldump备份
自增ID	time mysqldump -utim -ptimgood -h192.168.121.63 test UC_USER_1> UC_USER_1.sql	0m50.548s
UUID	time mysqldump -utim -ptimgood -h192.168.121.63 test UC_USER_PK_VARCHAR_1> UC_USER_PK_VARCHAR_1.sql	0m58.590s
MySQL恢复
自增ID	time mysql -utim -ptimgood -h192.168.121.63 test < UC_USER_1.sql	17m30.822s
UUID	time mysql -utim -ptimgood -h192.168.121.63 test < UC_USER_PK_VARCHAR_1.sql	23m6.360s

5、1000WSummary

Under the test of 1000W record table:

(1) For ordinary single or about 20 record retrieval, the efficiency of auto-increasing primary key is 2 to 3 times that of uuid primary key ;

(2) However, for range queries, especially for hundreds or thousands of records, the efficiency of auto-incrementing ids is greater than that of uuid;

(3) When doing statistical summary for range queries , the efficiency of the auto-incrementing id primary key is 1.5 to 2 times that of the uuid primary key;

(4) In terms of storage, the storage space occupied by the auto-incrementing id is 1/2 of uuid;

( 5) In terms of writing, the efficiency of the auto-incrementing ID primary key is 3 to 10 times that of the UUID primary key. The difference is obvious, especially when updating data within a small range.

(6) In terms of backup and recovery, the auto-incrementing ID primary key is slightly better than UUID.

6、MySQLDistributed Architecture trade-offs

Distributed architecture means that the uniqueness of the primary key of a table needs to be maintained in multiple instances. At this time, the ordinary single-table self-increasing ID primary key is not suitable, because multiple mysql instances will encounter the problem of global uniqueness of the primary key.

##6.1、Auto-incrementID Primary key+ step size, suitable for medium-scale distributed scenarios

On the master of each cluster node group, set (auto_increment_increment), stagger the starting point of each cluster by 1, and choose a step size larger than the number of split clusters that is basically impossible to achieve in the future, so as to achieve the effect of relatively segmenting the ID to meet the global unique effect.

The advantages are: simple implementation, simple post-maintenance, and transparent to the application.

The disadvantage is: the first setup is relatively complicated, because sufficient step length needs to be calculated for future business development;

Planning:

For example, if a total of N node groups are planned, then the i-th node group The configuration of my.cnf is:

auto_increment_offset i

auto_increment_increment N

If you plan 48 node groups, N is 48, and now configure the 8th Node group, this i is 8, the configuration in my.cnf of the 8th node group is:

auto_increment_offset 8

auto_increment_increment 48

6.2、UUID, suitable for small-scale distributed environment

For Innodb engine of the main key type, the data will be sorted according to the main key. Due to the disorder of UUID, InnoDB will produce huge IO pressure, and because the indexes and data are stored together, the string is made by the string, and the string is made by the string. The primary key will double the storage space.

During storage and retrieval, innodb will physically sort the primary keys, which is good news for auto_increment_int, because the position of the primary key inserted later is always at the end. But for uuid, this is bad news, because uuid is messy, and the position of the primary key inserted each time is uncertain. It may be at the beginning or in the middle. When performing physical sorting of primary keys, it will inevitably cause a large number of IO operations affect efficiency. When the amount of data continues to grow, especially when the amount of data exceeds tens of millions of records, the read and write performance drops dramatically.

Advantages: The construction is relatively simple and does not require the uniqueness of the primary key.

Disadvantages: takes up twice the storage space (it will cost 2 times more to store a piece of light on the cloud), and later Reading and writing performance drops drastically.

6.3, Snowflake algorithm creates global self-made Added ID, suitable for distributed scenarios in big data environments

The open source distributed ID algorithm snowflake (Java version) announced by twitter

IdWorker.java：

##package com.demo.elk;

import org.slf4j.Logger;

import org.slf4j.LoggerFactory;

public class IdWorker {

protected static final Logger LOG = LoggerFactory.getLogger(IdWorker.class);

private long workerId;

private long datacenterId;

private long sequence = 0L;

private long twepoch = 1288834974657L;

private long workerIdBits = 5L;

private long datacenterIdBits = 5L;

private long maxWorkerId = -1L ^ (-1L << workerIdBits);

private long maxDatacenterId = -1L ^ (-1L << datacenterIdBits);

private long sequenceBits = 12L;

private long workerIdShift = sequenceBits;

private long datacenterIdShift = sequenceBits + workerIdBits;

private long timestampLeftShift = sequenceBits + workerIdBits + datacenterIdBits;

private long sequenceMask = -1L ^ (-1L << sequenceBits);

private long lastTimestamp = -1L;

public IdWorker(long workerId, long datacenterId) {

// sanity check for workerId

if (workerId > maxWorkerId || workerId < 0) {

throw new IllegalArgumentException(String.format("worker Id can't be greater than %d or less than 0", maxWorkerId));

}

if (datacenterId > maxDatacenterId || datacenterId < 0) {

throw new IllegalArgumentException(String.format("datacenter Id can't be greater than %d or less than 0", maxDatacenterId));

}

this.workerId = workerId;

this.datacenterId = datacenterId;

LOG.info(String.format("worker starting. timestamp left shift %d, datacenter id bits %d, worker id bits %d, sequence bits %d, workerid %d", timestampLeftShift, datacenterIdBits, workerIdBits, sequenceBits, workerId));

}

public synchronized long nextId() {

long timestamp = timeGen();

if (timestamp < lastTimestamp) {

LOG.error(String.format("clock is moving backwards. Rejecting requests until %d.", lastTimestamp));

throw new RuntimeException(String.format("Clock moved backwards. Refusing to generate id for %d milliseconds", lastTimestamp - timestamp));

}

if (lastTimestamp == timestamp) {

sequence = (sequence + 1) & sequenceMask;

if (sequence == 0) {

timestamp = tilNextMillis(lastTimestamp);

}

} else {

sequence = 0L;

}

lastTimestamp = timestamp;

return ((timestamp - twepoch) << timestampLeftShift) | (datacenterId << datacenterIdShift) | (workerId << workerIdShift) | sequence;

}

protected long tilNextMillis(long lastTimestamp) {

long timestamp = timeGen();

while (timestamp <= lastTimestamp) {

timestamp = timeGen();

}

return timestamp;

}

protected long timeGen() {

return System.currentTimeMillis();

}

测试生成ID的测试类，IdWorkerTest.java：

package com.demo.elk;

import java.util.HashSet;

import java.util.Set;

public class IdWorkerTest {

static class IdWorkThread implements Runnable {

private Set set;

private IdWorker idWorker;

public IdWorkThread(Set set, IdWorker idWorker) {

this.set = set;

this.idWorker = idWorker;

}

public void run() {

while (true) {

long id = idWorker.nextId();

System.out.println(" real id:" + id);

if (!set.add(id)) {

System.out.println("duplicate:" + id);

}

public static void main(String[] args) {

Set set = new HashSet();

final IdWorker idWorker1 = new IdWorker(0, 0);

final IdWorker idWorker2 = new IdWorker(1, 0);

Thread t1 = new Thread(new IdWorkThread(set, idWorker1));

Thread t2 = new Thread(new IdWorkThread(set, idWorker2));

t1.setDaemon(true);

t2.setDaemon(true);

t1.start();

t2.start();

try {

Thread.sleep(30000);

} catch (InterruptedException e) {

e.printStackTrace();

}

7，Summary

（1) Single instance or single node group:

After 500W and 1000W stand-alone table testing, compared with UUID, auto-increment ID is The performance of incremental ID primary key is higher than that of UUID, and the disk storage cost is half of that of UUID. Therefore, on a single instance or a single node group, use the auto-incrementing ID as the preferred primary key.

（2）Distributed architecture scenario:

20 distributed scenarios under the node group, in order to quickly achieve deployment, you can use multi -flower storage costs and sacrifice some performance to use the UUID main key to quickly deploy; For medium-scale distributed scenarios with 20 to 200 node groups, a faster solution of self-increasing ID + step size can be used.

# The distributed scenario under the big data of the node group above the node group, you can learn from the global self -increase ID of the Twitter Snowflake algorithm structure as the primary key.

The above is the detailed process of comparing the advantages and disadvantages of using auto-incrementing ID primary key and UUID as the primary key in MySQL (testing from millions to tens of millions of table records). For more related content, please pay attention to the PHP Chinese website (m.sbmmt.com)!