#19 MySQL JSON

2019-09-05

MySQL 5.7 新增了一个 JSON 类型,它的设计目标不是简单地把 JSON 当作 TEXT 存储,而是采用内部二进制格式保存 JSON 文档,从而支持结构化访问、校验和部分索引能力。
PS: 8.0 增加了 JSON_TABLE()、JSON_VALUE()、JSON_OVERLAPS()、MEMBER OF()、JSON Schema 验证等能力,同时 JSON 索引和查询能力也进一步增强。

#18 MySQL 数据类型总结

2019-08-25

数值

  • bit [1 - 64]

  • tinyint 1

  • smallint 2
  • mediumint 3
  • int 4
  • bigint 8

  • float 4 浮点(单精度)

  • double 8 浮点(双精度)
  • decimal(m, d) max(m, d) + 2 定点

别名 Synonyms:

  • integer -> int
  • bool / boolean -> tinyint(1)
  • dec / numeric / fixed -> decimal
  • double precision / real -> double

PS: 如果开启 REAL_AS_FLOAT 模式,REAL 就变成了 FLOAT 的别名。

字符串/文本

  • char
  • varchar

  • tinytext

  • text
  • mediumtext
  • longtext

  • JSON MySQL 5.7 加入

二进制

  • binary
  • varbinary

  • tinyblob

  • blob
  • mediumblob
  • longblob

时间

类型 长度 备注
year 1 四位数:1901 ~ 2155
两位数:00 ~ 69 (2000 ~ 2069) 70 ~ 99 (1970 ~ 1999)
date 3 1000-01-01 ~ 9999-12-31
time 3 -838:59:59.999999 ~ 838:59:59.999999
即:-34d23h ~ 34d23h
datetime 8 1000-01-01 00:00:00.000000 ~
9999-12-31 23:59:59.999999
timestamp 4 1970-01-01 00:00:00 ~
2038-01-19 11:14:07
  1. 用字符串(varchar)表示时间,除了失去数据库这一层的数据类型保证之外,还会在时间比较运算场景下,失去索引命中可能。
  2. 用整型数 bigint(8 字节)表示时间,可以扩大 timestamp 时间范围,但要自己维护数据(其实还是比较好维护的)。
  3. 带时区的时间:timestamp
  4. 带精度的时间:time、datetime、timestamp,精度最大为 6,表示毫秒。比如:timestamp(6)

其他

  • enum
  • set
  • Geometry 系列

货币

  1. 以分为单位 Integer
  2. Decimal,不要用 float,double

参考资料与拓展阅读

#17 Gitlab 从 12.1 版本开始将不再支持 MySQL

2019-07-03

看到新闻,Gitlab 从 12.1 版本开始将不再支持 MySQL,理由是:

Gitlab 支持的另一个数据库是 PostgreSQL,意思是 PostgreSQL 不存在上面的问题。
这也可以看作是二者的部分区别吧!

值得研究研究。

#14 MySQL: wait for table metadata lock

2019-03-29

问题

mysql> status
--------------
mysql  Ver 14.14 Distrib 5.7.25, for Linux (x86_64) using  EditLine wrapper

Connection id:      17190053
Current database:   gkbb
Current user:       root@10.9.165.246
SSL:            Not in use
Current pager:      less
Using outfile:      ''
Using delimiter:    ;
Server version:     5.5.5-10.1.26-MariaDB MariaDB Server
Protocol version:   10
Connection:     10.9.108.125 via TCP/IP
Server characterset:    utf8
Db     characterset:    utf8
Client characterset:    utf8
Conn.  characterset:    utf8
TCP port:       3306
Uptime:         13 days 21 hours 14 min 38 sec

Threads: 276  Questions: 31378648  Slow queries: 212  Opens: 2977  Flush tables: 1  Open tables: 2761  Queries per second avg: 26.155
--------------

mysql> show global variables like "innodb_version";
+----------------+-------------+
| Variable_name  | Value       |
+----------------+-------------+
| innodb_version | 5.6.36-82.1 |
+----------------+-------------+
1 row in set (0.06 sec)

PS: 查看 status 还有一个快捷方式 \s。

编辑测试库表结构(添加字段),卡住,任何操作都不行了,等一个多小时,还是不行。。
还一度怀疑是不是表结构设计问题,字段、数据是不是太多了。

过程

偶尔想起看看会话情况:

SELECT * FROM information_schema.processlist WHERE db = 'mydb';

或命令:

  • mysqladmin -uroot -p123456 processlist
  • mysql -uroot -p123456 -e 'SHOW PROCESSLIST'

看到里面好几个会话的状态都是 wait for table metadata lock,这就有点奇怪了,之前没有见过。

网上的资料显示:

为了在并发环境下维护表元数据的数据一致性,在表上有活动事务(显式或隐式)的时候,不可以对元数据进行写入操作。因此 MySQL 引入了 metadata lock ,来保护表的元数据信息。
因此在对表进行上述操作时,如果表上有活动事务(未提交或回滚),请求写入的会话会等待在 Metadata lock wait 。

如果资料没错,那么就是说,如果有事务没有结束,DDL 操作请求 MDL(metadata lock)时会卡住这张表。

我想起我们的服务中确实存在会话没有关闭的情况。

  1. 用了 SQLAlchemy 做 ORM
  2. 每次查询都使用一个会话,包括 SELECT
  3. 增删改操作都立即 commit 了,SELECT 却没有(记得是有个什么原因特意如此)

合理怀疑:这个查询 SESSION 没有关闭,导致 ALTER 语句进入 MDL 等待状态,然后导致了表无法进行任何操作(包括查询,至于为什么这样,我不知道)。

本地复现

  1. 开两个终端,分别建立 MySQL 连接。
  2. 其中一个终端(A):
  3. SET SESSION auto_commit = 0;
  4. SELECT * FROM test.test LIMIT 1;
  5. 另一个终端(B)只需要:TRUNCATE test.test;,然后发现:卡住了。

PS:

  1. DDL 需要 metadata 锁。
  2. TRUNCATE 属于 DDL,可能因为其非事务性(不支持提交和回滚)。参考:https://dba.stackexchange.com/questions/36607/why-is-truncate-ddl

现在,回到终端 A:

mysql> select * from information_schema.processlist where db = 'test';
+----+------+-----------+------+---------+------+---------------------------------+----------------------------------------------------------------+
| ID | USER | HOST      | DB   | COMMAND | TIME | STATE                           | INFO                                                           |
+----+------+-----------+------+---------+------+---------------------------------+----------------------------------------------------------------+
|  3 | root | localhost | test | Query   |    0 | executing                       | select * from information_schema.processlist where db = 'test' |
|  5 | root | localhost | test | Query   | 6111 | Waiting for table metadata lock | truncate test                                                  |
+----+------+-----------+------+---------+------+---------------------------------+----------------------------------------------------------------+
2 rows in set (0.00 sec)

mysql> select * from information_schema.innodb_trx\G
*************************** 1. row ***************************
                    trx_id: 421232684444408
                 trx_state: RUNNING
               trx_started: 2019-03-29 16:06:14
     trx_requested_lock_id: NULL
          trx_wait_started: NULL
                trx_weight: 0
       trx_mysql_thread_id: 3
                 trx_query: select * from information_schema.innodb_trx
       trx_operation_state: NULL
         trx_tables_in_use: 0
         trx_tables_locked: 0
          trx_lock_structs: 0
     trx_lock_memory_bytes: 1136
           trx_rows_locked: 0
         trx_rows_modified: 0
   trx_concurrency_tickets: 0
       trx_isolation_level: REPEATABLE READ
         trx_unique_checks: 1
    trx_foreign_key_checks: 1
trx_last_foreign_key_error: NULL
 trx_adaptive_hash_latched: 0
 trx_adaptive_hash_timeout: 0
          trx_is_read_only: 0
trx_autocommit_non_locking: 0
1 row in set (0.00 sec)

mysql> show engine innodb status\G
*************************** 1. row ***************************
  Type: InnoDB
  Name:
Status:
=====================================
2019-03-29 19:04:40 0x7f1bcc1d6700 INNODB MONITOR OUTPUT
=====================================
Per second averages calculated from the last 3 seconds
-----------------
BACKGROUND THREAD
-----------------
srv_master_thread loops: 7 srv_active, 0 srv_shutdown, 11228 srv_idle
srv_master_thread log flush and writes: 11234
----------
SEMAPHORES
----------
OS WAIT ARRAY INFO: reservation count 16
OS WAIT ARRAY INFO: signal count 10
RW-shared spins 0, rounds 27, OS waits 12
RW-excl spins 0, rounds 32, OS waits 0
RW-sx spins 0, rounds 0, OS waits 0
Spin rounds per wait: 27.00 RW-shared, 32.00 RW-excl, 0.00 RW-sx
------------
TRANSACTIONS
------------
Trx id counter 54542
Purge done for trx's n:o < 54542 undo n:o < 0 state: running but idle
History list length 53
LIST OF TRANSACTIONS FOR EACH SESSION:
---TRANSACTION 421232684445328, not started
0 lock struct(s), heap size 1136, 0 row lock(s)
---TRANSACTION 421232684443488, not started
0 lock struct(s), heap size 1136, 0 row lock(s)
--------
FILE I/O
--------
I/O thread 0 state: waiting for completed aio requests (insert buffer thread)
I/O thread 1 state: waiting for completed aio requests (log thread)
I/O thread 2 state: waiting for completed aio requests (read thread)
I/O thread 3 state: waiting for completed aio requests (read thread)
I/O thread 4 state: waiting for completed aio requests (read thread)
I/O thread 5 state: waiting for completed aio requests (read thread)
I/O thread 6 state: waiting for completed aio requests (write thread)
I/O thread 7 state: waiting for completed aio requests (write thread)
I/O thread 8 state: waiting for completed aio requests (write thread)
I/O thread 9 state: waiting for completed aio requests (write thread)
Pending normal aio reads: [0, 0, 0, 0] , aio writes: [0, 0, 0, 0] ,
 ibuf aio reads:, log i/o's:, sync i/o's:
Pending flushes (fsync) log: 0; buffer pool: 0
639 OS file reads, 99 OS file writes, 21 OS fsyncs
0.00 reads/s, 0 avg bytes/read, 0.00 writes/s, 0.00 fsyncs/s
-------------------------------------
INSERT BUFFER AND ADAPTIVE HASH INDEX
-------------------------------------
Ibuf: size 1, free list len 0, seg size 2, 4 merges
merged operations:
 insert 0, delete mark 0, delete 0
discarded operations:
 insert 0, delete mark 0, delete 0
Hash table size 34679, node heap has 0 buffer(s)
Hash table size 34679, node heap has 0 buffer(s)
Hash table size 34679, node heap has 0 buffer(s)
Hash table size 34679, node heap has 0 buffer(s)
Hash table size 34679, node heap has 0 buffer(s)
Hash table size 34679, node heap has 0 buffer(s)
Hash table size 34679, node heap has 0 buffer(s)
Hash table size 34679, node heap has 0 buffer(s)
0.00 hash searches/s, 0.00 non-hash searches/s
---
LOG
---
Log sequence number 26417867
Log flushed up to   26417867
Pages flushed up to 26417867
Last checkpoint at  26417858
0 pending log flushes, 0 pending chkp writes
17 log i/o's done, 0.00 log i/o's/second
----------------------
BUFFER POOL AND MEMORY
----------------------
Total large memory allocated 137428992
Dictionary memory allocated 133441
Buffer pool size   8192
Free buffers       7710
Database pages     482
Old database pages 0
Modified db pages  0
Pending reads      0
Pending writes: LRU 0, flush list 0, single page 0
Pages made young 0, not young 0
0.00 youngs/s, 0.00 non-youngs/s
Pages read 446, created 41, written 72
0.00 reads/s, 0.00 creates/s, 0.00 writes/s
No buffer pool page gets since the last printout
Pages read ahead 0.00/s, evicted without access 0.00/s, Random read ahead 0.00/s
LRU len: 482, unzip_LRU len: 0
I/O sum[0]:cur[0], unzip sum[0]:cur[0]
--------------
ROW OPERATIONS
--------------
0 queries inside InnoDB, 0 queries in queue
1 read views open inside InnoDB
Process ID=4492, Main thread ID=139757271107328, state: sleeping
Number of rows inserted 6, updated 0, deleted 0, read 20
0.00 inserts/s, 0.00 updates/s, 0.00 deletes/s, 0.00 reads/s
----------------------------
END OF INNODB MONITOR OUTPUT
============================

1 row in set (0.00 sec)

表明:事务存在,TRUNCATE 锁等待。

如果,kill 3 干掉这个没有 commit 的查询 SESSION,TRUNCATE 就会正常执行下去。

结论

  1. 不管怎样,应该保持事务的短小精干,快速执行和退出。
    PS:业务代码中 SELECT 之前为什么不提交的问题需要进一步检查。
  2. DDL 需要 MDL,而没有结束的事务会阻止 MDL。
    更多细节,需要更多深入了解。

#13 MySQL 分区

2019-02-01
partition_options:
    PARTITION BY
        { [LINEAR] HASH(expr)
        | [LINEAR] KEY [ALGORITHM={1 | 2}] (column_list)
        | RANGE{(expr) | COLUMNS(column_list)}
        | LIST{(expr) | COLUMNS(column_list)} }
    [PARTITIONS num]
    [SUBPARTITION BY
        { [LINEAR] HASH(expr)
        | [LINEAR] KEY [ALGORITHM={1 | 2}] (column_list) }
      [SUBPARTITIONS num]
    ]
    [(partition_definition [, partition_definition] ...)]

partition_definition:
    PARTITION partition_name
        [VALUES
            {LESS THAN {(expr | value_list) | MAXVALUE}
            |
            IN (value_list)}]
        [[STORAGE] ENGINE [=] engine_name]
        [COMMENT [=] 'string' ]
        [DATA DIRECTORY [=] 'data_dir']
        [INDEX DIRECTORY [=] 'index_dir']
        [MAX_ROWS [=] max_number_of_rows]
        [MIN_ROWS [=] min_number_of_rows]
        [TABLESPACE [=] tablespace_name]
        [(subpartition_definition [, subpartition_definition] ...)]

subpartition_definition:
    SUBPARTITION logical_name
        [[STORAGE] ENGINE [=] engine_name]
        [COMMENT [=] 'string' ]
        [DATA DIRECTORY [=] 'data_dir']
        [INDEX DIRECTORY [=] 'index_dir']
        [MAX_ROWS [=] max_number_of_rows]
        [MIN_ROWS [=] min_number_of_rows]
        [TABLESPACE [=] tablespace_name]

分区类型

  • [LINEAR] HASH(expr) 根据值的哈希分区
  • [LINEAR] KEY [ALGORITHM={1 | 2}] (column_list)
  • RANGE{(expr) | COLUMNS(column_list)} 根据值得范围分区
  • LIST{(expr) | COLUMNS(column_list)} 根据不同的值分区

COLUMNS 不限于整数

创建分区

PARTITION BY LIST(column) (
    PARTITION a VALUES IN (a1, a2, a3),
    PARTITION b VALUES IN (b1, b2, b3),
    PARTITION c VALUES IN (c1, c2, c3)
)

PARTITION BY RANGE(column) (
    PARTITION 2012q1 VALUES LESS THAN('2012-04-01'),
    PARTITION 2012q2 VALUES LESS THAN('2012-07-01'),
    PARTITION 2012q3 VALUES LESS THAN('2012-10-01'),
    PARTITION 2012q4 VALUES LESS THAN('2013-01-01')
)

PARTITION BY HASH(column) PARTITIONS 128
PARTITION BY HASH(dayofmonth(date)) PARTITIONS 31

查看分区信息

SELECT * FROM `information_schema`.`PARTITIONS`;

子分区

  1. PARTITION 关键字换成 SUBPARTITION,PARTITIONS 关键字换成 SUBPARTITIONS,接在分区语句后面。
  2. 可以是不同类型。

比如:

PARTITION BY HASH (prod_id) SUBPARTITION BY HASH (cust_id)
PARTITIONS 4 SUBPARTITIONS 4;

脚本

如果是 By Range 分区,一般需要自动创建新的分区,删除久的分区。

比如:

CREATE TABLE `test` (
    `id` INT NOT NULL AUTO_INCREMENT,
    `date` DATE NOT NULL,
    `key` VARCHAR(50) NOT NULL COLLATE 'utf8mb4_general_ci',
    `value` VARCHAR(300) NOT NULL COLLATE 'utf8mb4_general_ci',
    `create_time` DATETIME NOT NULL DEFAULT CURRENT_TIMESTAMP,
    PRIMARY KEY (`id`, `date`) USING BTREE,
    UNIQUE INDEX `key` (`date`, `key`) USING BTREE
)
COLLATE='utf8mb4_general_ci'
/*!50100 PARTITION BY RANGE (to_days(`date`))
(PARTITION p20230123 VALUES LESS THAN (738909) ENGINE = InnoDB,
 PARTITION p20230124 VALUES LESS THAN (738910) ENGINE = InnoDB,
 PARTITION p20230125 VALUES LESS THAN (738911) ENGINE = InnoDB)  */;

然后,通过下面这个 cron 任务自动更新分区:

#!/bin/bash

# 开启调试模式,输出每条执行的命令及其执行结果
set -x

# 检查当前机器 IP 地址中是否包含指定的 VIP(虚拟 IP)
# 确认在主 MySQL 上执行
vip_w="192.168.12.34"
if [ $(/sbin/ip a | grep "${vip_w}" | wc -l) -eq 0 ]; then echo 'WARN: Wrong Machine!!!'; exit 1; fi

# 删除 90 天前的分区
# PS:如果分区不存在,TRUNCATE 不会报错。
delete_date=$(date -d '90 days ago' +%Y%m%d)
mysql -uroot -p123456 -e "USE test; ALTER TABLE test TRUNCATE PARTITION p$delete_date;"  # DROP

# 创建未来分区
create_date=$(date -d '7 days' +%Y%m%d)
mysql -uroot -p123456 -e "USE test; ALTER TABLE test ADD PARTITION (PARTITION p$delete_date VALUES LESS THAN (TO_DAYS("$delete_date")));"

#11 MySQL Boolean

2017-09-01

我们通常使用以下几种方式表示布尔值:

  1. tinyint(1)
  2. bit(1)
  3. enum('Y','N')

在 MySQL 中 bool, boolean 是 tinyint(1) 的别名。

如果只是一个 True OR False 的布尔型,没有比 bit(1) 更合适的了。
但是也有些时候,我们有好几个 bool 型用一个字段表示,最好用 bit(m),我也用过 int 型。

附:不同值的长度

Type Bit Byte Note
tinyint 8 1  
smallint 16 2  
middleint 24 3  
int 32 4  
bigint 64 8  
bit(m) m (m+7)/8  
binary[(m)]   m m 默认值:1
varbinary(m)   (m+1)  
tinyblob   (L+1) 1B 长度,最长 255B
blob[(m)]   (L+2) 2B 长度,最长 64KB - 1
mediumblob   (L+3) 3B 长度,最长 16MB - 1
longblob   (L+4) 4B 长度,最长 4GB - 1
enum('a',..)   1/2 最多可以存储 2^16 - 1 个值
set('a',..)   1/2/3/4/8 最多可以存储 64 个值

PS: blob 如果指定长度 m,MySQL 会选择足够存储数据的最小长度。
PS: MySQL set 类型

参考资料与拓展阅读