mysqladmin是MySQL一个重要的客户端,最常见的是使用它来关闭数据库,除此,该命令还可以了解MySQL运行状态、进程信息、进程杀死等。本文介绍一下如何使用mysqladmin extended-status(因为没有"歧义",所以可以使用ext代替)了解MySQL的运行状态。
1. 使用-r/-i参数
使用mysqladmin extended-status命令可以获得所有MySQL性能指标,即show global status的输出,不过,因为多数这些指标都是累计值,如果想了解当前的状态,则需要进行一次差值计算,这就是mysqladmin extended-status的一个额外功能,非常实用。默认的,使用extended-status,看到也是累计值,但是,加上参数-r(--relative),就可以看到各个指标的差值,配合参数-i(--sleep)就可以指定刷新的频率,那么就有如下命令:
代码如下:
mysqladmin -uroot -r -i 1 -pxxx extended-status
+------------------------------------------+----------------------+
| Variable_name | Value |
+------------------------------------------+----------------------+
| Aborted_clients | 0 |
| Com_select | 336 |
| Com_insert | 243 |
......
| Threads_created | 0 |
+------------------------------------------+----------------------+
2. 配合grep使用
配合grep使用,我们就有:
代码如下:
mysqladmin -uroot -r -i 1 -pxxx extended-status \
|grep "Questions\|Queries\|Innodb_rows\|Com_select \|Com_insert \|Com_update \|Com_delete "
| Com_delete | 1 |
| Com_delete_multi | 0 |
| Com_insert | 321 |
| Com_select | 286 |
| Com_update | 63 |
| Innodb_rows_deleted | 1 |
| Innodb_rows_inserted | 207 |
| Innodb_rows_read | 5211 |
| Innodb_rows_updated | 65 |
| Queries | 2721 |
| Questions | 2721 |
3. 配合简单的awk使用
使用awk,同时输出时间信息:
代码如下:
mysqladmin -uroot -p -h127.0.0.1 -P3306 -r -i 1 ext |\
awk -F"|" '{\
if($2 ~ /Variable_name/){\
print " ";\
}\
if($2 ~ /Questions|Queries|Innodb_rows|Com_select |Com_insert |Com_update |Com_delete |Innodb_buffer_pool_read_requests/)\
print $2 $3;\
}'
Com_delete 0
Com_insert 0
Com_select 0
Com_update 0
Innodb_buffer_pool_read_requests 589
Innodb_rows_deleted 0
Innodb_rows_inserted 2
Innodb_rows_read 50
Innodb_rows_updated 50
Queries 105
Questions 1
Com_delete 0
Com_insert 0
Com_select 0
Com_update 0
Innodb_buffer_pool_read_requests 1814
Innodb_rows_deleted 0
Innodb_rows_inserted 0
Innodb_rows_read 8
Innodb_rows_updated 8
Queries 17
Questions 1
4. 配合复杂一点的awk
反正也不简单了,那就更复杂一点,这样让输出结果更友好点,因为awk不支持动态变量,所以代码看起来比较复杂:
代码如下:
mysqladmin -P3306 -uroot -p -h127.0.0.1 -r -i 1 ext |\
awk -F"|" \
"BEGIN{ count=0; }"\
'{ if($2 ~ /Variable_name/ && ++count == 1){\
print "----------|---------|--- MySQL Command Status --|----- Innodb row operation ----|-- Buffer Pool Read --";\
print "---Time---|---QPS---|select insert update delete| read inserted updated deleted| logical physical";\
}\
else if ($2 ~ /Queries/){queries=$3;}\
else if ($2 ~ /Com_select /){com_select=$3;}\
else if ($2 ~ /Com_insert /){com_insert=$3;}\
else if ($2 ~ /Com_update /){com_update=$3;}\
else if ($2 ~ /Com_delete /){com_delete=$3;}\
else if ($2 ~ /Innodb_rows_read/){innodb_rows_read=$3;}\
else if ($2 ~ /Innodb_rows_deleted/){innodb_rows_deleted=$3;}\
else if ($2 ~ /Innodb_rows_inserted/){innodb_rows_inserted=$3;}\
else if ($2 ~ /Innodb_rows_updated/){innodb_rows_updated=$3;}\
else if ($2 ~ /Innodb_buffer_pool_read_requests/){innodb_lor=$3;}\
else if ($2 ~ /Innodb_buffer_pool_reads/){innodb_phr=$3;}\
else if ($2 ~ /Uptime / && count >= 2){\
printf(" %s |%9d",strftime("%H:%M:%S"),queries);\
printf("|%6d %6d %6d %6d",com_select,com_insert,com_update,com_delete);\
printf("|%6d %8d %7d %7d",innodb_rows_read,innodb_rows_inserted,innodb_rows_updated,innodb_rows_deleted);\
printf("|%10d %11d\n",innodb_lor,innodb_phr);\
}}'
代码如下:
----------|---------|--- MySQL Command Status --|----- Innodb row operation ----|-- Buffer Pool Read --
---Time---|---QPS---|select insert update delete| read inserted updated deleted| logical physical
10:37:13 | 2231| 274 214 70 0| 4811 160 71 0| 4146 0
10:37:14 | 2972| 403 256 84 23| 2509 173 85 23| 4545 0
10:37:15 | 2334| 282 232 66 1| 1266 154 67 1| 3543 0
10:37:15 | 2241| 271 217 66 0| 1160 129 66 0| 2935 0
10:37:17 | 2497| 299 224 97 0| 1141 149 95 0| 3831 0
10:37:18 | 2871| 352 304 74 23| 8202 226 73 23| 6167 0
10:37:19 | 2441| 284 233 82 0| 1099 121 78 0| 3292 0
10:37:20 | 2342| 279 242 61 0| 1083 224 61 0| 3366 0
就这样了,这几个命令自己用的比较多,随手分享出来。

MySQL is an open source relational database management system, mainly used to store and retrieve data quickly and reliably. Its working principle includes client requests, query resolution, execution of queries and return results. Examples of usage include creating tables, inserting and querying data, and advanced features such as JOIN operations. Common errors involve SQL syntax, data types, and permissions, and optimization suggestions include the use of indexes, optimized queries, and partitioning of tables.

MySQL is an open source relational database management system suitable for data storage, management, query and security. 1. It supports a variety of operating systems and is widely used in Web applications and other fields. 2. Through the client-server architecture and different storage engines, MySQL processes data efficiently. 3. Basic usage includes creating databases and tables, inserting, querying and updating data. 4. Advanced usage involves complex queries and stored procedures. 5. Common errors can be debugged through the EXPLAIN statement. 6. Performance optimization includes the rational use of indexes and optimized query statements.

MySQL is chosen for its performance, reliability, ease of use, and community support. 1.MySQL provides efficient data storage and retrieval functions, supporting multiple data types and advanced query operations. 2. Adopt client-server architecture and multiple storage engines to support transaction and query optimization. 3. Easy to use, supports a variety of operating systems and programming languages. 4. Have strong community support and provide rich resources and solutions.

InnoDB's lock mechanisms include shared locks, exclusive locks, intention locks, record locks, gap locks and next key locks. 1. Shared lock allows transactions to read data without preventing other transactions from reading. 2. Exclusive lock prevents other transactions from reading and modifying data. 3. Intention lock optimizes lock efficiency. 4. Record lock lock index record. 5. Gap lock locks index recording gap. 6. The next key lock is a combination of record lock and gap lock to ensure data consistency.

The main reasons for poor MySQL query performance include not using indexes, wrong execution plan selection by the query optimizer, unreasonable table design, excessive data volume and lock competition. 1. No index causes slow querying, and adding indexes can significantly improve performance. 2. Use the EXPLAIN command to analyze the query plan and find out the optimizer error. 3. Reconstructing the table structure and optimizing JOIN conditions can improve table design problems. 4. When the data volume is large, partitioning and table division strategies are adopted. 5. In a high concurrency environment, optimizing transactions and locking strategies can reduce lock competition.

In database optimization, indexing strategies should be selected according to query requirements: 1. When the query involves multiple columns and the order of conditions is fixed, use composite indexes; 2. When the query involves multiple columns but the order of conditions is not fixed, use multiple single-column indexes. Composite indexes are suitable for optimizing multi-column queries, while single-column indexes are suitable for single-column queries.

To optimize MySQL slow query, slowquerylog and performance_schema need to be used: 1. Enable slowquerylog and set thresholds to record slow query; 2. Use performance_schema to analyze query execution details, find out performance bottlenecks and optimize.

MySQL and SQL are essential skills for developers. 1.MySQL is an open source relational database management system, and SQL is the standard language used to manage and operate databases. 2.MySQL supports multiple storage engines through efficient data storage and retrieval functions, and SQL completes complex data operations through simple statements. 3. Examples of usage include basic queries and advanced queries, such as filtering and sorting by condition. 4. Common errors include syntax errors and performance issues, which can be optimized by checking SQL statements and using EXPLAIN commands. 5. Performance optimization techniques include using indexes, avoiding full table scanning, optimizing JOIN operations and improving code readability.


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