Source: http: //blog.itpub.net/26515977/viewspace-1208257/
We always want to live in a certain framework, constitute the legal framework have come from there from the moral, as well as from the unspoken rules. Most people just quiet living, death-defying people are in the minority, someone broke framework roughness Wun, but also someone to break the box frame fall into the abyss. Often communicate with students doing development, you'll hear the name of a large beach framework, that was very high on big look. But he can learn Stone Mountain, which is also in the framework of MySQL, this is common_schema we want to introduce. High Performance MySQL, author of Baron Schwartz says once: The common_schema is to MySQL as JQuery is to JavaScript. This section only briefly Schema relevant part, after all common_schema too tough too broad.
Software home page
: code.google.com/p/common-schema
Software installation
:
[mysql@DataHacker ~]$ mysql -uroot -p < common_schema-2.2.sql
Enter password:
complete
- Base components: installed
- InnoDB Plugin components: installed
- Percona Server components: not installed
- TokuDB components: partial install: 1/2
Installation complete. Thank you for using common_schema!Software Information :
mysql> select attribute_name,substr(attribute_value,1,50) from metadata;
+-------------------------------------+----------------------------------------------------+
| attribute_name | substr(attribute_value,1,50) |
+-------------------------------------+----------------------------------------------------+
| author | Shlomi Noach |
| author_url | http://code.openark.org/blog/shlomi-noach |
| base_components_installed | 1 |
| innodb_plugin_components_installed | 1 |
| install_mysql_version | 5.6.12-log |
| install_sql_mode | NO_AUTO_VALUE_ON_ZERO,STRICT_TRANS_TABLES,NO_ENGIN |
| install_success | 1 |
| install_time | 2014-02-05 21:53:55 |
| license |
common_schema - DBA\'s Framework for MySQL
Copyri |
| license_type | GPL |
| percona_server_components_installed | 0 |
| project_home | http://code.google.com/p/common-schema/ |
| project_name | common_schema |
| project_repository | https://common-schema.googlecode.com/svn/trunk/ |
| project_repository_type | svn |
| revision | 523 |
| version | 2.2 |
+-------------------------------------+----------------------------------------------------+
17 rows in set (0.00 sec)
Built-in help system
:
mysql> desc help_content;
+--------------+-------------+------+-----+---------+-------+
| Field | Type | Null | Key | Default | Extra |
+--------------+-------------+------+-----+---------+-------+
| topic | varchar(32) | NO | PRI | NULL | |
| help_message | text | NO | | NULL | |
+--------------+-------------+------+-----+---------+-------+
2 rows in set (0.00 sec)
mysql> select topic from help_content;
+--------------------------------+
| topic |
+--------------------------------+
| auto_increment_columns |
| candidate_keys |
| candidate_keys_recommended |
mysql> select help_message from help_content where topic=\'innodb_index_stats\'\G;
*************************** 1. row ***************************
help_message:
NAME
innodb_index_stats: Estimated InnoDB depth & split factor of key\'s B+ Tree
TYPE
View
DESCRIPTION
innodb_index_stats extends the INNODB_INDEX_STATS patch in Percona Server, and
presents with estimated depth & split factor of InnoDB keys.
Estimations are optimistic, in that they assume condensed trees. It is
possible that the depth is larger than estimated, and that split factor is
lower than estimated.
Estimated values are presented as floating point values, although in reality
these are integer types.
This view is experimental and in BETA stage.
This view depends upon the INNODB_INDEX_STATS patch in Percona Server.
Note that Percona Server 5.5.8-20.0 version introduced changes to the
INNODB_INDEX_STATS schema. This view is compatible with the new schema, and is
incompatible with older releases.
...............<此处省略输出>.............
So where data from the source? We redundant_keys track its source code, for example:
FROM
_flattened_keys AS redundant_keys
INNER JOIN _flattened_keys AS dominant_keys
USING (TABLE_SCHEMA, TABLE_NAME)
And then to see _flattened_keys base table:
FROM INFORMATION_SCHEMA.STATISTICS
I common_schema relates to a class of the schema archive, as shown below:
Then we expanded the classification of these five general introduction
1 Data Size per Schema
● data_size_per_schema
mysql> select * from data_size_per_schema where table_schema=\'sakila\'\G;
*************************** 1. row ***************************
TABLE_SCHEMA: sakila
count_tables: 16
count_views: 7
distinct_engines: 2
data_size: 4297536
index_size: 2581504
total_size: 6879040
largest_table: rental
largest_table_size: 2785280
1 row in set (0.16 sec)
2 Schema Object Analysis: Tables
DDL scripts
● sql_alter_table
● sql_foreign_keys
● sql_alter_table
● sql_foreign_keys
mysql> select table_name,sql_add_keys from sql_alter_table where table_schema=\'sakila\'\G;
*************************** 1. row ***************************
table_name: actor
sql_add_keys: ADD KEY `idx_actor_last_name`(`last_name`), ADD KEY `idx_actor_last_name_duplicate`(`last_name`), ADD PRIMARY KEY (`actor_id`)
*************************** 2. row ***************************
table_name: address
sql_add_keys: ADD KEY `idx_fk_city_id`(`city_id`), ADD PRIMARY KEY (`address_id`)
.................<此处省略输出>.................
mysql> select * from sql_foreign_keys where table_schema=\'sakila\'\G;
*************************** 1. row ***************************
TABLE_SCHEMA: sakila
TABLE_NAME: address
CONSTRAINT_NAME: fk_address_city
drop_statement: ALTER TABLE `sakila`.`address` DROP FOREIGN KEY `fk_address_city`
create_statement: ALTER TABLE `sakila`.`address` ADD CONSTRAINT `fk_address_city` FOREIGN KEY (`city_id`) REFERENCES `sakila`.`city` (`city_id`) ON DELETE RESTRICT ON UPDATE CASCADE
........................<此处省略输出>.........................
3 Schema Object Analysis: Columns
Column overviews
● auto_increment_columns
● text_columns
● text_columns
mysql> select table_name,column_name,data_type,max_value,auto_increment value,auto_increment_ratio ratio
-> from auto_increment_columns
-> where table_schema=\'sakila\';
+------------+--------------+-----------+------------+-------+--------+
| TABLE_NAME | COLUMN_NAME | DATA_TYPE | max_value | value | ratio |
+------------+--------------+-----------+------------+-------+--------+
| actor | actor_id | smallint | 65535 | 201 | 0.0031 |
| address | address_id | smallint | 65535 | 606 | 0.0092 |
| category | category_id | tinyint | 255 | 17 | 0.0667 |
| city | city_id | smallint | 65535 | 601 | 0.0092 |
| country | country_id | smallint | 65535 | 110 | 0.0017 |
| customer | customer_id | smallint | 65535 | 600 | 0.0092 |
| film | film_id | smallint | 65535 | 1001 | 0.0153 |
| inventory | inventory_id | mediumint | 16777215 | 4582 | 0.0003 |
| language | language_id | tinyint | 255 | 7 | 0.0275 |
| payment | payment_id | smallint | 65535 | 16050 | 0.2449 |
| rental | rental_id | int | 2147483647 | 16050 | 0.0000 |
| staff | staff_id | tinyint | 255 | 3 | 0.0118 |
| store | store_id | tinyint | 255 | 3 | 0.0118 |
+------------+--------------+-----------+------------+-------+--------+
13 rows in set (0.90 sec)4 Schema Object Analysis: Indexes
Keys and Indexes
● candidate_keys
● candidate_keys_recommended
● no_pk_innodb_tables
● rendundant_keys
● candidate_keys
● candidate_keys_recommended
● no_pk_innodb_tables
● rendundant_keys
mysql> select * from candidate_keys_recommended where table_schema=\'sakila\';
+--------------+---------------+------------------------+--------------+------------+-----------------------+---------------------+
| table_schema | table_name | recommended_index_name | has_nullable | is_primary | count_column_in_index | column_names |
+--------------+---------------+------------------------+--------------+------------+-----------------------+---------------------+
| sakila | language | PRIMARY | 0 | 1 | 1 | language_id |
| sakila | customer | PRIMARY | 0 | 1 | 1 | customer_id |
| sakila | film_category | PRIMARY | 0 | 1 | 2 | film_id,category_id |
| sakila | category | PRIMARY | 0 | 1 | 1 | category_id |
| sakila | rental | PRIMARY | 0 | 1 | 1 | rental_id |
| sakila | film_actor | PRIMARY | 0 | 1 | 2 | actor_id,film_id |
| sakila | inventory | PRIMARY | 0 | 1 | 1 | inventory_id |
| sakila | country | PRIMARY | 0 | 1 | 1 | country_id |
| sakila | store | PRIMARY | 0 | 1 | 1 | store_id |
| sakila | address | PRIMARY | 0 | 1 | 1 | address_id |
| sakila | payment | PRIMARY | 0 | 1 | 1 | payment_id |
| sakila | film | PRIMARY | 0 | 1 | 1 | film_id |
| sakila | film_text | PRIMARY | 0 | 1 | 1 | film_id |
| sakila | city | PRIMARY | 0 | 1 | 1 | city_id |
| sakila | staff | PRIMARY | 0 | 1 | 1 | staff_id |
| sakila | actor | PRIMARY | 0 | 1 | 1 | actor_id |
+--------------+---------------+------------------------+--------------+------------+-----------------------+---------------------+
16 rows in set (0.39 sec)
5 Schema Object Analysis: Dependencies
Dependency Routines
● get_event_dependencies(schema, name)
● get_routine_dependencies(schema, name)
● get_view_dependencies(schema, name)
● get_sql_dependencies(sql, schema)
● get_event_dependencies(schema, name)
● get_routine_dependencies(schema, name)
● get_view_dependencies(schema, name)
● get_sql_dependencies(sql, schema)
mysql> call get_view_dependencies(\'sakila\',\'actor_info\');
+-------------+---------------+-------------+--------+
| schema_name | object_name | object_type | action |
+-------------+---------------+-------------+--------+
| sakila | actor | table | select |
| sakila | category | table | select |
| sakila | film | table | select |
| sakila | film_actor | table | select |
| sakila | film_category | table | select |
+-------------+---------------+-------------+--------+
5 rows in set (0.32 sec)
Query OK, 0 rows affected (0.32 sec)These are common_schema fair share of things, and then introduce the following two kinds of ways to create Schema, which common_schema, that is a piece of cake.
1 eval()
Specific usage, view the help:
mysql> call help(\'eval\');
+--------------------------------------------------------------------------------+
| help |
+--------------------------------------------------------------------------------+
| |
| NAME |
| |
| eval(): Evaluates the queries generated by a given query. |
| |
| TYPE |
..............<此处省略输出>...............
Method presentation:
mysql> call eval(\'select concat(\\'create table test.\\', table_name,\\' as select * from sakila.\\', table_name)
\'> from information_schema.tables
\'> where table_schema = \\'sakila\\'\');
Query OK, 0 rows affected (11.30 sec)
mysql> show tables in test;
+----------------------------+
| Tables_in_test |
+----------------------------+
| actor |
| actor_info |
| address |
...... <此处省略输出>.......
| staff_list |
| store |
+----------------------------+
23 rows in set (0.00 sec)
mysql> call eval(\'select concat(\\'drop table test.\\', table_name) from information_schema.tables
\'> where table_schema = \\'test\\'\');
Query OK, 0 rows affected (0.92 sec)
mysql> show tables in test;
Empty set (0.00 sec)
2 foreach
Similarly, the view foreach help:
mysql> call help(\'foreach\');
+--------------------------------------------------------------------------------+
| help |
+--------------------------------------------------------------------------------+
| |
| NAME |
| |
| foreach(): Invoke a script on each element of given collection. $() is a |
| synonym of this routine. |
| |
| TYPE |
| |
| Procedure |
| |
| DESCRIPTION |
| |
| This procedure accepts collections of varying types, including result sets, |
| and invokes a QueryScript code per element. |
...............<此处省略N个输出>.................
Specific demonstrate the process:
mysql> call $(\'1:3\', \'create table test.${1}(id int,name varchar(20))\');
Query OK, 0 rows affected, 1 warning (0.59 sec)
mysql> show tables in test;
+----------------+
| Tables_in_test |
+----------------+
| 1 |
| 2 |
| 3 |
+----------------+
3 rows in set (0.00 sec)
mysql> call $(\'1:3\', \'drop table test.`${1}`\');
Query OK, 0 rows affected, 1 warning (0.40 sec)
mysql> show tables in test;
Empty set (0.00 sec)
By DataHacker
2014-2-7
Good Luck！
Reproduced in: https: //www.cnblogs.com/stevenzeng/p/5154977.html