MariaDB 使用CONNECT存儲引擎

MariaDB 使用CONNECT存儲引擎

環境：

CentOS 7.1 x64

mariadb-10.1.13 x64

https://mariadb.com/kb/en/connect/

一.安裝CONNECT存儲引擎

ln -s /lib64/libodbc.so.2.0.0 /lib64/libodbc.so.1

注意:ha_connect.so依賴libodbc.so.1(unixODBC)提供，但CentOS7的版本爲2，版本不符，所以在安裝的時候會報libodbc.so.1找不到，一般高版本的都會兼容低版本的，因此作了軟鏈就能夠解決問題

 

INSTALL SONAME 'ha_connect';

 

SHOW ENGINES;

 

SHOW PLUGINS;

| TokuDB                        | ACTIVE   | STORAGE ENGINE     | ha_tokudb.so  | GPL     |

| TokuDB_trx                    | ACTIVE   | INFORMATION SCHEMA | ha_tokudb.so  | GPL     |

| TokuDB_lock_waits             | ACTIVE   | INFORMATION SCHEMA | ha_tokudb.so  | GPL     |

| TokuDB_locks                  | ACTIVE   | INFORMATION SCHEMA | ha_tokudb.so  | GPL     |

| TokuDB_file_map               | ACTIVE   | INFORMATION SCHEMA | ha_tokudb.so  | GPL     |

| TokuDB_fractal_tree_info      | ACTIVE   | INFORMATION SCHEMA | ha_tokudb.so  | GPL     |

| TokuDB_fractal_tree_block_map | ACTIVE   | INFORMATION SCHEMA | ha_tokudb.so  | GPL     |

| CONNECT                       | ACTIVE   | STORAGE ENGINE     | ha_connect.so | GPL     |

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

 

63 rows in set (0.00 sec)

二.建立CONNECT表

CREATE TABLE test_data (

  path varchar(256) NOT NULL flag=1,

  filename varchar(256) NOT NULL flag=2,

  filesize double(12,0) NOT NULL flag=5

) ENGINE=CONNECT DEFAULT CHARSET=latin1

  TABLE_TYPE=DIR FILE_NAME='*.frm'

  OPTION_LIST='subdir=1';

TABLE_TYPE能夠有CSV, XML, INI, ODBC, MYSQL, DIR

 

Flag Number Information

1  Path 2  File name 3  File type 4  File attributes 5  File size 6  Last write-access date 7  Last read-access date 8  File creation date

MariaDB [isfdb]> SELECT * FROM test_data;

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

| path                                                      | filename            | filesize |

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

| /opt/mariadb-10.1.13-linux-glibc_214-x86_64/data/./isfdb/ | authors             |     1974 |

| /opt/mariadb-10.1.13-linux-glibc_214-x86_64/data/./isfdb/ | award_cats          |     1090 |

| /opt/mariadb-10.1.13-linux-glibc_214-x86_64/data/./isfdb/ | award_types         |     1323 |

| /opt/mariadb-10.1.13-linux-glibc_214-x86_64/data/./isfdb/ | awards              |     2281 |

| /opt/mariadb-10.1.13-linux-glibc_214-x86_64/data/./isfdb/ | bad_images          |      964 |

| /opt/mariadb-10.1.13-linux-glibc_214-x86_64/data/./isfdb/ | canonical_author    |     2484 |

| /opt/mariadb-10.1.13-linux-glibc_214-x86_64/data/./isfdb/ | cleanup             |     1543 |

| /opt/mariadb-10.1.13-linux-glibc_214-x86_64/data/./isfdb/ | directory           |     1012 |

| /opt/mariadb-10.1.13-linux-glibc_214-x86_64/data/./isfdb/ | emails              |     1001 |

| /opt/mariadb-10.1.13-linux-glibc_214-x86_64/data/./isfdb/ | history             |     1268 |

| /opt/mariadb-10.1.13-linux-glibc_214-x86_64/data/./isfdb/ | languages           |     2075 |

| /opt/mariadb-10.1.13-linux-glibc_214-x86_64/data/./isfdb/ | license_keys        |     1484 |

| /opt/mariadb-10.1.13-linux-glibc_214-x86_64/data/./isfdb/ | magazine            |     1145 |

| /opt/mariadb-10.1.13-linux-glibc_214-x86_64/data/./isfdb/ | metadata            |      578 |

| /opt/mariadb-10.1.13-linux-glibc_214-x86_64/data/./isfdb/ | missing_author_urls |     1048 |

| /opt/mariadb-10.1.13-linux-glibc_214-x86_64/data/./isfdb/ | mw_user             |     3054 |

| /opt/mariadb-10.1.13-linux-glibc_214-x86_64/data/./isfdb/ | mw_user_groups      |     1458 |

| /opt/mariadb-10.1.13-linux-glibc_214-x86_64/data/./isfdb/ | notes               |      965 |

| /opt/mariadb-10.1.13-linux-glibc_214-x86_64/data/./isfdb/ | pseudonyms          |     1969 |

| /opt/mariadb-10.1.13-linux-glibc_214-x86_64/data/./isfdb/ | pub_content         |     2011 |

| /opt/mariadb-10.1.13-linux-glibc_214-x86_64/data/./isfdb/ | pub_series          |     1555 |

| /opt/mariadb-10.1.13-linux-glibc_214-x86_64/data/./isfdb/ | publishers          |     1541 |

| /opt/mariadb-10.1.13-linux-glibc_214-x86_64/data/./isfdb/ | notes_tokudb        |      965 |

| /opt/mariadb-10.1.13-linux-glibc_214-x86_64/data/./isfdb/ | pubs                |     3302 |

| /opt/mariadb-10.1.13-linux-glibc_214-x86_64/data/./isfdb/ | reference           |     1093 |

| /opt/mariadb-10.1.13-linux-glibc_214-x86_64/data/./isfdb/ | series              |     1607 |

| /opt/mariadb-10.1.13-linux-glibc_214-x86_64/data/./isfdb/ | submissions         |     4660 |

| /opt/mariadb-10.1.13-linux-glibc_214-x86_64/data/./isfdb/ | tag_mapping         |     2483 |

| /opt/mariadb-10.1.13-linux-glibc_214-x86_64/data/./isfdb/ | tags                |      990 |

| /opt/mariadb-10.1.13-linux-glibc_214-x86_64/data/./isfdb/ | title_awards        |     1964 |

| /opt/mariadb-10.1.13-linux-glibc_214-x86_64/data/./isfdb/ | title_relationships |     3009 |

| /opt/mariadb-10.1.13-linux-glibc_214-x86_64/data/./isfdb/ | trans_legal_names   |     1015 |

| /opt/mariadb-10.1.13-linux-glibc_214-x86_64/data/./isfdb/ | trans_pub_series    |     1024 |

| /opt/mariadb-10.1.13-linux-glibc_214-x86_64/data/./isfdb/ | trans_publisher     |     1021 |

| /opt/mariadb-10.1.13-linux-glibc_214-x86_64/data/./isfdb/ | user_languages      |     2001 |

| /opt/mariadb-10.1.13-linux-glibc_214-x86_64/data/./isfdb/ | user_preferences    |     2434 |

| /opt/mariadb-10.1.13-linux-glibc_214-x86_64/data/./isfdb/ | user_sites          |     2001 |

| /opt/mariadb-10.1.13-linux-glibc_214-x86_64/data/./isfdb/ | verification        |     3045 |

| /opt/mariadb-10.1.13-linux-glibc_214-x86_64/data/./isfdb/ | votes               |     1992 |

| /opt/mariadb-10.1.13-linux-glibc_214-x86_64/data/./isfdb/ | webpages            |     1192 |

| /opt/mariadb-10.1.13-linux-glibc_214-x86_64/data/./isfdb/ | websites            |     1030 |

| /opt/mariadb-10.1.13-linux-glibc_214-x86_64/data/./isfdb/ | authors_tokudb      |     2980 |

| /opt/mariadb-10.1.13-linux-glibc_214-x86_64/data/./isfdb/ | titles              |     4213 |

| /opt/mariadb-10.1.13-linux-glibc_214-x86_64/data/./isfdb/ | pub_authors         |     1962 |

| /opt/mariadb-10.1.13-linux-glibc_214-x86_64/data/./isfdb/ | test_data           |     1092 |

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

45 rows in set (0.01 sec)

MariaDB [isfdb]> SELECT path,COUNT(*),SUM(filesize) FROM test_data GROUP BY path;

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

| path                                                      | COUNT(*) | SUM(filesize) |

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

| /opt/mariadb-10.1.13-linux-glibc_214-x86_64/data/./isfdb/ |       45 |         80898 |

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

1 row in set (0.00 sec)

MariaDB [isfdb]> DROP TABLE test_data;

 

Query OK, 0 rows affected (0.01 sec)

三.讀寫CSV

1.導出CSV

SELECT author_id, author_canonical, author_legalname,

              author_birthplace, author_birthdate, author_deathdate

           INTO OUTFILE '/tmp/authors.csv'

    FIELDS TERMINATED BY ',' ENCLOSED BY '"'

FROM authors ORDER BY author_id LIMIT 100;

2.建立CSV類型的表

CREATE TABLE authors_csv (

         author_id int(11) NOT NULL,

         author_canonical varchar(1024) NOT NULL,

         author_legalname varchar(1024) NOT NULL,

         author_birthplace varchar(1024) NOT NULL,

         author_birthdate varchar(10),

         author_deathdate varchar(10)

       ) ENGINE=CONNECT 

       TABLE_TYPE='CSV'

       FILE_NAME='/tmp/authors.csv'

       SEP_CHAR=',' QCHAR='"' QUOTED=1;

CREATE TABLE authors_csv2 (

  author_id int(11) NOT NULL,

  author_birthdate varchar(10) NOT NULL FLAG=5,

  author_birthplace varchar(1024) NOT NULL FLAG=4,

  author_canonical varchar(1024) NOT NULL FLAG=2

) ENGINE=CONNECT DEFAULT CHARSET=utf8

TABLE_TYPE='CSV'

FILE_NAME='/tmp/authors_csv.CSV'

SEP_CHAR=',' QCHAR='"' QUOTED=1;

3.插入記錄

INSERT authors_csv VALUES (

         101,"Fake Author",

         "Author, Fake",

         "Charlotte, North Carolina, USA",

         "1970-01-01",""), (

         102,"Really Fake Author",

         "Author, Really Fake",

         "St. Paul, Minnesota, USA",

         "1969-12-31","");

4.直接修改/tmp/authors.csv

echo '103,"Fake","Fake","Fake, USA","1970-04-01", ' >>/tmp/authors.csv

5.查詢

MariaDB [isfdb]> SELECT * FROM authors_csv WHERE author_id >= 100;

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

| author_id | author_canonical   | author_legalname    | author_birthplace               | author_birthdate | author_deathdate |

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

|       100 | Iain M. Banks      | Banks, Iain Menzies | Dunfermline, Fife, Scotland, UK | 1954-02-16       | 2013-06-09       |

|       101 | Fake Author        | Author, Fake        | Charlotte, North Carolina, USA  | 1970-01-01       | NULL             |

|       102 | Really Fake Author | Author, Really Fake | St. Paul, Minnesota, USA        | 1969-12-31       | NULL             |

|       103 | Fake               | Fake                | Fake, USA                       | 1970-04-01       | NULL             |

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

 

4 rows in set (0.01 sec)

四.讀寫XML

1.建表

CREATE TABLE authors_xml (

     author_id int,

     author_canonical varchar(1024),

     author_legalname varchar(1024),

     author_birthplace varchar(1024),

     author_birthdate char(10),

     author_deathdate char(10),

     note_id int,

     author_wikipedia varchar(1024),

     author_views int,

     author_imdb varchar(1024),

     author_marque int,

     author_image varchar(1024),

     author_annualviews int,

     author_lastname varchar(1024),  author_language int

       ) ENGINE=CONNECT TABLE_TYPE=XML FILE_NAME='/tmp/isfdb-001.xml'

         TABNAME='resultset'

         OPTION_LIST='rownode=row,colnode=field,coltype=HTML'

       ;

2.插入記錄

INSERT authors_xml VALUES (

         101,"Terry Pratchett","Pratchett, Terry",

         "Beaconsfield, Buckinghamshire, UK",

         "0000-00-00","0000-00-00",101,

         "",101,"",101,"",101,"Terry",101 );

3.查詢       

SELECT author_id, author_canonical FROM authors_xml WHERE author_birthplace LIKE '%UK';

MariaDB [isfdb]> SELECT author_id, author_canonical FROM authors_xml WHERE author_birthplace LIKE '%UK';

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

| author_id | author_canonical |

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

|       101 | Terry Pratchett  |

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

 

1 row in set (0.00 sec)

五.經過CONNECT訪問mysql

1.建表

CREATE TABLE websites_2 (

         site_id int(11),

         site_name varchar(255),

         site_url varchar(1024),

         PRIMARY KEY (site_id)

       ) ENGINE=CONNECT TABLE_TYPE=MYSQL

       CONNECTION='mysql://jlive:liujun@192.168.130.254/isfdb/websites';

       

2. 插入兩條記錄      

INSERT websites_2 VALUES

         ("","MariaDB.com","https://mariadb.com"),

         ("","MariaDB.org","https://mariadb.org");

3.查詢記錄

MariaDB [isfdb]> SELECT * FROM websites WHERE LENGTH(site_url)<40;

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

| site_id | site_name      | site_url                                | site_isbn13 |

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

|       5 | Amazon CA      | http://www.amazon.ca/dp/%s              |        NULL |

|       6 | Amazon DE      | http://www.amazon.de/dp/%s              |        NULL |

|       7 | Amazon FR      | http://www.amazon.fr/dp/%s              |        NULL |

|       8 | Barnes & Noble | http://www.barnesandnoble.com/s/%s      |           1 |

|      13 | Powells        | http://www.powells.com/biblio?isbn=%s   |           1 |

|      15 | WorldCat       | http://www.worldcat.org/isbn/%s         |           1 |

|      16 | Smashwords     | http://www.smashwords.com/isbn/%s       |           1 |

|      17 | Open Library   | http://openlibrary.org/isbn/%s          |        NULL |

|      19 | LibraryThing   | http://www.librarything.com/isbn/%s     |           1 |

|      21 | GoodReads      | http://www.goodreads.com/book/isbn/%s   |           1 |

|      28 | Booktopia      | http://www.booktopia.com.au/prod%s.html |           1 |

|      30 | MariaDB.com    | https://mariadb.com                     |        NULL |

|      31 | MariaDB.org    | https://mariadb.org                     |        NULL |

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

13 rows in set (0.01 sec)

MariaDB [isfdb]> SELECT * FROM websites_2 WHERE LENGTH(site_url)<40;

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

| site_id | site_name      | site_url                                |

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

|       5 | Amazon CA      | http://www.amazon.ca/dp/%s              |

|       6 | Amazon DE      | http://www.amazon.de/dp/%s              |

|       7 | Amazon FR      | http://www.amazon.fr/dp/%s              |

|       8 | Barnes & Noble | http://www.barnesandnoble.com/s/%s      |

|      13 | Powells        | http://www.powells.com/biblio?isbn=%s   |

|      15 | WorldCat       | http://www.worldcat.org/isbn/%s         |

|      16 | Smashwords     | http://www.smashwords.com/isbn/%s       |

|      17 | Open Library   | http://openlibrary.org/isbn/%s          |

|      19 | LibraryThing   | http://www.librarything.com/isbn/%s     |

|      21 | GoodReads      | http://www.goodreads.com/book/isbn/%s   |

|      28 | Booktopia      | http://www.booktopia.com.au/prod%s.html |

|      30 | MariaDB.com    | https://mariadb.com                     |

|      31 | MariaDB.org    | https://mariadb.org                     |

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

 

13 rows in set (0.00 sec)

六.使用XCOL表類型

當某個字段的值是一個列表時，XCOL就很是有用

1.建表

CREATE TABLE superheroes (

         team varchar(50),

         heroes varchar(1024)

       );

2.插入記錄      

INSERT superheroes VALUES

         ("The Avengers","Thor, Iron Man, Black Widow, Hawkeye, Hulk,

       Captain America"),

         ("The Justice League", "Superman, Batman, Aquaman, Flash, Wonder

       Woman"),

         ("The X-Men", "Storm, Cyclops, Wolverine, Rogue, Iceman");

3.建立XCOL表        

CREATE USER 'foo'@'localhost';

GRANT SELECT ON isfdb.superheroes_xcol TO 'foo'@'localhost';

GRANT SELECT ON isfdb.superheroes TO 'foo'@'localhost';  

       

CREATE TABLE superheroes_xcol ENGINE=CONNECT

  TABLE_TYPE=XCOL TABNAME='superheroes'

 

  OPTION_LIST='user=foo,colname=heroes';

4.查詢

MariaDB [isfdb]> SELECT * FROM superheroes_xcol;

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

| team               | heroes                  |

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

| The Avengers       | Thor                    |

| The Avengers       | Iron Man                |

| The Avengers       | Black Widow             |

| The Avengers       | Hawkeye                 |

| The Avengers       | Hulk                    |

       Captain America |

| The Justice League | Superman                |

| The Justice League | Batman                  |

| The Justice League | Aquaman                 |

| The Justice League | Flash                   |

       Woman     |ue | Wonder

| The X-Men          | Storm                   |

| The X-Men          | Cyclops                 |

| The X-Men          | Wolverine               |

| The X-Men          | Rogue                   |

| The X-Men          | Iceman                  |

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

16 rows in set (0.00 sec)

MariaDB [isfdb]> SELECT * FROM superheroes_xcol WHERE heroes LIKE "S%";

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

| team               | heroes   |

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

| The Justice League | Superman |

| The X-Men          | Storm    |

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

2 rows in set (0.00 sec)

MariaDB [isfdb]> SELECT team, count(heroes) FROM superheroes_xcol GROUP BY team;

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

| team               | count(heroes) |

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

| The Avengers       |             6 |

| The Justice League |             5 |

| The X-Men          |             5 |

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

 

3 rows in set (0.00 sec)

七.使用PIVOT表類型

很是適合於sort和count,比group by更容易理解

1.建表

USE test; 

CREATE TABLE expenses (

     who varchar(64),

     day varchar(10),

     what varchar(64),

     amount varchar(10)

);

2.插入數據

INSERT expenses VALUES

     ("Daniel","2013-09-01","Clothing",42.50),

     ("Amy","2013-09-02","Food",5.22),

     ("Daniel","2013-09-01","Clothing",27.75),

     ("Daniel","2013-09-03","Food",10.27),

     ("Amy","2013-09-03","Gas",42.84),

     ("Amy","2013-09-01","Food",15.01),

     ("Amy","2013-09-01","Clothing",11.00),

     ("Daniel","2013-09-01","Gas",34.10),

     ("Amy","2013-09-02","Food",15.00),

     ("Daniel","2013-09-01","Food",12.50),

     ("Daniel","2013-09-02","Gas",32.20),

     ("Daniel","2013-09-03","Clothing",82.80),

     ("Amy","2013-09-03","Food",8.72),

     ("Daniel","2013-09-03","Gas",15.08),

     ("Daniel","2013-09-02","Clothing",17.27),

     ("Amy","2013-09-03","Clothing",32.00) ;

3.建立PIVOT類型表

GRANT SELECT ON test.expenses TO 'foo'@'localhost';  

CREATE TABLE expenses_pivot ENGINE=CONNECT TABLE_TYPE=PIVOT TABNAME=expenses OPTION_LIST='user=foo';

MariaDB [test]> SELECT who, day, what, SUM(amount) FROM expenses GROUP BY who, day, what;

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

| who    | day        | what     | SUM(amount) |

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

| Amy    | 2013-09-01 | Clothing |          11 |

| Amy    | 2013-09-01 | Food     |       15.01 |

| Amy    | 2013-09-02 | Food     |       20.22 |

| Amy    | 2013-09-03 | Clothing |          32 |

| Amy    | 2013-09-03 | Food     |        8.72 |

| Amy    | 2013-09-03 | Gas      |       42.84 |

| Daniel | 2013-09-01 | Clothing |       70.25 |

| Daniel | 2013-09-01 | Food     |        12.5 |

| Daniel | 2013-09-01 | Gas      |        34.1 |

| Daniel | 2013-09-02 | Clothing |       17.27 |

| Daniel | 2013-09-02 | Gas      |        32.2 |

| Daniel | 2013-09-03 | Clothing |        82.8 |

| Daniel | 2013-09-03 | Food     |       10.27 |

| Daniel | 2013-09-03 | Gas      |       15.08 |

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

 

14 rows in set (0.00 sec)

七.使用OCCUR表類型

CREATE TABLE gadgets (

   who varchar(64),

   phone int,

   tablet int,

   mp3player int,

   camera int

);

INSERT gadgets VALUES

         ("Jim",1,2,1,2),

         ("Bob",0,0,3,0),

         ("Tom",1,1,1,0),

         ("Joe",1,1,1,1),

         ("Rob",2,2,0,0),

         ("Tim",0,3,1,1)

;

CREATE TABLE gadgets_occur (

         who varchar(64) NOT NULL,

         gadget varchar(16) NOT NULL,

         number int NOT NULL

       ) ENGINE=CONNECT TABLE_TYPE=OCCUR TABNAME=gadgets

       OPTION_LIST='user=foo,occurcol=number,rankcol=gadget'

       COLIST='phone,tablet,mp3player,camera';

       

GRANT ALL ON isfdb.gadgets TO foo@localhost;  

注意: 用戶必定要有相關權限，否則沒法進行查詢等操做   

SELECT * FROM gadgets_occur;

SELECT * FROM gadgets_occur

         WHERE gadget="tablet" and number > 1;

MariaDB [isfdb]> SELECT * FROM gadgets_occur  WHERE number > 1;

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

| who | gadget    | number |

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

| Jim | tablet    |      2 |

| Jim | camera    |      2 |

| Bob | mp3player |      3 |

| Rob | phone     |      2 |

| Rob | tablet    |      2 |

| Tim | tablet    |      3 |

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

6 rows in set (0.00 sec)

MariaDB [isfdb]> SELECT who,phone AS gadget FROM gadgets WHERE phone > 1 UNION ALL SELECT who,tablet FROM gadgets WHERE tablet > 1 UNION ALL SELECT who,mp3player FROM gadgets WHERE mp3player > 1 UNION ALL SELECT who,camera FROM gadgets WHERE camera > 1;

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

| who  | gadget |

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

| Rob  |      2 |

| Jim  |      2 |

| Rob  |      2 |

| Tim  |      3 |

| Bob  |      3 |

| Jim  |      2 |

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

 

6 rows in set (0.00 sec)

八.使用WMI表類型(二進制包不支持)

 

CREATE TABLE alias (

         friendlyname char(32) NOT NULL,

         target char(64) NOT NULL

       ) ENGINE=CONNECT TABLE_TYPE=WMI

       OPTION_LIST='Namespace=root\\cli,Class=Msft_CliAlias';

       

SELECT * FROM alias;

九.使用MAC地址表類型(二進制包不支持)

CREATE TABLE host (

         hostname varchar(132) flag=1,

         domain   varchar(132) flag=2,

         ipaddr   char(16) flag=15,

         gateway  char(16) flag=17,

         dhcp     char(16) flag=18,

         leaseexp datetime flag=23

       ) ENGINE=CONNECT TABLE_TYPE=MAC;

       

SELECT * FROM host;