Cassandra 在2.1中的升级

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Cassandra在2.1中进行了很多有意思的升级，其中有一项升级，是非常不错的，那就是 User defined type，简称就是UDT，代表用户自顶一个类型。下面我们用一个例子来说明。
假如你要存放你的profile，这其中包括以下几个属性，name，email，phone…………，这个时候，一个用户可能有多个email，也可能有多个phone，用关系型数据库的想法，就是创建两个关联表，进行一对多的关联，但是现在我们有UDT后，可以这样来做。

CREATE TYPE address (      street text,      city text,      zip int  );  CREATE TABLE user_profiles (      login text PRIMARY KEY,      first_name text,      last_name text,      email text,      addresses map<text, frozen<address>>  );  // Inserts a user with a home address  INSERT INTO user_profiles(login, first_name, last_name, email, addresses)  VALUES ('tsmith',          'Tom',          'Smith',          'tsmith@gmail.com',          { 'home': { street: '1021 West 4th St. #202',                      city: 'San Fransisco',                      zip: 94110 }});  // Adds a work address for our user  UPDATE user_profiles     SET addresses = addresses                   + { 'work': { street: '3975 Freedom Circle Blvd',                                 city: 'Santa Clara',                                 zip: 95050 }}   WHERE login = 'tsmith';

我们先是创建了一个address的UDT，然后将它在profile中进行引用。使用UDT有很多好处，他非常的灵活，你可以在你的表用去引用这些UDT，同样可以在collection进行引用，同时UDT里面还可以继续定义UDT，假如address里面一个人有很多个phone，我们可以这样

CREATE TYPE phone (      number text,      tags set<text>  );  // Add a 'phones' field to address that is a set of the 'phone' UDT above  ALTER TYPE address ADD phones set<frozen<phone>>;

这样就达到了UDT里面嵌套UDT了，那么现在可以这样更新

UPDATE user_profiles     SET addresses['work'] = {             street: '3975 Freedom Circle Blvd',             city: 'Santa Clara',             zip: 95050,             phones : {               {number: '212 221 9165', tags: { 'preferred', 'direct line' }},               {number: '500 310 2342', tags: { 'fax' }}             }         }   WHERE login = 'tsmith';

然后我们来进行一个查询，结果会是这样

SELECT * FROM user_profiles;  login  | addresses                                                                                                                                                                                                                                                                       | email            | first_name | last_name  -------+---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+------------------+------------+-----------  tsmith | {'home': {street: '1021 West 4th St. #202', city: 'San Fransisco', zip: 94110}, 'work': {street: '3975 Freedom Circle Blvd', city: 'Santa Clara', zip: 95050, phones: {{number: '212 221 9165', tags: {'direct line', 'preferred'}}, {number: '500 310 2342', tags: {'fax'}}}}} | tsmith@gmail.com |        Tom |     Smith

使用了UDT后，我们的查询也可以用.的方式去查询，例如

CREATE TABLE location (      id int PRIMARY KEY,      addr frozen<address>, // Reuse the address type from above      longitude double,      latitude double  );  // The following is allowed  SELECT addr.street, addr.city FROM location WHERE id=42;

addr.street, addr.city这两个就是用.的方式去查询。
另外在2.1后，UDT可以作为Secondary index，例如

CREATE TABLE products (      id int PRIMARY KEY,      description text,      price int,      categories set<text>,      features map<text, text>  );  // This is now allowed in Cassandra 2.1  CREATE INDEX cat_index ON products(categories);  CREATE INDEX feat_index ON products(features);  INSERT INTO products(id, description, price, categories, features)       VALUES (34134,               '120-inch 1080p 3D plasma TV',               9999,               {'tv', '3D', 'hdtv'},               {'screen' : '120-inch', 'refresh-rate' : '400hz', 'techno' : 'plasma'});  INSERT INTO products(id, description, price, categories, features)       VALUES (29412,               '32-inch LED HDTV (black)',               929,               {'tv', 'hdtv'},               {'screen' : '32-inch', 'techno' : 'LED'});  INSERT INTO products(id, description, price, categories, features)       VALUES (38471,               '32-inch LCD TV',               110,               {'tv', 'used'},               {'screen' : '32-inch', 'techno' : 'LCD'});  // You can then query those index through CONTAINS  SELECT id, description FROM products WHERE categories CONTAINS 'hdtv';   id    | description  -------+-----------------------------   29412 |    32-inch LED HDTV (black)   34134 | 120-inch 1080p 3D plasma TV  SELECT id, description FROM products WHERE features CONTAINS '32-inch';   id    | description  -------+--------------------------   29412 | 32-inch LED HDTV (black)   38471 |           32-inch LCD TV

同时，上面我们是对map的value进行了创建index，你也可以通过key去创建index，例如

DROP INDEX feat_index;  CREATE INDEX feat_key_index ON products(KEYS(features));  SELECT id, description    FROM products    WHERE features CONTAINS KEY 'refresh-rate';   id    | description  -------+-----------------------------   34134 | 120-inch 1080p 3D plasma TV

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