1.E-R关系策略的由来
join是关系数据库最常用的一个特性,然而在分布式环境中,跨分片的join最复杂,最难解决。
这是官方文档的描述。
具体点,比如:
mycat逻辑库hello,两张表格t1,t2。做了分库策略,t1放到了datanode1,t2放到了datanode2。如果我t1 join t2检索数据,
怎么办?
这就是E-R关系策略要解决的问题。
mycat借鉴了table group的概念,将子表的存储位置依赖于子表,并且在物理上紧邻存放,解决了join的效率和性能问题。E-R关系的数据分片策略,根据这一思路,将子表的记录和所关联的父表记录存放在同一个数据分片上。
2.测试官方教程文档上的E-R关系表
customer采用sharding-by-intfile(分片枚举)策略,分片在dn1,dn2上,orders依赖父表进行分片,两个表的关联关系为orders.customer_id=customer.id。
<table name="customer" primaryKey="ID" dataNode="dn1,dn2" rule="sharding-by-intfile"> <childTable name="orders" joinKey="customer_id" parentKey="id"/> </table>
解释:
<table name="customer" primaryKey="ID" dataNode="dn1,dn2" rule="sharding-by-intfile">
这一行是定义customer表,主键是id,分片部署在dn1,dn2,分片规则是sharding-by-intfile
<childTable name="orders" joinKey="customer_id" parentKey="id"/>
这一行是定义orders是childtable。
childtable是依赖父表的结构,就是前面时候的E-R关系的表。
childtable的joinkey会按照父表的parentkey一起切分。
</table>
这是对应 <table name= 的结束格式,参考xml格式。
3.
表格设计:
customer表
id(primarykey) name city (用city做分片)
orders表
customer_id(primary key) orders
两表格关系:
customer表的主键id为orders表主键customer_id的外键
4.mycat上实际测试:
停止mycat服务,修改配置文件,如下:
[root@ha1 conf]# cat schema.xml <?xml version="1.0"?> <!DOCTYPE mycat:schema SYSTEM "schema.dtd"> <mycat:schema xmlns:mycat="http://io.mycat/"> <schema name="hello" checkSQLschema="false" sqlMaxLimit="100"> <!-- auto sharding by id (long) --> <table name="t1" dataNode="dn1,dn2" rule="sharding-by-intfile" /> <!-- global table is auto cloned to all defined data nodes ,so can join with any table whose sharding node is in the same data node --> <table name="t2" primaryKey="ID" type="global" dataNode="dn1,dn2" /> <table name="t3" dataNode="dn1" /> <table name="t4" dataNode="dn2" /> <table name="customer" primaryKey="id" dataNode="dn1,dn2" rule="sharding-by-intfile"> <childTable name="orders" joinKey="customer_id" parentKey="id"/> </table> </schema> <!-- <dataNode name="dn1$0-743" dataHost="localhost1" database="db$0-743" /> --> <dataNode name="dn1" dataHost="mysql1" database="db1" /> <dataNode name="dn2" dataHost="mysql3" database="db2" /> <dataHost name="mysql1" maxCon="1000" minCon="10" balance="3" writeType="0" dbType="mysql" dbDriver="native" switchType="1" slaveThreshold="100"> <heartbeat>select user()</heartbeat> <!-- can have multi write hosts --> <writeHost host="hostM1" url="192.168.211.138:3306" user="root" password="Alex2010@"> </writeHost> <writeHost host="hostS1" url="192.168.211.139:3306" user="root" password="Alex2010@"> </writeHost> </dataHost> <dataHost name="mysql3" maxCon="1000" minCon="10" balance="0" writeType="0" dbType="mysql" dbDriver="native" switchType="1" slaveThreshold="100"> <heartbeat>select user()</heartbeat> <!-- can have multi write hosts --> <writeHost host="hostM1" url="192.168.211.142:3306" user="root" password="Alex2010@"> <!-- can have multi read hosts --> <readHost host="hostS2" url="192.168.211.142:3306" user="root" password="Alex2010@"/> </writeHost> </dataHost> </mycat:schema>
定义分片规则:
<tableRule name="sharding-by-intfile"> <rule> <columns>city</columns> <algorithm>hash-int</algorithm> </rule> </tableRule>
<function name="hash-int" class="io.mycat.route.function.PartitionByFileMap"> <property name="mapFile">partition-hash-int.txt</property> <property name="type">1</property> <property name="defaultNode">0</property> </function>
[root@ha2 conf]# cat partition-hash-int.txt gz=0 sz=1
启动mycat,创建表格:
mysql> create table customer(id int not null primary key,name varchar(10),city varchar(20)); Query OK, 0 rows affected (0.11 sec)
mysql> create table orders (customer_id int not null primary key,orders int not null,foreign key(customer_id) references customer(id) on delete cascade on update cascade); Query OK, 0 rows affected (0.25 sec)
customer插入数据测试:
mysql> insert into customer(id,name,city) values(1,'am1','gz'),(2,'am2','gz'),(3,'am3','sz'); mysql> select * from customer where city='gz'; +----+------+------+ | id | name | city | +----+------+------+ | 1 | am1 | gz | | 2 | am2 | gz | +----+------+------+ 2 rows in set (0.08 sec)
mysql> explain select * from customer where city='gz'; +-----------+----------------------------------------------------+ | DATA_NODE | SQL | +-----------+----------------------------------------------------+ | dn1 | SELECT * FROM customer WHERE city = 'gz' LIMIT 100 | +-----------+----------------------------------------------------+ 1 row in set (0.01 sec)
gz的数据都在dn1实现了分片。
orders插入数据测试:
mysql> insert into orders(customer_id,orders) values(1,10001); Query OK, 1 row affected (0.33 sec) mysql> insert into orders(customer_id,orders) values(2,10002); Query OK, 1 row affected (0.29 sec) mysql> insert into orders(customer_id,orders) values(3,10003); Query OK, 1 row affected (0.48 sec)
根据E-R分片规则,orders表格根据外键的值也就是customer的主键值切分,
也就是orders.customer_id=customer.id的数据分在一个区。
分别在db1,db2检索数据,看看是否达到E-R分片的设计要求。