MyCat 学习笔记 第十一篇.数据分片 之 分片数据查询 ( select * from table_name limit 100000,100 )

1 环境说明

VM 模拟3台MYSQL 5.6 服务器

　　 VM1 192.168.31.187：3307

　　 VM2 192.168.31.212：3307

　　 VM3 192.168.31.150:  3307

 

MYCAT 1.5 服务部署在宿主机上

　　MYCAT 192.168.31.207 :8806【SQL执行端口】 / 9066【管理端口】

 

2 应用场景

2.0 MYCAT配置

schema.xml

<schema name="TESTDB" checkSQLschema="false" sqlMaxLimit="100">
　　<table name="t_demo_travel_record" dataNode="dn1,dn2,dn3" rule="auto-sharding-long" />
　　<table name="t_demo_travel_record_child" dataNode="dn1,dn2,dn3" rule="auto-sharding-long" />
</schema>

<dataNode name="dn1" dataHost="vm1" database="test" />
<dataNode name="dn2" dataHost="vm2" database="test" />
<dataNode name="dn3" dataHost="vm3" database="test" />

<dataHost name="vm1" maxCon="1000" minCon="10" balance="0"
　　writeType="0" dbType="mysql" dbDriver="native" switchType="1" slaveThreshold="100">
　　<heartbeat>select user()</heartbeat>
　　<writeHost host="vm1M1" url="192.168.31.187:3307" user="root" password="root123"></writeHost>
</dataHost>

<dataHost name="vm2" maxCon="1000" minCon="10" balance="0"
　　writeType="0" dbType="mysql" dbDriver="native" switchType="1" slaveThreshold="100">
　　<heartbeat>select user()</heartbeat>
　　<writeHost host="vm2M1" url="192.168.31.212:3307" user="root" password="root123"></writeHost>

</dataHost>

<dataHost name="vm3" maxCon="1000" minCon="10" balance="0"
　　writeType="0" dbType="mysql" dbDriver="native" switchType="1" slaveThreshold="100">
　　<heartbeat>select user()</heartbeat>
　　<writeHost host="vm3M1" url="192.168.31.150:3307" user="root" password="root123"></writeHost>

</dataHost>

 

rule.xml

 

<tableRule name="auto-sharding-long">
　　<rule>
　　　　<columns>id</columns>
　　　　<algorithm>rang-long</algorithm>
　　</rule>
</tableRule>

 

<function name="rang-long"
　　class="org.opencloudb.route.function.AutoPartitionByLong">
　　<property name="mapFile">autopartition-long.txt</property>
　　<property name="defaultNode">0</property>
</function>

 

autopartition-long.txt

# range start-end ,data node index
# K=1000,M=10000.
0-500M=0
500M-1000M=1
1000M-1500M=2

 

 

2.1 模拟在3个数据库上保存了200多万条记录，验证下数据库查询的响应。

物理库上数据情况

VM1 192.168.31.187：3307  保存了74.8万条记录

mysql> SELECT min(id),max(id),count(1) FROM test.t_demo_travel_record;

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

| min(id) | max(id) | count(1) |

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

|   10000 | 5000000 |   748002 |

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

1 row in set (0.16 sec)

 

VM2 192.168.31.212：3307  保存了74.9万条记录

mysql> SELECT min(id),max(id),count(1) FROM test.t_demo_travel_record;

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

| min(id) | max(id)  | count(1) |

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

| 5000001 | 10000000 |   749500 |

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

1 row in set (0.17 sec)

 

 VM3 192.168.31.150:  3307 比VM2少一条记录

mysql> SELECT min(id),max(id),count(1) FROM test.t_demo_travel_record;

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

| min(id)  | max(id)  | count(1) |

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

| 10000001 | 14991498 |   749499 |

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

1 row in set (0.17 sec)

 

 MYCAT 192.168.31.207:  8806  一共224.7万条记录，最大记录从 VM1 结点获取，最大记录从 VM3 结点获取

mysql> SELECT min(id),max(id),count(1) FROM t_demo_travel_record;

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

| MIN0  | MAX1     | COUNT2  |

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

| 10000 | 14991498 | 2247001 |

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

1 row in set (0.31 sec)

 

在MYCAT中进行不指定排序的分页查询 ，从第100万条记录开始取100，浩时1.5秒，好久~~

mysql> select * from t_demo_travel_record where id between 4999980 and 14999980 limit 1000000,100;

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

| id       | context          |

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

| 13341025 | context_13341025 |

| 13341026 | context_13341026 |

| 13341027 | context_13341027 |

| 13341028 | context_13341028 |

| 13341029 | context_13341029 |

....

|  8320686 | context_8320686  |

|  8320687 | context_8320687  |

|  8320688 | context_8320688  |

|  8320689 | context_8320689  |

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

100 rows in set (1.50 sec)

 

看下日志，MYCAT是把 limit 1000000,100 改为 limit 0 , 1000100 往物理库中发送，速度一个字：不慢才怪。

02/02 23:41:47.958  DEBUG [$_NIOREACTOR-2-RW] (ServerQueryHandler.java:56) -ServerConnection [id=12, schema=TESTDB, host=192.168.31.207, user=test,txIsolation=3, autocommit=true, schema=TESTDB]select * from t_demo_travel_record where id between 4999980 and 14999980 limit 1000000,100

02/02 23:41:47.958  DEBUG [$_NIOREACTOR-2-RW] (EnchachePool.java:70) -SQLRouteCache hit cache ,key:TESTDBselect * from t_demo_travel_record where id between 4999980 and 14999980 limit 1000000,100

02/02 23:41:47.958  DEBUG [$_NIOREACTOR-2-RW] (NonBlockingSession.java:113) -ServerConnection [id=12, schema=TESTDB, host=192.168.31.207, user=test,txIsolation=3, autocommit=true, schema=TESTDB]select * from t_demo_travel_record where id between 4999980 and 14999980 limit 1000000,100, route={

   1 -> dn1{SELECT *

FROM t_demo_travel_record

WHERE id BETWEEN 4999980 AND 14999980

LIMIT 0, 1000100}

   2 -> dn2{SELECT *

FROM t_demo_travel_record

WHERE id BETWEEN 4999980 AND 14999980

LIMIT 0, 1000100}

   3 -> dn3{SELECT *

FROM t_demo_travel_record

WHERE id BETWEEN 4999980 AND 14999980

LIMIT 0, 1000100}

} rrs 

02/02 23:41:47.958  DEBUG [$_NIOREACTOR-2-RW] (MultiNodeQueryHandler.java:82) -execute mutinode query select * from t_demo_travel_record where id between 4999980 and 14999980 limit 1000000,100

02/02 23:41:47.958  DEBUG [$_NIOREACTOR-2-RW] (MultiNodeQueryHandler.java:97) -has data merge logic 

 

02/02 23:41:47.961  DEBUG [$_NIOREACTOR-3-RW] (MultiNodeQueryHandler.java:241) -on row end reseponse MySQLConnection [id=19, lastTime=1454427707947, user=root, schema=test, old shema=test, borrowed=true, fromSlaveDB=false, threadId=36, charset=utf8, txIsolation=3, autocommit=true, attachment=dn1{SELECT *

FROM t_demo_travel_record

WHERE id BETWEEN 4999980 AND 14999980

LIMIT 0, 1000100}, respHandler=org.opencloudb.mysql.nio.handler.MultiNodeQueryHandler@24e67429, host=192.168.31.187, port=3307, statusSync=null, writeQueue=0, modifiedSQLExecuted=false]

 

这里进行数据合并，好在使用了auto-sharding-long模式，如果是sharding-by-mod模式的话，数据是非连续离散在不同数据结点中，那合并起来就更慢了。

在大数据量分片分页查询时，MYCAT 可能会存在效率与内存占用问题。

02/02 23:41:49.392  DEBUG [BusinessExecutor6] (DataMergeService.java:296) -prepare mpp merge result for select * from t_demo_travel_record where id between 4999980 and 14999980 limit 1000000,100

02/02 23:41:49.393  DEBUG [BusinessExecutor6] (MultiNodeQueryHandler.java:324) -last packet id:105