文档编写目的:记录备忘
1.环境搭建
4台centOS 7的主机,分别安装了四个ClickHouse数据库,安装参考:https://www.jianshu.com/p/2ce45a9c30ce
zookeeper集群(也可以不集群,直接使用单机也可以),集群参考:https://www.cnblogs.com/ysocean/p/9860529.html
2.新增配置文件metrika.xml
vim /etc/clickhouse-server/metrika.xml
本次4个数据库分两片,每片两个副本
<yandex>
<clickhouse_remote_servers>
<!--集群名称 自定义 -->
<my_cluster>
<!-- 分片1 -->
<shard>
<internal_replication>true</internal_replication>
<replica>
<host>192.168.120.87</host>
<port>9000</port>
<user>sunny</user>
<password>sunny</password>
</replica>
<replica>
<host>192.168.120.103</host>
<port>9000</port>
<user>sunny</user>
<password>sunny</password>
</replica>
</shard>
<!-- 分片2 -->
<shard>
<internal_replication>true</internal_replication>
<replica>
<host>192.168.120.105</host>
<port>9000</port>
<user>sunny</user>
<password>sunny</password>
</replica>
<replica>
<host>192.168.120.140</host>
<port>9000</port>
<user>sunny</user>
<password>sunny</password>
</replica>
</shard>
</my_cluster>
</clickhouse_remote_servers>
<!-- 副本名称 -->
<macros>
<shard>node01</shard>
<replica>192.168.120.87</replica>
</macros>
<networks>
<ip>::/0</ip>
</networks>
<!-- zookeeper -->
<zookeeper-servers>
<node index="1">
<host>192.168.120.87</host>
<port>2181</port>
</node>
<node index="2">
<host>192.168.120.103</host>
<port>2181</port>
</node>
<node index="3">
<host>192.168.120.105</host>
<port>2181</port>
</node>
</zookeeper-servers>
<!-- 数据压缩算法 -->
<clickhouse_compression>
<case>
<min_part_size>10000000000</min_part_size>
<min_part_size_ratio>0.01</min_part_size_ratio>
<method>lz4</method>
</case>
</clickhouse_compression>
</yandex>
通过scp将metrika.xml文件发送到其他三台服务器上
scp /etc/clickhouse-server/metrika.xml root@192.168.120.103:/etc/clickhouse-server/metrika.xml
然后修改其他三台服务器上的metrika.xml,仅修改图中红框代码,同一分片的<shard></shard>必须相同,互不重复,其他都不变:


然后编辑4个服务器上的config.xml,引入metrika.xml:
vim /etc/clickhouse-server/config.xml
加上下面这句:
<include_from>/etc/clickhouse-server/metrika.xml</include_from>

取消<interserver_http_host></interserver_http_host>这行的注释,值修改为当前服务器IP:

与metrika.xml文件中的此处对应,如下图红框:

重启服务:
service clickhouse-server restart
3.测试
此种集群适合表引擎为ReplicatedMergeTree的表,在每个服务器数据库创建如下表:
-- 本地表
create table department
(
id Int32,
dept_code String,
dept_name String,
createDate Date
) engine = ReplicatedMergeTree('/clickhouse/tables/{shard}/department', '{replica}', createDate,
(dept_code, createDate), 8192);
--分布式表
create table department_all as department ENGINE = Distributed(my_cluster, ClickHouseTest, department, rand());
插入数据:
insert into department_all (id, dept_code, dept_name, createDate) values (1, 1001, '肾脏内科', '2020-01-01');
insert into department_all (id, dept_code, dept_name, createDate) values (2, 1002, '肾脏内科', '2020-01-02');
insert into department_all (id, dept_code, dept_name, createDate) values (3, 1003, '肾脏内科', '2020-01-03');
insert into department_all (id, dept_code, dept_name, createDate) values (4, 1004, '肾脏内科', '2020-01-04');
insert into department_all (id, dept_code, dept_name, createDate) values (5, 1005, '肾脏内科', '2020-01-05');
insert into department_all (id, dept_code, dept_name, createDate) values (6, 1006, '肾脏内科', '2020-01-06');
insert into department_all (id, dept_code, dept_name, createDate) values (7, 1007, '肾脏内科', '2020-01-07');
insert into department_all (id, dept_code, dept_name, createDate) values (8, 1008, '肾脏内科', '2020-01-08');
insert into department_all (id, dept_code, dept_name, createDate) values (9, 1009, '肾脏内科', '2020-01-09');
insert into department_all (id, dept_code, dept_name, createDate) values (10, 1010, '肾脏内科', '2020-01-10');
insert into department_all (id, dept_code, dept_name, createDate) values (11, 1011, '肾脏内科', '2020-01-11');
insert into department_all (id, dept_code, dept_name, createDate) values (12, 1012, '肾脏内科', '2020-01-12');
insert into department_all (id, dept_code, dept_name, createDate) values (13, 1013, '肾脏内科', '2020-01-13');
insert into department_all (id, dept_code, dept_name, createDate) values (14, 1014, '肾脏内科', '2020-01-14');
insert into department_all (id, dept_code, dept_name, createDate) values (15, 1015, '肾脏内科', '2020-01-15');
分别查询87和103服务器上的department和department_all
查询结果如下:
87的department:

87的department_all:

103上的department:

103上的department_all:

87和103为同一个shard的不同副本,对比可以看出87和103上department表的数据相同,相互备份,其中一个服务器挂掉,也不会影响数据库的正常使用。105和140是另一个分片下的两个副本,存储的是上面插入数据的剩余部分,所以上图中两个department_all均为15条数据。
总结:此种方式为多分片多副本的集群方式,需要zookeeper+ReplicatedMergeTree引擎实现副本表的相互备份,本例中是两个副本,还可以增加,三个四个都行,当某个服务器数据库挂掉之后,还有剩余的副本正常工作,不会影响业务,从而实现高可用。
注意:当从分布式表插入重复数据时,不同分片中不会去重,多个分片之间会出现重复数据,在做数据采集时需要注意。