最后更新: 2020-09-13
在 MySQL 里,为了保证高可用以及数据安全性会采取主从模式,数据通过 binlog 来进行同步。
在 ClickHouse 里,我们可以使用 ReplicatedMergeTree 引擎,数据同步通过 zookeeper 完成。
本文先从搭建一个多 replica 集群开始,然后一窥底层的机制,简单吃两口。
1. 集群搭建 搭建一个 2 replica 测试集群,由于条件有限,这里在同一台物理机上起 clickhouse-server(2个 replica) + zookeeper(1个),为了避免端口冲突,两个 replica 端口会有所不同。
1.1 zookeeper 1 docker run -p 2181:2181 --name some-zookeeper --restart always -d zookeeper
1.2 replica集群 replica-1 config.xml:
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 <zookeeper> <node index="1"> <host>172.17.0.2</host> <port>2181</port> </node> </zookeeper> <remote_servers> <mycluster_1> <shard_1> <internal_replication>true</internal_replication> <replica> <host>s1</host> <port>9000</port> </replica> <replica> <host>s2</host> <port>9001</port> </replica> </shard_1> </mycluster_1> </remote_servers> <macros> <cluster>mycluster_1</cluster> <shard>1</shard> <replica>s1</replica> </macros> <tcp_port>9101</tcp_port> <interserver_http_port>9009</interserver_http_port> <path>/cluster/d1/datas/</path>
replica-2 config.xml:
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 <zookeeper> <node index="1"> <host>172.17.0.2</host> <port>2181</port> </node> </zookeeper> <remote_servers> <mycluster_1> <shard_1> <internal_replication>true</internal_replication> <replica> <host>s1</host> <port>9000</port> </replica> <replica> <host>s2</host> <port>9001</port> </replica> </shard_1> </mycluster_1> </remote_servers> <macros> <cluster>mycluster_1</cluster> <shard>1</shard> <replica>s2</replica> </macros> <tcp_port>9102</tcp_port> <interserver_http_port>9010</interserver_http_port> <path>/cluster/d2/datas/</path>
1.3 创建测试表 1 2 3 4 5 6 7 8 9 CREATE TABLE default.rtest1 ON CLUSTER 'mycluster_1' ( `id` Int64, `p` Int16 ) ENGINE = ReplicatedMergeTree('/clickhouse/tables/replicated/test', '{replica}') PARTITION BY p ORDER BY id
1.4 查看 zookeeper 1 2 3 4 5 docker exec -it some-zookeeper bash ./bin/zkCli.sh [zk: localhost:2181(CONNECTED) 17] ls /clickhouse/tables/replicated/test/replicas [s1, s2]
两个 replica 都已经注册到 zookeeper。
2. 同步原理 如果在 replica-1 上执行了一条写入:
1 replica-1> INSERT INTO rtest VALUES(33,33);
数据是如何同步到 replica-2 的呢?
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 s1. replica-1> StorageReplicatedMergeTree::write --> ReplicatedMergeTreeBlockOutputStream::write(const Block & block) s2. replica-1> storage.writer.writeTempPart,写入本地磁盘 s3. replica-1> ReplicatedMergeTreeBlockOutputStream::commitPart s4. replica-1> StorageReplicatedMergeTree::getCommitPartOp,提交LogEntry到zookeeper,信息包括: ReplicatedMergeTreeLogEntry { type: GET_PART, source_replica: replica-1, new_part_name: part->name, new_part_type: part->getType } s5. replica-1> zkutil::makeCreateRequest(zookeeper_path + "/log/log-0000000022"),更新log_pointer到zookeeper s6. replica-2> StorageReplicatedMergeTree::queueUpdatingTask(),定时pull任务 s7. replica-2> ReplicatedMergeTreeQueue::pullLogsToQueue ,拉取 s8. replica-2> zookeeper->get(replica_path + "/log_pointer") ,向zookeeper获取当前replica已经同步的位点 s9. replica-2> zookeeper->getChildrenWatch(zookeeper_path + "/log") ,向zookeeper获取所有的LogEntry信息 s10. replica-2> 根据同步位点log_pointer从所有LogEntry中筛选需要同步的LogEntry,写到queue s11. replica-2> StorageReplicatedMergeTree::queueTask,消费queue任务 s12. replica-2> StorageReplicatedMergeTree::executeLogEntry(LogEntry & entry),根据LogEntry type执行消费 s13. replica-2> StorageReplicatedMergeTree::executeFetch(LogEntry & entry) s14. replica-2> StorageReplicatedMergeTree::fetchPart,从replica-1的interserver_http_port下载part目录数据 s15. replica-2> MergeTreeData::renameTempPartAndReplace,把文件写入本地并更新内存meta信息 s16. replica-2> 数据同步完成
也可以进入 zookeeper docker 内部直接查看某个 LogEntry:
1 2 3 4 5 6 7 [zk: localhost:2181(CONNECTED) 85] get /clickhouse/tables/replicated/test/log/log-0000000022 format version: 4 create_time: 2020-09-13 16:39:05 source replica: s1 block_id: 33_2673203974107464807_7670041793554220344 get 33_2_2_0
3. 总结 本文以写入为例,从底层分析了 ClickHouse ReplicatedMergeTree 的工作原理,逻辑并不复杂。
不同 replica 的数据同步需要 zookeeper(目前社区有人在做etcd的集成 pr#10376 )做元数据协调,是一个订阅/消费模型,涉及具体数据目录还需要去相应的 replica 通过 interserver_http_port 端口进行下载。
replica 的同步都是以文件目录为单位,这样就带来一个好处:我们可以轻松实现 ClickHouse 的存储计算分离 ,多个 clickhouse-server 可以同时挂载同一份数据进行计算,而且这些 server 每个节点都是可写,虎哥已经实现了一个可以 work 的原型,详情请参考下篇 <存储计算分离方案与实现> 。
4. 参考 [1] StorageReplicatedMergeTree.cpp [2] ReplicatedMergeTreeBlockOutputStream.cpp [3] ReplicatedMergeTreeLogEntry.cpp [4] ReplicatedMergeTreeQueue.cpp