本文首发于 2020-09-15 20:15:14

《ClickHouse和他的敌人们》系列文章转载自圈内好友 BohuTANG 的博客,原文链接:
https://bohutang.me/2020/09/1...
以下为注释。

在 MySQL 里,为了保障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,咱们能够应用 ReplicatedMergeTree 引擎,数据同步通过 zookeeper 实现。

本文先从搭建一个多 replica 集群开始,而后一窥底层的机制,简略吃两口。

1. 集群搭建

搭建一个 2 replica 测试集群,因为条件无限,这里在同一台物理机上起 clickhouse-server(2个 replica) + zookeeper(1个),为了防止端口抵触,两个 replica 端口会有所不同。

1.1 zookeeper

docker run  -p 2181:2181 --name some-zookeeper --restart always -d zookeeper

1.2 replica集群

replica-1 config.xml:

<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:

<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 创立测试表

CREATE TABLE default.rtest1 ON CLUSTER 'mycluster_1'(    `id` Int64,    `p` Int16)ENGINE = ReplicatedMergeTree('/clickhouse/tables/replicated/test', '{replica}')PARTITION BY pORDER BY id

1.4 查看 zookeeper

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 都曾经注册到 zookeeper。

2. 同步原理

如果在 replica-1 上执行了一条写入:

replica-1> INSERT INTO rtest VALUES(33,33);

数据是如何同步到 replica-2 的呢?

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::commitParts4.  replica-1> StorageReplicatedMergeTree::getCommitPartOp,提交LogEntry到zookeeper,信息包含:    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zookeepers6.  replica-2> StorageReplicatedMergeTree::queueUpdatingTask(),定时pull工作s7.  replica-2> ReplicatedMergeTreeQueue::pullLogsToQueue ,拉取s8.  replica-2> zookeeper->get(replica_path + "/log_pointer") ,向zookeeper获取以后replica曾经同步的位点s9.  replica-2> zookeeper->getChildrenWatch(zookeeper_path + "/log") ,向zookeeper获取所有的LogEntry信息s10. replica-2> 依据同步位点log_pointer从所有LogEntry中筛选须要同步的LogEntry,写到queues11. replica-2> StorageReplicatedMergeTree::queueTask,生产queue工作s12. replica-2> StorageReplicatedMergeTree::executeLogEntry(LogEntry & entry),依据LogEntry type执行生产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> 数据同步实现

也能够进入 zookeeper docker 外部间接查看某个 LogEntry:

[zk: localhost:2181(CONNECTED) 85] get /clickhouse/tables/replicated/test/log/log-0000000022format version: 4create_time: 2020-09-13 16:39:05source replica: s1block_id: 33_2673203974107464807_7670041793554220344get33_2_2_0

3. 总结

本文以写入为例,从底层剖析了 ClickHouse ReplicatedMergeTree 的工作原理,逻辑并不简单。

不同 replica 的数据同步须要 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/生产模型,波及具体数据目录还须要去相应的 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,这样就带来一个益处:咱们能够轻松实现 ClickHouse 的存储计算拆散,多个 clickhouse-server 能够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,虎哥曾经实现了一个能够 work 的原型,详情请参考下篇 <存储计算拆散计划与实现>。

4. 参考

  • [1]StorageReplicatedMergeTree.cpp
  • [2]ReplicatedMergeTreeBlockOutputStream.cpp
  • [3]ReplicatedMergeTreeLogEntry.cpp
  • [4]ReplicatedMergeTreeQueue.cpp

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