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Help Center/ MapReduce Service/ Service Overview/ Components/ ClickHouse/ ClickHouse Enhanced Open Source Features

ClickHouse Enhanced Open Source Features

Updated on 2024-08-28 GMT+08:00

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MRS ClickHouse has advantages such as automatic cluster mode, HA deployment, and smooth and elastic scaling.

Automatic Cluster Mode
As shown in Figure 1, a cluster consists of multiple ClickHouse nodes, which has no central node. It is more of a static resource pool. If the ClickHouse cluster mode is used for services, you need to pre-define the cluster information in the configuration file of each node. Only in this way, services can be correctly accessed.
Figure 1 ClickHouse cluster

Users are unaware of data partitions and replica storage in common database systems. However, ClickHouse allows you to proactively plan and define detailed configurations such as shards, partitions, and replica locations. The ClickHouse instance of MRS packs the work in a unified manner and adapts it to the automatic mode, implementing unified management, which is flexible and easy to use.

A ClickHouse instance consists of three ZooKeeper nodes and multiple ClickHouse nodes. The Dedicated Replica mode is used to ensure high reliability of dual data copies.
Figure 2 ClickHouse cluster structure
Smooth and Elastic Scaling
As business grows rapidly, MRS provides ClickHouse, a data migration tool, for scenarios such as the cluster's storage capacity or CPU compute resources approaching the limit. This tool is used to migrate some partitions of one or multiple MergeTree tables on several ClickHouseServer nodes to the same tables on other ClickHouseServer nodes. In this way, service availability is ensured and smooth capacity expansion is implemented.

When you add ClickHouse nodes to a cluster, use this tool to migrate some data from the existing nodes to the new ones for data balancing after the expansion.
HA Deployment Architecture
MRS uses the ELB-based high availability (HA) deployment architecture to automatically distribute user access traffic to multiple backend nodes, expanding service capabilities to external systems and improving fault tolerance. As shown in Figure 3, when a client application requests a cluster, Elastic Load Balance (ELB) is used to distribute traffic. With the ELB polling mechanism, data is written to local tables and read from distributed tables on different nodes. In this way, data read/write load and high availability of application access are guaranteed.

After the ClickHouse cluster is provisioned, each ClickHouse instance node in the cluster corresponds to a replica, and two replicas form a logical shard. For example, when creating a ReplicatedMergeTree table, you can specify shards so that data can be automatically synchronized between two replicas in the same shard.

Figure 3 HA deployment architecture