Implementation of Cross-Cluster Queries in ClickHouse (Data Distribution and Access Strategies)

Cross-cluster queries are a complex and important concept in ClickHouse, allowing you to extract data from different clusters and perform calculations. This capability is crucial for managing large-scale data clusters.

Data Distribution

In ClickHouse, data distribution is achieved through the use of replication and partition. Replication involves copying part or all of your data into another cluster, while partitioning divides data into smaller subsets to facilitate access and management.

Replication

Replication is a key feature in ClickHouse that allows you to replicate data from one cluster to another, enabling cross-cluster queries.

  • Single table replication: When using the replicate statement, ClickHouse replicates all rows of your table into the specified clusters.
  • Multi-table replication: When using the create materialized view statement, ClickHouse creates a view and replicates it entirely whenever you update the underlying tables.

Partitioning

Partitioning is another important feature in ClickHouse that allows you to organize data into smaller subsets for easier access and management.

  • Static partitioning: When using the partition by statement, ClickHouse partitions your table based on a specified column and creates multiple files.
  • Dynamic partitioning: When using the partition range statement, ClickHouse partitions your table based on specific ranges.

Access Strategies

In ClickHouse, access strategies refer to how data is extracted from different clusters before performing calculations.

Read Access

Read access is the most common method; when you use the select statement, ClickHouse attempts to extract required data from each cluster and returns it to you.

  • Local read: When using the select from statement, ClickHouse reads directly from your table to retrieve the necessary data.
  • Distributed read: When using the select from ... using statement, ClickHouse extracts the required data from different clusters and returns it to you.

Write Access

Write access refers to adding new data into ClickHouse, which also requires cross-cluster queries across different clusters.

  • Local write: When using the insert into statement, ClickHouse writes directly to your table.
  • Distributed write: When using the insert into ... using statement, ClickHouse extracts required data from different clusters and adds new data to these clusters.

Cross-cluster Views

Cross-cluster views are an important concept in ClickHouse that allow you to create a view based on multiple tables within one cluster, enabling cross-cluster queries.

  • Creating a cross-cluster view: When using the create materialized view statement, ClickHouse creates a multi-table view and replicates it entirely whenever you update the underlying tables.
  • Using a cross-cluster view: When using the select from statement, ClickHouse extracts required data from different clusters and returns it to you.