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This guide shows how to scale ClickHouse clusters with Spring Boot for high-performance queries and analytics.

1. Cluster Setup in ClickHouse

Create cluster configuration with multiple nodes. 
CREATE TABLE events_cluster ON CLUSTER my_cluster ( id UInt64, type String, ts DateTime ) ENGINE = ReplicatedMergeTree('/clickhouse/tables/{shard}/events', '{replica}') ORDER BY ts;
This ensures replication and high availability.

2. Distributed Table for Queries

Create a distributed table that routes queries across shards. 
CREATE TABLE events_distributed ON CLUSTER my_cluster AS events_cluster ENGINE = Distributed(my_cluster, default, events_cluster, rand());

3. Spring Boot Configuration

Set JDBC URL to distributed node or load balancer: 
spring.datasource.url=jdbc:clickhouse://clickhouse-proxy:8123/default spring.datasource.driver-class-name=com.clickhouse.jdbc.ClickHouseDriver

4. Repository for Cluster Queries

public interface EventRepository extends JpaRepository<Event, Long> { @Query(value = "SELECT type, count(*) FROM events_distributed GROUP BY type", nativeQuery = true) List<Object[]> countByType(); }

5. Batch Inserts into Cluster

Use the distributed table to insert data automatically across shards. 
jdbcTemplate.batchUpdate( "INSERT INTO events_distributed (id, type, ts) VALUES (?, ?, ?)", events, 1000, (ps, e) -> { ps.setLong(1, e.getId()); ps.setString(2, e.getType()); ps.setTimestamp(3, Timestamp.valueOf(e.getTs())); } );

6. Performance Tips

  • Use sharding keys for balanced data.
  • Enable compression in JDBC for faster transfers.
  • Monitor with system.merges and system.replication_queue.

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