Clickhouse Best Practices

ClickHouse Best Practices

Insert Best Practices

• Batch 10k-100k rows per insert; max 1-2 inserts/sec per table
• Sub-1k-row inserts cause part proliferation; insert in sorting-key order to reduce merge work
• For bulk loads, tune min_insert_block_size_rows / max_insert_block_size_rows

Async Inserts

• SET async_insert = 1; SET wait_for_async_insert = 1; (1=durable, 0=fire-and-forget)
• Tune async_insert_max_data_size (1M) and async_insert_busy_timeout_ms (10s) for batch window

Query Cache (v23.5+)

• SET allow_experimental_query_cache = 1; SET use_query_cache = 1;
• TTL: query_cache_ttl; share across users: query_cache_shared_between_users = 1
• Control: enable_writes_to_query_cache, enable_reads_from_query_cache

Connection Pooling

• HTTP: set pool_size, max_queries; keep-alive is critical
• TCP: built-in multiplexing; tune max_connections
• Monitor system.metrics for HTTPConnection/TCPConnection to size pools

Production Settings

• max_threads — lower for concurrent loads; max_insert_threads — raise for parallel inserts
• max_execution_time / max_memory_usage — per-query limits
• join_algorithm — prefer grace_hash or auto for large joins
• input_format_allow_errors_num / ratio — tolerate parse errors in bulk imports

Query Patterns

• COLUMNS('pattern') — regex column selection; APPLY func transforms matches
• clusterAllReplicas('cluster') — aggregate across all replicas
• FINAL — force merge for ReplacingMergeTree; use sparingly (full scan)