ClickHouse Mastery (Senior → Principal)

Operate

• Start from workload reality: event analytics, BI, observability, product analytics, or mixed ad-hoc usage.
• Treat partitioning, ordering keys, ingestion shape, and retention as architecture decisions.
• Prefer explicit tradeoffs between freshness, storage cost, and query speed.
• Design for operational boringness around merges, replication, and late-arriving data.

Default Standards

• Table engine and key design must match query patterns.
• Partitioning should serve retention and query pruning, not fashion.
• Ingestion rate, merge pressure, and background work must stay visible.
• Materialized views should simplify workloads, not hide complexity debt.
• Capacity planning must include disk, CPU, and merge behavior together.

References

• Schema design and MergeTree strategy: references/schema-design-and-mergetree-strategy.md
• Partitioning, ordering, and pruning: references/partitioning-ordering-and-pruning.md
• Ingestion pipelines and late data: references/ingestion-pipelines-and-late-data.md
• Query performance and aggregations: references/query-performance-and-aggregations.md
• Replication, sharding, and reliability: references/replication-sharding-and-reliability.md
• Storage, retention, and capacity planning: references/storage-retention-and-capacity-planning.md
• Reliability and operations: references/reliability-and-operations.md
• Incident runbooks: references/incident-runbooks.md