ClickHouse materialized views behave as AFTER INSERT triggers that fire per block, not as scheduled snapshots. Key engineering details covered: the block-level trigger model and its insert latency implications, why explicit TO syntax is mandatory, how SummingMergeTree and AggregatingMergeTree handle partial aggregations differently, the silent data corruption caused by using non-additive aggregates (uniq, avg, quantile) without the State/Merge pattern, write amplification benchmarks showing up to 90% throughput reduction with ten chained MVs, painful schema migration procedures, correct backfill strategy using partition-sized chunks instead of POPULATE, and scenarios where MVs are the wrong tool entirely. Alternatives including Projections, Refreshable MVs, and upstream pipeline pre-aggregation are also discussed.
Table of contents
The Insert Trigger ModelDesigning the Target TableThe Aggregation Gotchas You Need to KnowOperational Costs: Write Amplification, Schema Changes, BackfillingWhen to Skip ThemSort: