Topic
Column-store analytics: MergeTree design, partition and ordering keys, materialized views, and keeping system log tables from quietly eating the disk.
I have worked with ClickHouse since 2021, including in production systems and independent product experiments. It rewards careful ordering keys, partitions, and read-shaped models, then punishes weak choices quietly through merge pressure, part counts, and disk growth rather than a clean error. These notes focus on reproducible mechanics: MergeTree design, materialized views as incremental aggregation, query evidence, and the maintenance that keeps system logs from becoming the largest workload.
Attach StarRocks to the same Polaris REST catalog Trino writes through, measure both on identical data, and check for standing S3 keys.
~20 min, mostly waiting for the StarRocks backend to register