ClickHouse Certified case studies

ClickHouse Certified · Put your knowledge to work in context.

The ClickHouse Certified credential is an independent study target for engineers, analysts, and data platform specialists who work with ClickHouse, the fast open-source OLAP database for real-time analytics. This page is an unofficial preparation resource built by an independent study platform; it is not affiliated with, endorsed by, or sponsored by ClickHouse, Inc., and it does not reproduce any commercial question bank. The ClickHouse Certified case studies are 5 cases and about 4,616 words.

Tenant dashboards scan 800 GB: fixing the sorting key on a 14-billion-row table

Your team runs a self-managed 6-node ClickHouse cluster holding an events table with 14 billion rows (~90 TB compressed). Ingest is ~1.5 TB/day, appended by a Kafka pipeline.

713 words, about 4 min 2

CDC updates show duplicate orders: ReplacingMergeTree semantics in practice

An orders table receives CDC from PostgreSQL via Debezium into Kafka and then into ClickHouse. It holds 250 million rows, with ~40,000 updates per hour against ~5,000 inserts.

942 words, about 5 min 3

Nightly uniqExact report hits the memory limit on a distributed join

A 3-shard, 2-replica cluster (64 GB RAM per node, max memory usage = 30 GiB , disk spilling disabled) runs a nightly report. ) to a local table pages (12 million rows; page id, page url ) and computes count() and uniqExact(user id) grouped by page url over the last 30 days.

1,041 words, about 5 min 4

Too many parts from single-row inserts, plus a lagging Kafka consumer

A Go service collects clickstream events and sends one HTTP request per event: roughly 2,500 single-row INSERT INTO clicks VALUES (...) statements per second into a 3-shard cluster with 2 replicas per shard. Tables are ReplicatedMergeTree with PARTITION BY toYYYYMMDD(event time) and ORDER BY (event time, user id) .

960 words, about 5 min 5

ClickHouse Cloud: noisy-neighbour BI load, tenant isolation and private networking

A 120-person analytics team runs ClickHouse Cloud on AWS in us-east-1 with one production service. Three clients share it: a BI tool using a single shared service account that refreshes 60 dashboards every 10 seconds; about 120 analysts running ad-hoc SQL through a web SQL editor; and an ingestion job loading 400 million rows/day.

960 words, about 5 min