Knowledge Base

ClickHouse Keeper improves upon ZooKeeper with features like reduced disk space usage, faster recovery, and less memory consumption, offering better performance for ClickHouse clusters.

Learn how to calculate the ratio of empty or zero values in every column of a ClickHouse table to optimize sparse column serialization.

ClickHouse is popular for logs and metrics analysis because of the real-time analytics capabilities provided. Ready to find out more?

Learn how to connect to ClickHouse Cloud Service using Python with a step-by-step example using the clickhouse-connect driver.

Learn how to validate that two ClickHouse queries produce identical result-sets using hash functions and comparison techniques.

Learn how to resolve the SSL Exception CERTIFICATE_VERIFY_FAILED error.

This article explains how to resolve the DB::Exception error related to intersecting parts in ClickHouse, often caused by a race condition or manual intervention in the ZooKeeper data.

TTL rules in ClickHouse are eventually applied, and you can control when they are executed using the `merge_with_ttl_timeout` setting. Learn how to force TTL application and manage background threads for TTL execution.

Learn how to install and test ClickHouse on Windows 10 using WSL 2. Includes setup, troubleshooting, and running a test environment.

Learn how to use the `query_log` table in ClickHouse to identify the most memory and CPU-intensive queries across distributed nodes.