ClickHouse
ClickHouse Performance Observability: 9 Proven Signals We Trust in 26.9
ClickHouse performance observability on ClickHouse 26.9: nine system tables and endpoints, tested SQL, and a real Code 241 incident traced to one function.
clickhouse troubleshooting
ClickHouse
Advanced ClickHouse Troubleshooting on 26.8 LTS: 9 Proven Techniques for Slow Queries, Stuck Merges and Memory Errors
The ClickHouse troubleshooting method ChistaDATA uses on 26.8 LTS and 26.9: nine techniques, the system tables behind each, the queries we run, and one disk-full incident from our own lab.
ChistaDATA University
ClickHouse Troubleshooting Techniques: 8 Proven Drills We Teach
The ClickHouse troubleshooting techniques taught in CHT-400 at ChistaDATA University: a scope, prove, fix method and the diagnostic queries for eight production incidents, from too many parts to distributed timeouts.
ClickHouse
ClickHouse Sharding Troubleshooting and Performance Optimization
A field guide to ClickHouse sharding troubleshooting: Distributed send-queue backlogs, duplicate rows from internal_replication, shard skew, initiator merge bottlenecks, distributed JOIN failures and unavailable shards, each with the system.* evidence, the mechanism, the staged fix, and the alert that catches it early.
ClickHouse Sharding
ClickHouse Shard Contention Troubleshooting: A Complete Guide
ClickHouse shard contention is one of the most frustrating performance problems a distributed database team can face. When a cluster scales out to dozens or hundreds of nodes, the promise of linear scalability quietly breaks […]
ClickHouse Query Profiler
ClickHouse Query Profiling for Performance Monitoring
Introduction Creating a Python CLI (Command-Line Interface) application for custom profiling of ClickHouse Server queries involves several components. The application will allow users to input queries via the command line, execute them on a ClickHouse […]
ClickHouse Ingestion
ClickHouse High-Volume Data Ingestion: Server Configuration Guide
Optimizing ClickHouse for high-velocity and high-volume data loading involves several server configuration and tuning techniques.
ClickHouse Index
ClickHouse Index Granularity: Tuning index_granularity for Performance
Understanding index granularity is crucial for troubleshooting performance issues in ClickHouse, especially when it comes to optimizing how ClickHouse uses indexes for query execution.
ClickHouse Kubernetes
ClickHouse on Kubernetes: Running ClickHouse Cluster on Minikube
Introduction Kubernetes orchestration simplifies many common operational concerns like scheduling, auto-scaling, and failover. It has support for Persistent Volumes and Persistent Volume Claims ( PV & PVC ). Usually, databases that support replication, sharding, and […]
ClickHouse Backup & DR
ClickHouse Troubleshooting: How to Restore/Recover ClickHouse after ZooKeeper Metadata is Corrupted/Lost
Introduction When you are building a highly available ClickHouse Infrastrstucture for scale and performance we use ZooKeeper for ClickHouse Replication Management and Operations with ReplicatedMergeTree table engine. You can expect ZooKeeper to face data loss […]