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HomeClickHouse DBA Support

ClickHouse DBA Support

ClickHouse Performance Settings
ClickHouse

ClickHouse Performance Settings in 26.8 LTS: 14 Proven Changes

ChistaDATA Inc.
The ClickHouse performance settings that changed between 26.3 LTS and 26.8 LTS: what each default does to ingest, aggregation, joins and distributed execution, how to measure it, and the rollout method we use.

[…]

ClickHouse Troubleshooting Techniques
ChistaDATA University

ClickHouse Troubleshooting Techniques: 8 Proven Drills We Teach

ChistaDATA Inc.
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 certification and competency ladder at ChistaDATA University: CHT-100 to CHT-300 core levels, CHT-400 and CHT-500 specialist programmes, CHT-900 executive track, and the three certification tiers
ChistaDATA

ClickHouse Certification at ChistaDATA University: 3 Proven Tiers

ChistaDATA Inc.
How ChistaDATA University builds ClickHouse certification on a competency ladder: CHT-100 to CHT-900 programmes, real lab code, failure drills, a live-cluster capstone defence, corporate and academic delivery, and how to start.

[…]

ClickHouse Upgrade
ClickHouse DBA Support

ClickHouse Upgrade Guide: 6 Proven Steps for Zero-Downtime Rolling LTS Upgrades

ChistaDATA Inc.
A production ClickHouse upgrade done properly is a rolling, replica-by-replica operation with zero query downtime, a measured before/after regression check, and a rollback posture decided before the first package is installed. Done casually, it is […]
ClickHouse Ingestion Performance
ClickHouse

ClickHouse Ingestion Performance: Batch Sizing, Async Inserts, and Kafka Pipelines

ChistaDATA Inc.
ClickHouse ingestion performance is decided long before the query planner ever touches your data. It is decided by how many parts your writers create per second, how much background merge work those parts generate, and […]
ClickHouse Merge Performance
ClickHouse

ClickHouse Merge Performance: Diagnosing Too Many Parts, Slow Merges, and Stuck Mutations

ChistaDATA Inc.
ClickHouse merge performance is the hinge on which every high-ingest MergeTree deployment turns. When background merges keep pace with inserts, part counts stay flat and SELECT latency stays predictable. When they fall behind, the failure […]
ClickHouse MergeTree Optimization
ClickHouse

ClickHouse MergeTree Optimization: Sort Keys, Partitioning, Skip Indexes, and Projections

ChistaDATA Inc.
ClickHouse MergeTree optimization is the difference between a table that answers analytical queries in milliseconds and one that scans hundreds of gigabytes for every request. This guide is written for senior engineers who already understand […]
ClickHouse Query Performance Tuning
ClickHouse

ClickHouse Query Performance Tuning: A Production Diagnostic Playbook

ChistaDATA Inc.
Effective ClickHouse query performance tuning is less about magic settings and more about a repeatable diagnostic loop: measure, read the plan, isolate the bottleneck, change one variable, and re-measure. This playbook is written for senior […]
ClickHouse Performance Observability and Monitoring
ClickHouse

ClickHouse Performance Observability and Monitoring: A Complete Whitepaper

ChistaDATA Inc.
ClickHouse performance observability and monitoring is the discipline of measuring, visualizing, and continuously improving how a ClickHouse cluster behaves under real-world workloads. As organizations adopt ClickHouse to power sub-second analytics over petabyte-scale datasets, the gap […]
ClickHouse Performance
ClickHouse

20 Things You Should Not Do With ClickHouse Which Will Destroy ClickHouse Performance

ChistaDATA Inc.
ClickHouse is one of the fastest open source columnar databases for real-time analytics, and it powers observability platforms, product analytics, and large-scale reporting workloads across the industry. Yet raw speed can be deceptive. Many teams […]

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ChistaDATA is committed to open source software and building high performance ColumnStores

In the spirit of freedom, independence and innovation. ChistaDATA Corporation is not affiliated with ClickHouse Corporation 

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* Everything changes over time – Our blogs/posts and comments changes over time, That’s how it should be! Whatever we comment from ChistaDATA Inc. Teams (including Shiv Iyer) and other stakeholders or guest bloggers posted here are never permanent, These things worked for us. But, there is no guarantee they will work for you too, When using the recommendations from ChistaDATA or MinervaDB or MinervaSQL or any other online resources / Google,  You must test the advice before applying them to your production systems, and always invest for a robust Database DR solution, Thank you for understanding. 

Recent Posts from ChistaDATA

  • Real-Time Payments Analytics on ClickHouse: 6 Proven Layers for Southeast Asia
  • ClickHouse Performance Settings in 26.8 LTS: 14 Proven Changes
  • ClickHouse Troubleshooting Techniques: 8 Proven Drills We Teach
  • ClickHouse Certification at ChistaDATA University: 3 Proven Tiers
  • Real-Time Analytics on ClickHouse 26.8: 6 Proven Levers

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CHISTADATA IS COMMITTED TO OPEN SOURCE SOFTWARE AND BUILDING HIGH PERFORMANCE COLUMNSTORES

In the spirit of freedom, independence and innovation. ChistaDATA Corporation is not affiliated with ClickHouse Corporation 

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Licensed under the Apache License, Version 2.0 (the “License”); you may not use this file except in compliance with the License. You may obtain a copy of the License at

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Contents

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  • Why ClickHouse Performance Depends on What You Avoid
  • 1. Do Not Insert Rows One at a Time
  • 2. Do Not Ignore the ORDER BY Key
  • 3. Do Not Over-Partition Your Tables
  • 4. Do Not Use Nullable Columns Everywhere
  • 5. Do Not Run SELECT * on Wide Tables
  • 6. Do Not Rely on Mutations for Frequent Updates
  • 7. Do Not Forget About Data Skipping Indexes
  • 8. Do Not Use High-Cardinality Columns as the First Sort Key
  • 9. Do Not Join Huge Tables Without a Plan
  • 10. Do Not Ignore LowCardinality for Repetitive Strings
  • 11. Do Not Store Everything as String
  • 12. Do Not Overuse FINAL
  • 13. Do Not Neglect Compression Codecs
  • 14. Do Not Let Parts Pile Up Without Merges
  • 15. Do Not Query Without Partition or Primary Key Pruning
  • 16. Do Not Create Too Many Materialized Views on One Table
  • 17. Do Not Ignore max_memory_usage and Query Limits
  • 18. Do Not Use ClickHouse as a Key-Value Store
  • 19. Do Not Skip Replication and Backups Until It Is Too Late
  • 20. Do Not Fly Blind Without Monitoring
  • How ChistaDATA Helps You Protect ClickHouse Performance
  • Understanding the Root Cause of ClickHouse Performance Loss
  • A Practical Checklist to Preserve ClickHouse Performance
  • Scaling Without Sacrificing ClickHouse Performance
  • Frequently Asked Questions About ClickHouse Performance
    • What is the fastest way to improve ClickHouse performance?
    • Does partitioning improve ClickHouse performance?
    • Why does my ClickHouse query get slower over time?
    • Should I use FINAL to get correct results?
    • When should I bring in ClickHouse performance experts?
  • Conclusion
→ Index