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HomeClickHouse Observability

ClickHouse Observability

ClickHouse performance observability map from query stages to system tables
ClickHouse

ClickHouse Performance Observability: 9 Proven Signals We Trust in 26.9

ChistaDATA Inc.
ClickHouse performance observability on ClickHouse 26.9: nine system tables and endpoints, tested SQL, and a real Code 241 incident traced to one function.

[…]

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

  • ClickHouse Performance Observability: 9 Proven Signals We Trust in 26.9
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  • ClickHouse Query Execution Explained: 4 Proven Stages From INSERT to Distributed JOIN
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Contents

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  • What ClickHouse performance observability means in 26.9
  • What changed for ClickHouse monitoring in 26.7, 26.8 and 26.9
  • Turn the evidence on: the ClickHouse observability config we deploy
  • A ClickHouse performance triage tree: symptom first
  • system.processes: ClickHouse performance while the query is still running
  • system.query_log: name the query fingerprint behind the ClickHouse performance problem
  • EXPLAIN ANALYZE: see where ClickHouse performance went, step by step
  • system.query_metric_log: how ClickHouse query memory grew, second by second
  • system.trace_log: which ClickHouse function used the CPU and the memory
  • system.processors_profile_log: is the query CPU-bound or starved for data?
  • system.part_log: ClickHouse insert performance and merge pressure
  • metric_log and asynchronous_metric_log: ClickHouse monitoring for the whole node
  • The Prometheus endpoint: ClickHouse performance monitoring outside the server
  • Allocation profiling with system.jemalloc_sampled_allocations
  • What did not work, and what caught us out
  • The ClickHouse performance observability checklist we hand to on-call
  • ClickHouse performance observability: common questions
    • Which system table should I check first for a slow ClickHouse query?
    • How do I find out why a ClickHouse query exceeded the memory limit (Code 241)?
    • Is EXPLAIN ANALYZE safe to run on production ClickHouse?
    • Does the ClickHouse query profiler slow the server down?
    • What should I alert on for ClickHouse monitoring?
  • Related ChistaDATA guides and sources
  • Want this run on your own ClickHouse cluster?
→ Index