ClickHouse Troubleshooting: Understanding Estimated I/O and CPU Costs


In ClickHouse, like many database systems, performance troubleshooting and query optimization often involve understanding various metrics, including estimated I/O (Input/Output) costs and estimated CPU (Central Processing Unit) costs. These metrics are crucial for identifying potential bottlenecks and optimizing query performance. Let’s delve into the details of each.

Estimated I/O Costs

    • Definition: Estimated I/O costs refer to the expected amount of disk input/output operations required to execute a query. This estimation is crucial in database systems like ClickHouse, where data is often stored in a columnar format and can involve significant disk reads.
    • Factors Influencing I/O Costs: The size of the data, the efficiency of the data storage format (like compression), indexing, and the nature of the query (such as the need for full table scans versus using an index).
    • Performance Impact: High I/O costs can lead to slower query performance, especially if the disk subsystem is slow (e.g., HDDs compared to SSDs) or if there is high competition for I/O resources. I/O bottlenecks are often observed in disk-bound systems where the data processing speed is limited by the disk read/write speed.
    • Optimization Strategies: To reduce I/O costs, you can optimize table structures (like partitioning and indexing), use more efficient data formats, or upgrade hardware (like using faster SSDs).

Estimated CPU Costs

      • Definition: Estimated CPU costs represent the amount of CPU resources expected to be consumed when executing a query. This includes computations like filtering, aggregating, joining, and data transformation operations.
      • Factors Influencing CPU Costs: The complexity of the query, the amount of data processed, the types of operations (e.g., complex joins or aggregations), and the efficiency of the data processing algorithms.
      • Performance Impact: High CPU costs can lead to query performance issues, especially in CPU-bound systems where the processing speed is limited by CPU resources. This is particularly relevant for complex analytical queries common in ClickHouse.
      • Optimization Strategies: Optimizations include simplifying query logic, reducing the amount of data processed (e.g., filtering data earlier in the query), improving algorithm efficiency, and ensuring appropriate resource allocation based on workload.

Understanding the Difference for Troubleshooting in ClickHouse

  • Diagnosing Bottlenecks: By analyzing estimated I/O and CPU costs, you can diagnose whether a performance bottleneck is due to disk I/O or CPU processing. For instance, if the I/O cost is high but CPU cost is low, the issue might be related to disk access patterns or hardware limitations.
  • Query Plan Analysis: These estimates are often part of a query execution plan. Analyzing the plan can help you understand which parts of the query are most resource-intensive and need optimization.
  • Balanced Resource Usage: Effective performance tuning aims for a balance where neither CPU nor I/O is disproportionately a bottleneck. This involves a holistic approach to query design, indexing, hardware configuration, and database settings.


In conclusion, understanding the estimated I/O and CPU costs in ClickHouse is fundamental for effective performance troubleshooting. It helps in identifying whether the performance issues are due to disk I/O or CPU processing, guiding the direction for optimizations.

To learn more about Tuning & Troubleshooting CPU in ClickHouse, do consider reading the following articles:

About Shiv Iyer 215 Articles
Open Source Database Systems Engineer with a deep understanding of Optimizer Internals, Performance Engineering, Scalability and Data SRE. Shiv currently is the Founder, Investor, Board Member and CEO of multiple Database Systems Infrastructure Operations companies in the Transaction Processing Computing and ColumnStores ecosystem. He is also a frequent speaker in open source software conferences globally.