ClickHouse Troubleshooting: Impact of External Cache on Internal Cache Efficiency


Using external caching mechanisms alongside ClickHouse can sometimes interfere with or ‘ruin’ the effectiveness of ClickHouse’s internal caching, leading to suboptimal performance.

Understanding why this happens requires insight into how ClickHouse manages data and memory. Here’s an explanation:

ClickHouse Internal Caching

  1. Mark Cache: Stores index marks for primary and secondary indices, speeding up data selection processes.
  2. Data Cache: ClickHouse may cache data blocks in memory, depending on the query and data structure.
  3. Query Result Cache: Some results might be cached, depending on the configuration and query type.
  4. Efficient MergeTree Engines: Designed to minimize unnecessary reads and writes.

Impact of ClickHouse External Caching

  1. Duplicate Caching: External caching (like OS file system cache or third-party caching tools) might duplicate what ClickHouse already caches. This can lead to inefficient memory usage, as the same data is stored twice in RAM.
  2. Memory Overhead: Extra memory used by external caches can starve ClickHouse of the memory it needs for its internal operations, reducing its ability to cache effectively.
  3. I/O Patterns Interference: ClickHouse optimizes I/O patterns based on its caching logic. External caching mechanisms can disrupt these patterns, leading to less efficient data retrieval and increased I/O wait times.
  4. Cache Invalidation Issues: External caches may not be as finely tuned to the specific invalidation requirements of ClickHouse data, leading to stale data being served or unnecessary cache refreshes.
  5. Increased Complexity: Relying on external caching adds complexity to the system, making it harder to diagnose performance issues or optimize the data handling pipeline.
  6. Reduced Predictability: With external caching, the predictability of performance can decrease. ClickHouse’s internal caching is designed to offer consistent performance, which can be undermined by external factors.

Recommendations for ClickHouse Caching

  1. Memory Allocation: Ensure that ClickHouse has enough allocated memory for its internal caching mechanisms to work effectively.
  2. Understand Workload Patterns: Tailor caching strategies to your specific workload patterns. What works for one type of query or data might not work for another.
  3. Monitoring and Testing: Regularly monitor performance and test the impact of any external caching solutions. Sometimes, the perceived benefits of external caching might not materialize in practice.
  4. Configuration Tuning: Tune ClickHouse settings like mark_cache_sizemax_bytes_in_join, and max_bytes_before_external_group_by to optimize internal caching.
  5. Avoid Unnecessary External Caching: If ClickHouse is effectively managing its cache, additional layers of caching may not be necessary and could be disabled to free up resources.


External caching solutions can potentially conflict with ClickHouse’s internal caching mechanisms, leading to reduced efficiency and performance. It’s crucial to understand the unique caching behaviors of ClickHouse and configure your environment in a way that leverages these capabilities to the fullest, rather than inadvertently undermining them.

To read more about ClickHouse Caches, do consider reading the below articles

About Shiv Iyer 222 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.