ClickHouse Caches: Configuring Buffer Cache for High Performance

Introduction

The ClickHouse Buffer Cache works by caching frequently accessed data in memory. This cache reduces disk I/O operations and speeds up query performance.

The buffer cache is organized as a pool of memory blocks, each of which can contain a portion of a table’s data. When a query requests data, the buffer cache is first checked for the requested data. If the data is found in the cache, it is returned immediately, without the need for a disk I/O operation. If the data is not found in the cache, it is read from disk and then cached in memory for future use.

The buffer cache operates on a least-recently-used (LRU) algorithm, which means that the oldest data in the cache is evicted first when new data needs to be cached. This ensures that the cache is always filled with the most frequently accessed data.

ClickHouse also implements a two-level buffer cache, which includes both a small, fast cache for frequently accessed data and a larger, slower cache for less frequently accessed data. This two-level cache ensures that hot data is always served quickly, while still providing a large pool of memory for the less frequently accessed data.

Configuration Parameters

ClickHouse has several configuration parameters that control memory management, which are critical for efficient and optimal performance. Some of the key parameters include:

  1. max_memory_usage: This setting determines the maximum amount of memory that can be used by ClickHouse for storing data, query processing, and other operations.
  2. memory_tracker_fault_probability: This setting specifies the probability of triggering a memory fault, which allows you to simulate low memory conditions and test the behavior of your queries under such conditions.
  3. memory_tracker_events_stack_size: This setting determines the maximum number of memory allocation events that can be stored in the memory tracker.
  4. readonly_max_buffer_size: This setting determines the maximum size of the buffer used for reading data during query processing.
  5. max_compress_block_size: This setting controls the maximum size of the blocks used by the compression library.
  6. join_use_nulls: This setting enables or disables the use of NULL values in join operations, which can have an impact on memory usage.
  7. max_threads: This setting determines the maximum number of concurrent threads that can be used by ClickHouse for query processing.
  8. max_block_size: This setting determines the maximum size of the blocks used by ClickHouse for storing data.

Conclusion

It’s important to carefully evaluate and adjust these parameters based on the specific requirements of your application and hardware resources. Monitoring key performance metrics, such as query execution time, memory usage, and CPU utilization, can also help you ensure that your memory management configuration is aligned with your workload and performance goals. Overall, the ClickHouse Buffer Cache is an important component in the performance optimization of ClickHouse. By caching frequently accessed data in memory, it reduces disk I/O operations and speeds up query performance, resulting in improved system performance and scalability.

If you would like to read more about Caches in ClickHouses, do consider reading the below articles:

About Shiv Iyer 225 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.