Comprehensive Guide for ClickHouse Storage Infrastructure Optimization

Introduction

Mastering ClickHouse storage optimization is the key to unlocking unparalleled data analytics performance.

Optimizing ClickHouse storage infrastructure is vital to ensure the database performs at its best, especially for large-scale data analytics tasks. ClickHouse is already well-optimized out of the box, but as with any database system, there are always adjustments that can be made based on the specifics of your workload and infrastructure.

Runbook for ClickHouse Storage Infrastructure Optimization

Use SSDs for Storage

  • Explanation: SSDs (Solid State Drives) provide faster data access times compared to traditional HDDs (Hard Disk Drives). ClickHouse performance, especially for queries, can benefit from the low-latency, high-IOPS characteristics of SSDs.
  • Benefits:
    • Faster query performance.
    • More consistent performance metrics.
  • Recommended Values: Always choose enterprise-grade SSDs for production workloads.

Partitioning

  • Explanation: ClickHouse supports table partitioning. By partitioning tables based on specific columns (usually date or range columns), you can ensure that queries touching only certain partitions read less data.
  • Benefits:
    • Improved query performance.
    • Easier data management and maintenance.
  • Recommended Values: Partition tables based on frequently filtered columns, often by month or week for time-based data.

MergeTree Settings

  • Explanation: ClickHouse’s primary storage engine is MergeTree. Adjusting its settings can improve storage performance.
  • Benefits:
    • Efficient data merges.
    • Controlled resource usage.
  • Recommended Values:
    • max_bytes_to_merge_at_max_space_in_pool: Adjust according to available disk space.
    • number_of_free_entries_in_pool_to_lower_max_size_of_merge: Set based on server’s workload and merge frequency.

Enable Compression

  • Explanation: ClickHouse supports data compression, and using efficient codecs can reduce the amount of storage used.
  • Benefits:
    • Reduced storage costs.
    • Improved I/O performance due to reading fewer bytes.
  • Recommended Values: Use the LZ4 codec for a balance of speed and compression or ZSTD for better compression ratios at a slightly higher CPU cost.

Adjust Index Granularity

  • Explanation: The index granularity in ClickHouse determines how often the database creates an index entry for a block of rows.
  • Benefits:
    • Higher granularities can speed up some range queries.
    • Lower granularities can reduce memory usage.
  • Recommended Values: Default is 8192. Adjust based on query patterns.

Use RAID for Redundancy and Performance

  • Explanation: RAID (Redundant Array of Independent Disks) can be used to pool multiple disks together. Depending on the RAID level, this can offer redundancy, performance improvements, or both.
  • Benefits:
    • Increased data reliability.
    • Potential performance improvements.
  • Recommended Values: RAID 10 (mirroring and striping) offers a good balance of redundancy and performance.

Network Storage Adjustments

  • Explanation: If using network-attached storage (NAS) or storage area networks (SAN), ensure the network link between the storage and ClickHouse servers is high-bandwidth and low-latency.
  • Benefits:
    • Avoid network bottlenecks.
    • Consistent storage performance.
  • Recommended Values: Use 10 Gbps or higher network links for storage.

Regularly Optimize Tables

  • Explanation: ClickHouse tables, especially MergeTree variants, benefit from occasional optimization, which merges parts and frees up space.
  • Benefits:
    • Reduced storage space.
    • Improved query performance.
  • Recommended Values: Run OPTIMIZE TABLE <tablename> FINAL during low-load periods, but not too frequently as it’s resource-intensive.

Adjust Background I/O Settings

  • Explanation: ClickHouse performs a variety of background I/O tasks. Their priority can be adjusted to avoid impacting foreground query performance.
  • Benefits:
    • More consistent query performance.
    • Efficient use of I/O resources.
  • Recommended Values:
    • background_schedule_pool_size: Set based on the number of physical cores.

Storage Policy and Volumes

  • Explanation: ClickHouse allows defining storage policies and volumes. This can be used to move older data to slower, cheaper storage.
  • Benefits:
    • Cost savings.
    • Efficient use of high-performance storage.
  • Recommended Values: Create a policy that moves data older than a certain age to slower storage tiers.

Conclusion

In conclusion, while ClickHouse is performant out of the box, understanding and tweaking its storage settings can lead to substantial improvements in both performance and cost efficiency. Always test any changes in a staging environment before applying them to production to ensure they have the desired effect.

To know more about storage optimization in ClickHouse, do consider reading the following 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.