Overview
ClickHouse Release 23.9 introduces a variety of new features, performance optimizations, and bug fixes aimed at enhancing user experience and functionality. Key highlights include type inference for JSON, a new GCD codec for improved compression, and support for SSH key authentication.
What You'll Learn
1
How to use type inference for JSON in ClickHouse to simplify schema definition
2
Why the GCD codec improves compression for decimal values in ClickHouse
3
How to authenticate with ClickHouse using SSH keys for easier access management
4
How to implement workload scheduling in ClickHouse to manage resource limits
Prerequisites & Requirements
- Basic understanding of ClickHouse and database concepts
- Familiarity with SQL and ClickHouse client tools(optional)
Key Questions Answered
What new features are introduced in ClickHouse Release 23.9?
ClickHouse Release 23.9 introduces 20 new features, 19 performance optimizations, and 55 bug fixes. Notable features include type inference for JSON, a new GCD codec for better compression, and support for SSH key authentication.
How does the GCD codec improve data compression in ClickHouse?
The GCD codec uses the Greatest Common Divisor algorithm to enhance compression for decimal values stored in ClickHouse. It reduces the scale of values, allowing other compression algorithms to work more effectively, resulting in significant size reductions.
How can users authenticate to ClickHouse using SSH keys?
Users can authenticate to ClickHouse by adding their public SSH key to the configuration file or via DDL. This allows them to connect without entering a password, streamlining access management across multiple clusters.
What is the purpose of workload scheduling in ClickHouse?
Workload scheduling in ClickHouse allows users to define resource limits for specific queries, ensuring that long-running queries do not negatively impact the performance of business-critical queries. This feature is essential for managing shared resources effectively.
Key Statistics & Figures
New features in ClickHouse 23.9
20
This includes significant enhancements like type inference for JSON and a new GCD codec.
Performance optimizations
19
These optimizations aim to improve the overall efficiency of ClickHouse operations.
Bug fixes
55
These fixes address various issues to enhance stability and performance.
Technologies & Tools
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Key Actionable Insights
1Utilize type inference for JSON to streamline your data ingestion process in ClickHouse.This feature allows users to automatically infer schemas from well-structured JSON data, reducing the overhead of manual schema definitions and making it easier for new users to get started.
2Implement the GCD codec for columns with high precision decimal values to achieve better compression.By applying the GCD codec, you can significantly reduce the size of your data storage, especially for large datasets where values change incrementally.
3Adopt SSH key authentication to simplify access management for ClickHouse clusters.This method enhances security and convenience, allowing users to connect without needing to remember multiple passwords for different clusters.
4Leverage workload scheduling to manage resource allocation for queries effectively.This feature is crucial for maintaining performance during heavy query loads, ensuring that critical operations are not disrupted by long-running tasks.
Common Pitfalls
1
Failing to define an optimized schema when using inferred schemas can lead to performance issues.
While inferred schemas simplify the initial setup, they may not provide the best performance. Users are encouraged to manually define schemas for production use.
Related Concepts
Data Compression Techniques
Database Authentication Methods
Workload Management In Databases