Quix Streams Release 3.16.0

Quix Streams 3.16.0: Accelerating R&D Data Pipelines with Enhanced Enrichment

Quix Streams 3.16.0 delivers critical enhancements for engineering teams managing complex R&D data workflows. This release focuses on improving data enrichment capabilities and system performance, specifically designed to accelerate the design-validation cycle in hardware development and testing environments.

Key Feature: Seamless Integration with R&D Data Sources

The experimental StreamingDataFrame.join_lookup() method enables real-time enrichment of test and simulation data with reference information from existing engineering systems. This addresses a critical need for integrating live test data with Model-Based Development tools like MATLAB and Simulink.

# Example usage of the new join_lookup
enriched_stream = stream.join_lookup(    
    lookup_func=query_database,  # Your custom lookup function    
    data_identifier="user_id",   # Field to match on    
    stateful=False               # Whether to cache results
)

Performance Optimizations for Engineering Workloads

Version 3.16.0 introduces optimizations specifically beneficial for handling large volumes of time-series data common in engineering applications:

Performance and Stability Improvements

Version 3.16.0 includes several under-the-hood optimizations:‍

1. RocksDB Column Family Management: Reduces memory overhead by up to 40% for applications managing multiple test configurations, enabling more efficient processing of high-frequency sensor data.‍

2. Topic Handling Refactoring: Improves reliability when managing multiple data streams from test rigs and simulation environments, with enhanced error recovery mechanisms.‍

3. Windowed Reducer Fix: Ensures accurate statistical analysis of time-series data, critical for engineering validation and verification processes.

Real-World Applications for Engineering Teams

New resources demonstrate practical applications for R&D organizations:‍

• Test Data Enrichment Guide: Step-by-step tutorial on enriching live test data with configuration parameters and reference models
• Simulation-Data Correlation: Example implementation for correlating real-world test results with simulation outputs
• Regulatory Compliance: Best practices for maintaining data lineage and audit trails in regulated environments

Getting Started

Upgrade to Quix Streams 3.16.0 using pip:‍

pip install quixstreams==3.16.0

‍

More Information

For detailed documentation and examples, visit the Quix Streams documentation and for the full release note visit GitHub.

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Note: The join_lookup feature is currently marked as experimental. We encourage users to test it in non-production environments and provide feedback to help shape its future development.