DeepSketch - A New Machine Learning-Based Reference Search Technique for Post-Deduplication Delta Compression
Explore a cutting-edge machine learning-based reference search technique for post-deduplication delta compression in this 15-minute conference talk from FAST '22. Learn about DeepSketch, a novel approach that leverages deep neural networks to extract data block sketches, improving data-reduction efficiency in storage systems. Discover how this technique outperforms existing methods, achieving up to 33% better data-reduction ratios across eleven real-world workloads. Gain insights into the challenges of reference search in delta compression and how DeepSketch addresses them through innovative data clustering and training data set processing. Understand the methodology used to evaluate DeepSketch's performance and its overall benefits in minimizing data center management costs.