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Performance

By selecting the appropriate index type, typical search times can be kept within a few milliseconds. The performance of staticseek is influenced by various factors, including the size of the dataset, the complexity of the queries, and the chosen indexing strategy.

The following benchmarks illustrate the performance of different index types under worst-case scenarios, with approximately 100 articles:

  • LinearIndex: < 5ms
  • GPULinearIndex: < 5ms
  • HybridTrieBigramInvertedIndex: < 1ms
  • LinearIndex: < 150ms
  • GPULinearIndex: < 25ms
  • HybridTrieBigramInvertedIndex: < 2ms
  • LinearIndex: ~1sec
  • GPULinearIndex: ~1sec
  • HybridTrieBigramInvertedIndex: ~2sec
  • LinearIndex: 1.3MB
  • GPULinearIndex: 1.3MB
  • HybridTrieBigramInvertedIndex: 0.5MB

Recommendations for Optimizing Performance

Section titled “Recommendations for Optimizing Performance”
  1. Choose the Right Index Type: For smaller datasets, LinearIndex may be sufficient. For larger datasets or applications requiring fuzzy search, consider GPULinearIndex or HybridTrieBigramInvertedIndex.
  2. Pre-generate Indices: Generate indices during the build process to optimize search performance at runtime.

For detailed benchmarks across different hardware configurations and index types, see the Benchmarks section.