Commit 37390a7
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feat: Add merge join optimization for multi-term queries with ORDER BY + LIMIT
This commit implements a significant optimization for multi-term full-text search queries when combined with ORDER BY and LIMIT clauses. The optimization uses a merge join algorithm that avoids materializing large intermediate result sets.
Key improvements:
- Index: Add query planning with selectivity estimation for choosing between streaming merge join vs standard intersection
- Index: Implement efficient 2-way and N-way merge join algorithms for DESC ordered queries
- Server: Extend GetTopN optimization to support multi-ngram terms (e.g., CJK characters)
- Server: Add detailed debug info tracking (ORDER BY applied, explicit LIMIT/OFFSET flags)
- CLI: Fix debug output parsing to properly handle \r\n\r\n separators between response and debug sections
- Connection: Add context labels for better logging (e.g., "snapshot builder", "binlog worker")
- Main: Implement graceful snapshot cancellation on SIGINT/SIGTERM signals
- Main: Improve shutdown sequence to destroy resources in reverse initialization order
- Query parser: Track whether LIMIT/OFFSET were explicitly specified by user
- Binlog reader: Improve thread shutdown ordering to prevent use-after-free
Performance impact:
- For highly selective queries (>50% selectivity), merge join provides O(M) performance vs O(M + K*N*log(M)) for binary search approach
- For single-term multi-ngram queries, avoids materializing all results when only top-N needed
- Deep offsets (>10000) still use standard path to avoid inefficiency
This optimization is particularly effective for:
1. CJK (Japanese/Chinese/Korean) text searches with multiple character n-grams
2. Queries with high term correlation (common in natural language)
3. Pagination queries with ORDER BY id DESC LIMIT N1 parent 2aeb75c commit 37390a7
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