A research platform combining Lucene, distributed join execution, Bloom-filter optimized probing, and hierarchical query planning - built for real-time, relationship-aware search.
SearchHound is an experimental Lucentrix-native engine designed for real-time distributed JOIN execution over Lucene indexes. It introduces a hierarchical coordination model, Bloom-filter optimized hashing, adaptive join strategies, and hybrid RDBMS + Lucene indexing for high-speed relational lookups.
This page documents the core architecture and distributed join protocol used by SearchHound. The system uses a hierarchical tree of SearchCoordinators and SearchLeaf nodes. Join planning is cost-based; build-side nodes generate Bloom filters which are merged and distributed to probe nodes to prune non-matching keys and drastically reduce network transfer.
SearchHound introduces a novel Bloom-filter optimized join mechanism that reduces network transfer by 60–90% in typical join scenarios. Join planning is adaptive and depends on cardinality, selectivity, and cluster topology.
Join Execution Flow:
1. Query → Root Node
2. Extract join keys
3. Build Bloom filters
4. Distribute filters to probe nodes
5. Local Lucene + RDBMS join
6. Aggregate results upward
Main coordination layer with adaptive join selection.
Leaf Lucene node with RDBMS join index and Bloom probing.
Aggregation node orchestrating the join pipeline.
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