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Current state: ["Approved"]

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IPL2HAMMINGJACCARDTANIMOTOSUBSTRUCTURESUPERSTRUCTURE
BIN_IDMAP

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BIN_IVF_FLAT

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IDMAP
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IVF_FLAT
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IVF_PQ
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IVF_SQ8
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HNSW
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ANNOY






DISKANN
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If call range search API with unsupported index types or unsupported metric types, exception will be thrown out.

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This API returns all unsorted results with distance falling in the specified range scope.

PROTO
virtual DatasetPtr
QueryByRange(const DatasetPtr& dataset, const Config& config, const faiss::BitsetView bitset)

INPUT

Dataset {
    knowhere::meta::TENSOR: -   // query data
    knowhere::meta::ROWS: -      // rows of queries
    knowhere::meta::DIM: -          // dimension
}

Config {

    knowhere::meta::RADIUS: -   

    knowhere::meta::RANGE_FILTER: -   

}

OUTPUT

Dataset {
    knowhere::meta::IDS: -                // result IDs with length LIMS[nq]
    knowhere::meta::DISTANCE: -  // result DISTANCES with length LIMS[nq]
    knowhere::meta::LIMS: -            // result offset prefix sum with length nq + 1
}

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This API does range search for no-index dataset, it returns all unsorted results with distance "better than radius" (for IP: > radius; for others: < radius).

PROTO
static DatasetPtr
RangeSearch(const DatasetPtr base_dataset,
            const DatasetPtr query_dataset,
            const Config& config,
            const faiss::BitsetView bitset);

INPUT

Dataset {
    knowhere::meta::TENSOR: -   // base data
    knowhere::meta::ROWS: -      // rows of base data
    knowhere::meta::DIM: -          // dimension
}

Dataset {
    knowhere::meta::TENSOR: -   // query data
    knowhere::meta::ROWS: -      // rows of queries
    knowhere::meta::DIM: -          // dimension
}

Config {

    knowhere::meta::RADIUS: -   

    knowhere::meta::RANGE_FILTER: -   

}

OUTPUT

Dataset {
    knowhere::meta::IDS: -                // result IDs with length LIMS[nq]
    knowhere::meta::DISTANCE: -  // result DISTANCES with length LIMS[nq]
    knowhere::meta::LIMS: -            // result offset prefix sum with length nq + 1
}

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  1. pass radius parameters (radius _low_bound / radiusrange_high_boundfilter) to knowhere 
  2. get all unsorted range search result from knowhere
  3. for each NQ's results, do heap-sort
  4. return result Dataset with TOPK results

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If user wants to get more than 16384 range search results, they can call range search multiple times with different radius range_filter parameter (use L2 as an example)

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