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Current state: ["Under DiscussionApproved"]

ISSUE: #17599

PRs: 

Keywords: search, range search, radius, low bound, high boundrange filter

Released: 

Summary(required)

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This MEP is about to realize a functionality named "range search". User specifies a range scope -- including radius low bound and radius high boundand range filter (optional), Milvus does "range search", and also returns TOPK sorted results with distance falling in this range scope.

• both radius low bound and radius high bound param "radius" MUST be set, param "range filter" is optional
• falling in range scope means

MotivationMotivation(required)

Many users request the "range search" functionality. With this capability, user can

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We reuse the SDK interface Search() to do "range search". Only add 2 more parameters "radius_low_bound" and "radiusrange_high_boundfilter" into params.

When When param "radius_low_bound" and "radius_high_bound" are " is specified, Milvus does range search; otherwise, Milvus does search.

As shown in the following figure, set "radiusrange_low_boundfilter": 1.0, "radius_high_bound": 2.0 in search_ params.params.

  default_index = {"index_type": "HNSW", "params":{"M": 48, "efConstruction": 500}, "metric_type": "L2"}
  collection.create_index("float_vector", default_index)
  collection.load()  
  search_params = {"metric_type": "L2", "params": {"ef": 32, "radiusrange_low_boundfilter": 1.0, "radius_high_bound": 2.0}}
  res = collection.search(vectors[:nq], "float_vector", search_params, limit, "int64 >= 0")

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In Knowhere, two new parameters "radius_low_bound" and "radiusrange_high_boundfilter" are passed in via config, and range search will return all un-sorted results with distance falling in this range scope.

Knowhere run range search in 2 steps:

1. pass param "radius" to thirdparty to call their range search APIs, and get result
2. if param "range_filter " is set, filter above result and return; if not, return above result directly

We add 3 new APIs CheckRangeSearch(), QueryByRange() and BruteForce::RangeSearch() to support range search.

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

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

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Segcore uses radius parameter's existence to decide whether to run search, or to run range search.to run search, or to run range search.

• when param "radius
• when both "radius_low_bound" and "radius_high_bound" are set, range search is called; 
• when only one of "radius_low_bound" and "radius_high_bound" is set, exception range search is thrown outcalled; 
• otherwise, search is called. 

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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 parameter (use L2 as an example)

• NQ = 1

1st call with (radiusrange_low_bound filter = 0.0, radius _high_bound = inf), get result distances like this:

{d(0), d(1), d(2), ..., d(n-1)}

2nd call with (radiusrange_low_bound filter = d(n-1), radius _high_bound = inf), get result distances like this:

{d(n), d(n+1), d(n+2), ..., d(2n-1)}

3rd call with (radiusrange_low_bound filter = d(2n-1), radius _high_bound = inf), get result distances like this:

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• NQ > 1 (suppose NQ = 2)

1st call with (radiusrange_low_bound filter = 0.0, radius _high_bound = inf), get result distances like this: 

{d(0,0), d(0,1), d(0,2), ..., d(0,n-1), d(1,0), d(1,1), d(1,2), ..., d(1,n-1)}

2nd call with (radiusrange_low_bound filter = min{d(0,n-1), d(1,n-1)}, radius _high_bound = inf), get result distances like this: 

{d(0,n), d(0,n+1), d(0,n+2), ..., d(0,2n-1), d(1,n), d(1,n+1), d(1,n+2), ..., d(1,2n-1)}

3rd call with (radiusrange_low_bound filter = min{d(0,2n-1), d(1,2n-1)}, radius _high_bound = inf), get result distances like this:

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1. test/milvus/ann_hdf5/binary/sift-4096-hamming-range.hdf5
   1. base dataset and query dataset are identical with sift1m
   2. radius _low_bound = 0.0, radius_high_bound = 291.0
   3. result length for each nq is different
   4. total result num 1,063,078
2. test/milvus/ann_hdf5/sift-128-euclidean-range.hdf5
   1. base dataset and query dataset are identical with sift1m
   2. radius_low_bound = 0.0, radius_high_bound = radius = 186.0 * 186.0
   3. result length for each nq is different
   4. total result num 1,054,377
3. test/milvus/ann_hdf5/sift-128-euclidean-range-multi.hdf5
   1. base dataset and query dataset are identical with sift1m
   2. ground truth IDs and Distances are identical with sift1m
   3. each nq's radius _low_bound is 0.0, radius_high_bound is set to the last ground truth distance
   4. result length for each nq is 100
   5. total result num 1,000,000
4. test/milvus/ann_hdf5/glove-200-angular-range.hdf5
   1. base dataset and query dataset are identical with glove200
   2. radius _low_bound = 0.52, radius_high_bound = 1.01
   3. result length for each nq is different
   4. total result num 1,060,888

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1. use sift1M/glove200 dataset to test range search (radius _low_bound = = max_float / -1.0, radius_high_bound = max_float), we expect to get identical results as search

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