Comments (3)
Some rough ideas on how to implement this:
Keep the same L2Lsh Mapping structure. This seems to be strictly a query-time optimization.
Add a parameter probes: Int
to the L2Lsh query structure, controlling how many additional hashes of length k
(k is called M in the original paper..) are generated for each of the L
tables.
Hashing function will generate the additional probes
hashes right after it generates the standard hash.
Roughly:
for l in range(L):
generate the original hash and do some bookkeeping for below..
for p in range(probes):
generate additional hash
Otherwise the query looks exactly the same. It takes the generated hashes and goes on to look them up the same as any other approx. query.
Implement the naive version first (enumerate, score, sort all possible perturbations). Make sure that you can get equivalent recall on SIFT with fewer tables and ideally but not necessarily shorter query time. Then go back and implement the optimized version which precomputes perturbation sets, estimates the scores, etc. Make sure the optimized matches the naive.
from elastiknn.
Implemented the naive version in #123.
As far I can tell, the naivety is not a bottleneck in the current benchmarking configuration (k = 2, probes = 3
).
In this configuration the overwhelming bottleneck is (understandably) still the countMatches
method.
The only thing I could find related to the multiprobe implementation was taking 0.1% of the runtime on search threads.
Even with k = 3, probes = 27
, any footprint from the hashWithProbes
method is minimal compared to countMatches
.
So for now there are likely more worthwhile things to implement than the optimized version.
from elastiknn.
🎆 🥳 🎈
Implemented Algorithm 1 from Qin et. al. in #124. This generates the perturbation sets iteratively instead of generating them exhaustively and sorting all of them. I'd say this is good enough or now. There doesn't seem to be a need to implement the expected scores optimization from section 4.5, and it's also not obvious to me why/how it works.
from elastiknn.
Related Issues (20)
- Try vectors from Project Panama for LSH operations HOT 3
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- Q&A: Scale effects HOT 2
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- Hope to support version 7.17.20, later 7.17.x can be downloaded HOT 1
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