Comments (3)
jelmerk
commented on May 21, 2024
you are trying to find the best 50k results for each item in the set ? that would be a huge data set. I can speculate about the problem but thats not something thats going to be easy to reproduce. And a bit of a unusual scenario
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ccalvin97
commented on May 21, 2024
Does this model have the limitation of K? I found that when I set k=50,000. It still output empty dataframe
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jelmerk
commented on May 21, 2024
no it should never give an empty dataframe
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Related Issues (20)
- mvn test hnsw-spark NormalizerSpec java.lang.NoClassDefFoundError: org/apache/spark/ml/param/shared/HasInputCol HOT 4
- Not able to load persisted index HOT 6
- excludeSelf parameter in hnswlib class not working HOT 5
- Repeatability HOT 1
- Why is there no float-64 support in hnswlib-core-jdk17 HOT 1
- Small number of queries succeeds, whereas larger number fails HOT 4
- benchmark / performance HOT 1
- PySpark OOM advice HOT 12
- Unable to update index HOT 4
- Unable to load the HnswSimilarity model HOT 1
- scala 2.12 port running very slowly HOT 7
- Error: Cannot up cast `partition` from bigint to int. HOT 1
- Brute Force vs hnsw Problem HOT 3
- Load does not work HOT 1
- not all index partitions are persisted (data loss) on k8s HOT 28
- cannot calculate resize correctly leading to SizeLimitExceededException HOT 2
- support for num_threads parameter while building the index HOT 1
- Question about maxLevel
- Performance much worse than hnswlib HOT 5
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