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GeezerVison is showing github.com — refactor: hnswlib performance by JoanFM · Pull Request #1727 · docarray/docarray
This repository was archived by the owner on Sep 9, 2026. It is now read-only.
ConversationSigned-off-by: Joan Fontanals Martinez <[email protected]> …ctor-hnswlib-performance
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Codecov ReportPatch coverage:
Additional details and impacted files@@ Coverage Diff @@ ## main #1727 +/- ## ========================================== - Coverage 84.46% 84.45% -0.01% ========================================== Files 134 134 Lines 8798 8834 +36 ========================================== + Hits 7431 7461 +30 - Misses 1367 1373 +6
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Signed-off-by: Joan Fontanals Martinez <[email protected]>
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Signed-off-by: Joan Fontanals Martinez <[email protected]>
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📝 Docs are deployed on https://ft-refactor-hnswlib-performance--jina-docs.netlify.app 🎉 |
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| rows = self._execute_filter(filter_query=filter_query, limit=limit) | ||
| return DocList[self.out_schema](self._doc_from_bytes(blob) for _, blob in rows) # type: ignore[name-defined] | ||
| hashed_ids = [doc_id for doc_id, _ in rows] | ||
| embeddings: OrderedDict[str, list] = OrderedDict() |
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Why specifically OrderedDict? I think normal dict in python will already be ordered by default
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I would still like to be specific about the requirement for order
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do we have any measure on how much faster hnsw works now?
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| self._hnsw_indices[col_name] = self._create_index(col_name, col) | ||
| self._logger.info(f'Created a new index for column `{col_name}`') | ||
| if self._hnsw_indices[col_name].space == 'cosine': | ||
| cosine_metric_index_exist = True |
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why do we care about this?
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Because for cosine, HNSWLib normalizes the vectors, and then if we retrieve, they have chanded, so no consistent API can be provided
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We have observed around 10% improvement |
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