SOLR-15880: K Nearest Neighbors Search #476
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- indexing knn vector field - custom query parser for knn vector search
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solr/core/src/java/org/apache/solr/schema/DenseVectorField.java
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The Pull Request is now complete and ready for review. |
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This is great! Very excited to see this getting in to Solr. My main comments are about the de/serialization format. I wonder also if you have a plan for providing access to the index-time hyperparameters, like graph fanout (maxConns) etc. It is pretty important, for best performance, to be able to optimize these for a particular set of vectors embeddings.
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| private IndexableField createStoredField(SchemaField field, Object value) { | ||
| return new StoredField(field.getName(), value.toString()); |
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This doesn't seem like something very useful for numeric vector fields? You'd end up with strings like [0.3485723998437523,...] which would be a very inefficient way to store the information
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| public void write(TextResponseWriter writer, String name, IndexableField f) throws IOException { | ||
| writer.writeVal(name, f.stringValue()); |
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Not sure what stringValue will return here - will it be the Arrays.toString() of the vector? Something else?
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| /** | ||
| * Parses a String vector. | ||
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| * @param value with format: [f1, f2, f3, f4...fn] |
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Have you considered an alternate more compressed string format? Maybe b64-encode the bytes of the float array?
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thanks @msokolov for your initial feedback! |
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I should have addressed most of the comments regarding the documentation. Only a few questions remain, that I don't think are really critical, so I'll wait for some reply on them before committing. In regards to the "Neural Search" name, as I expressed in a comment before, I think it's fine, but I'll raise the matter to the wider community through slack for a quick feedback! Cheers and thanks again! |
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I refactored the documentation contribution, changing the name of the section to "Dense Vector Search". If no blockers, I'll proceed tomorrow with the merge! |
This contribution introduces dense vector indexing and searching
This contribution introduces dense vector indexing and searching
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Hi guys, thanks for working on this feature! I would like to index vectors with a dimension > 1024 (embeddings come from a ResNet), do you know how this would be possible 🤔 Many thanks in advance ❤️ |
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We put in a limit of 1024 since we need some limit in order to help people not to shoot themselves in the foot and then blame the software... What dimension in fact are your vectors? Maybe consider adding some dimensionality reduction step? Sorry I don't know what a ResNet is :) |
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I'm currently using 2048, but I can use a smaller model that outputs 1024 :) |
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@msokolov : larger embeddings are definitely useful. Oxford's "VGG-Face" outputs a vector of 2622 elements. Support for larger embeddings would enable Solr features like "boost the results of word docs containing an image with a similar face to George Washington" using such models . |
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Trying to query for topK greater than 10 but cannot get more than 10 documents in response. This is from the film examples in solr docs, the query works fine on the UI with Is there something in the documentation regarding this? |
https://issues.apache.org/jira/browse/SOLR-15880
Description
This is the first milestone in integrating neural search in Apache Solr.
We are reviewing the Pull Request internally and finishing the documentation.
Other than that, the code is ready for review.
It includes a DenseVectorField to wrap the Lucene implementation using Hierarchical Navigable Small World to index the dense vector.
It includes a Knn query parser to run K Nearest Neighbors query.
Solution
A new Apache Solr field Type has been added.
A new Apache Solr Query Parser has been added.
Tests
Dense vector fields and the query parser have tests.
Checklist
Please review the following and check all that apply:
mainbranch../gradlew check.