![]() ![]() (Both are enabled by default.) Migration to Roaring Bitmaps You can configure the new indexFilterable and indexSearchable parameters to determine whether to create the roaring set index and the BM25-suitable Map index, respectively. The exit conditions for the search are the same as for an unfiltered search: The search will stop when the desired limit is reached and additional candidates no longer improve the result quality.Ī roaring bitmap index for text properties is available from 1.19 and up, and it is implemented using two separate ( filterable & searchable) indexes, which replaces the existing single index. The index will move along any node's edges normally, but will only add ids to the result set that are present on the allow list. A vector search is performed where the allow-list is passed to the HNSW index.This list is essentially a list of uint64 ids, so it can grow very large without sacrificing efficiency. An inverted index (similar to a traditional search engine) is used to create an allow-list of eligible candidates.Most notably, each shard contains an inverted index right next to the HNSW index. In the section about Storage, we have described in detail which parts make up a shard in Weaviate. Efficient Pre-Filtered Searches in Weaviate We do not make this distinction, as Weaviate does not have to resort to brute-force searches, even when pre-filtering due to the its combined inverted index and HNSW index. Some authors make a distinction between "pre-filtering" and "single-stage filtering" where the former implies a brute-force search and the latter does not. The vector search then only considers candidates that are present on the "allow" list. Pre-Filtering describes an approach where eligible candidates are determined before a vector search is started. The limitations of post-filtering are overcome by pre-filtering. it matches only a small percentage of data points relative to the size of the data set, there is a chance that the original vector search does not contain any match at all. If the filter is very restrictive, i.e.You cannot easily predict how many elements will be contained in the search, as the filter is applied to an already reduced list of candidates.This is an approach where a vector search is performed first and then some results are removed which do not match the filter. Systems that cannot make use of pre-filtering typically have to make use of post-filtering. Additionally, the process is efficient and has minimal overhead compared to an unfiltered vector search. Thanks to Weaviate's efficient pre-filtering mechanism, you can keep the recall high - even when filters are very restrictive. ![]() Weaviate provides powerful filtered vector search capabilities, meaning that you can eliminate candidates in your "fuzzy" vector search based on individual properties.
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