Two things:
- There is no direct equivalent to
LIKEin Lucene/Elasticsearch, or at least not one that performs well enough to be considered. Lucene/Elasticsearch are about full-text search, so they take a different, more sensible approach: you don’t match “substrings”, you match “tokens” (words). There’s a decent introduction to full-text search in Hibernate Search 6’s documentation: Hibernate Search 6.0.11.Final: Reference Documentation Hibernate Search 6 is still in beta and APIs are vastly different but the concept is the same. - A single filter will not address all your problems. The idea is to find the right tokenizer/filter for each problem, and to combine them.
So, about the filter…
- To make the query “nike” match the indexed text “nike 1234”, use a tokenizer. The
whitespacetokenizer will tokenize on spaces only, thestandardtokenizer will have more advanced behavior that tokenizes on punctuation, which may be what you’re looking for. - To make the query “Nike” match the indexed text “nike” (i.e. to get case insensitivity), use the
lowercasefilter. - To make the query “1234” match the indexed text “12345” (match the beginning of words), use an
edge-ngram. Notngram, edge-ngram. Check out the javadoc, they are different. - To make the query “1234” match “1243” or “4123”, use an
ngram. It’s really about matching parts of tokens instead of the whole token, but it’s not exactly the same asLIKEin SQL. The query “nike 1234” with a min gram size of 2 and a max gram size of 3 will match “ni 123”, for example. You will have to rely on scoring (sort hits by relevance), which is enabled by default, to get the best matches first. - To handle Japanese/Chinese, I suppose you’ll have to rely on the ICU tokenizer and CJK filter, but frankly I don’t have a clue how these work (I’ve never had to work with Japanese/Chinese).