But, now the issue is, the elasticsearch is going through all the documents to fetch the list of unique values present in that index (confirmed by evaluating the response below). I got the list of unique values for my field. Somehow, I got the doc_values enabled and I’m trying to do term aggregation to solve same business problem. My business problem is “get all the distinct values/terms of a field (type: keyword)”.Īs you suggested, I can do with elasticsearch terms aggregation only when the field has doc_values enabled. Thanks for your quick reply Alessandro Benedetti. – You don’t need Indexing time boosting per field – You don’t need to boost short field contents The norms data structure will not be built – You want to use the Posting Highlighter.Ī fast version of highlighting that uses the posting list instead of the term vector. The posting list for each term will contain the term offsets in addition. – You do need to search in your corpus with phrase or positional queries. The posting list for each term will contain the term positions in addition.Ġ : 1 :, 1 : 2 :, 2 : 1 : Login to the Lucene.NET build pipeline on Azure DevOps Click the Run pipeline button Ensure the master branch is selected Expand Variables Update the PackageVersion variable to the release version number (i.e. – You do need scoring to take Term Frequencies in consideration The posting list for each term will simply contain the document Ids ( ordinal) and term frequency in the document. You don’t need score to be affected by the number of occurrences of a term in a document field. Thus, your class should only reference the input via the protected 'input' field of Tokenizer. – You don’t need to search in your corpus with phrase or positional queries. (A future release of Apache Lucene.NET will remove the reader parameters from the Tokenizer constructors.) Tokenizer wraps the text reader in an object that helps enforce that applications comply with the analysis workflow. The posting list for each term will simply contain the document Ids ( ordinal) and nothing else. You don’t need to search in your corpus of documents.
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