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Small index file, Elasticlunr.js did not store TokenCorpus because there is no need to compute query vector and document vector, then the index file is very small, this is especially helpful when elasticlunr.js is used as offline search. Fast, Elasticlunr.js removed TokenCorpus and Vector from lunr.js, by using combined model there is need to compute the vector of a document to compute the score of a document, this improve the search speed significantly. And have in mind that we only keep json values.
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JsonTest WITH (INDEX (IXJsonTestParameter1),INDEX (IXJsonTestParameter2)) WHERE Parameter1 1 and Parameter2 2 This approach queries a table with 2m records in less than 1 second. Combined Boolean Model, TF/IDF Model and the Vector Space Model, make the results ranking more reliable. And now finally you can query your table very fast: SELECT Json, Parameter1, Parameter2 FROM dbo. Boolean Model, you could set which field to search and the boolean model for each query token, such as "OR", "AND". Field-search, you could choose which field to index and which field to search. More rational scoring mechanism, Elasticlunr.js use quite the same scoring mechanism as Elasticsearch, and also this scoring mechanism is used by lucene. Query-Time boosting, you don't need to setup boosting weight in index building procedure, this make it more flexible that you could try different boosting scheme. "body": "As expected, Oracle released its profit report of 2015, during the good sales of database and hardware, Oracle's profit of 2015 reached 12.5 Billion."Īlso, you could do query-time boosting by passing in a configuration:Įlasticlunr.js is developed based on lunr.js, but more flexible than lunr.js. "title": "Oracle released its profit report of 2015", "body": "Yestaday Oracle has released its new database Oracle 12g, this would make more money for this company and lead to a nice profit report of annual year." Certain parameters are required to initiate a. For example, using JavaScript you could store. "title": "Oracle released its latest database Oracle 12g", json (recommended) indicates output in JavaScript Object Notation (JSON) xml indicates output as XML. What is ‘full text search’ For a small amount of simple textual data it’s possible to provide basic search functionality via simple string matching. Open your browser's developer tools on this page to follow along or you could use Node.js to try in different way.Ī very simple search index can be created using the following scripts:Īdding documents to the index is as simple as: