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In this case, it loads data into a separate internal index, and transforms the user’s input into a term query. However, under the hood, it applies the EdgeNGramTokenFilter filter to suggestions to give multiterm unordered suggestions.
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Lookup implementation is varied and the following features can be compared: Data can then be loaded from a source into a lookup-ready data structure automatically upon startup/reload (buildOnStartup parameter). A collection of weighted suggestions can be taken from the index, or from an alternate data source such as a file stored on a disk. To make this component work, two things need to be configured in the search engine’s config: the data source for suggestions (dictionaryImpl parameter), and how these suggestions are stored and searched in query-time (lookupImpl parameter). Suggester is a search component, which is a building block of Solr’s search pipeline. So, let’s take a more detailed look at Solr suggester and how it can be utilized. The most common questions that we received on that post centered around the need to separate indexes and queries, as well as if there was a built-in dedicated Solr suggester that can manage all aspects of these two tasks.
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