Mongodb compass filter regex symbols8/8/2023 ![]() ![]() Executing queries against elastic and retrieving matched documents by id from mongo.Defining appropriate autocomplete edgeGram / nGram indexes.Continuously syncing the mongo collection (maybe only the title and id fields) to elastic search.If we strictly do not want to use atlas search, we may consider: Using this solution we can efficiently search for prefixes of words or for any part of the text, if we run mongo on atlas.Ībove options were easy solutions to the problem. The search index can be defined via terraform (if we want to follow infrastructure as code :-)).These search indexes can accomplish a lot more (fuzzy search, compound search, and maybe more).Once the Atlas search index is ready, we can query the mongo collection using an aggregation pipeline like this: maxGrams: The maximum length of characters which will be tokenised.Setting a very low minGrams value (like 1) with nGram tokeniser will result in a huge index, and setting something very high won't be useful enough. If minGrams is 2, then by searching for "c" we wont get any results, we need to have at least 2 characters. minGrams: The minimum length from which tokenisation will start.E.g.: searching by "put", will return entities #1 and #2 nGram: This will behave like a contains search.E.g.: searching by "comp" will return entities #1 and #2, but searching by "puter" wont return anything edgeGram: This will allow prefix searches against tokenised words.Choose the tokeniser for Autocomplete datatype:.String - for complete text matching (also needed for autocomplete match if we want to increase the search score of completely matched strings).Also define two datatypes for the field:.Define explicit fields to index, in this case it can be the title field.Disable dynamic mapping (assuming that we already know which field to index, and the field name / hierarchy doesn't change).This will tokenise the field's value into words We can define a search index on topics following these steps: autocomplete indexing and searching perfectly meets our use case. This is only applicable when mongo is running on atlas.Ītlas provides a very powerful way to search through documents for partial words. Using this solution we can efficiently search for full words or for phrases containing at least one full word. only doc #1 will pass this check, which will be returned as the result of the query among all these documents, mongo will examine the title fields and check whether the exact phrase "computer sci" is present or not.fetch documents containing either "computer" (this will match doc #1) or "sci" (this will match doc #5).tokenise the search text into "computer" and "sci".Enter fullscreen mode Exit fullscreen mode ![]()
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