Hello everyone I reread all the documentation of full-text search and the following question arose:
How to perform an accurate word search using Postgresql ?
For example, I have 100 document titles.
Names:
Document
Document red
The document is green outdated
I want to send a "Document" request and get only the Document, and not see the rest in the search results.
This is possible by means of Postgresql FTS?
I read all the documentation on full-text search and did not see such possibilities and examples
If your concern is just not to build yet another index, you can write a FTS query to use the index, and combine it with a simple AND equality check to rule out the things the index returns but which you don't want:
WHERE doc = 'Document' AND
tsv ## phraseto_tsquery('english','Document')
Related
I'm new in mongoDB and I'm facing an issue about performance that need your help. I have a collection with 400k records, when not create index for any field on the collection it takes 20-30s for each query then I create indexs for fields that usually using for search query, but the problem is, when using $regex to search for a string field with index on it, mongoDB does not use index on that field, mongodb still scan for all records in that collection, I've searched on internet with this keyword: "index on regex fields mongodb" and I found some answers which say that "MongoDB use prefix of RegEx to lookup indexes" which means you have to use "^" prefix for the index to work like "db.users.find({name: /^key word/})", but that is not working for me, does "index on $regex field" need MongoDB Atlas to work? because i'm using comunity version of mongoDB. Thanks!
There's a lot to unpack here. We'll split the answer into two parts, the first to try and answer some of the direct questions about index usage and the second to explore solutions to satisfy the application requirements.
Index Usage with $regex
As is true with an index in any database that captures the full string value as the key, MongoDB can use the index for a $regex operation but its efficiency in doing so greatly depends on the regex being applied. That is what the Index Use documentation from the comments and the other answers you reference are describing.
In the comments you mention that an example query might be db.users.find({name: {$regex: '.*keyword.*', $options: 'i'}}). That means that the regex is a both unanchored and case-insensitive. The aforementioned doumentation states directly:
Case insensitive regular expression queries generally cannot use indexes effectively.
Why is this? because the substring that you are searching for can be found in any string value captured by the index. So the document with matching value {name: 'a keyword'} would be located at one end of the index, {name: 'keyWord' }, may be somewhere in the middle, and {name: 'Z keyword'} may be at the end. The only way to ensure correct results is for the database to scan the index for all string values. So while it is still using the index, it may not be efficient as most of the scanned values will not be match and will be discarded.
You may always use .explain() to better understand how the database is answering the query, such as if and how it is using an index.
Solutions
So what do we do about this?
Well as #rickhg12hs suggests in the comments, it depends on exactly what you are trying to achieve. You reiterate that that you are looking for 'full regex search capability', but that is really an approach/solution rather than a goal. If what you really need, for example, is just to match an exact string in a case insensitive manner, then something as simple as a case insensitive index would likely do the trick.
However if truly do wish to perform arbitrary substring searching, then you are really looking at search engine capabilities. In that situation your best bets would probably be to emulate their indexes directly in MongoDB (e.g. have the application manually tokenize the strings to be indexed), stand up something like Solr/Elasticsearch next to MongoDB, or use MongoDB's Atlas Search offering. The $text operator mentioned in the comment has limitations when it comes to substring searching (such as just part of a word), which may or may not be relevant for your needs.
Currently, I have a MongoDB instance, which contains a collection with a lot of entities. Each entity contains a string attribute, which represents some text. My goal is to provide a strict text search in the collection. It should work as a MySQL query:
SELECT *
FROM texts
WHERE text LIKE '%test%';
MongoDB text index would be great, but it doesn't provide a strict search. How I could organize a strict search for such data? Could I do some optimization?
I already checked other software (such as ElasticSearch, Lucene, MongoDB, ClickHouse), but I haven't found options to do it. Searching as now took too much time.
In mongoDB you can do it as follow:
db.texts.find({ text:/test/ })
Since it is not possible to find "blueberry" by the word "blue" by using a mongodb full text search, I want to help my users to complete the word "blue" to "blueberry". To do so, is it possible to query all the words in a mongodb full text index -> that I can use the words as suggestions i.e. for typeahead.js?
Language stemming in text search uses an algorithm to try to relate words derived from a common base (eg. "running" should match "run"). This is different from the prefix match (eg. "blue" matching "blueberry") that you want to implement for an autocomplete feature.
To most effectively use typeahead.js with MongoDB text search I would suggest focusing on the prefetch support in typeahead:
Create a keywords collection which has the common words (perhaps with usage frequency count) used in your collection. You could create this collection by running a Map/Reduce across the collection you have the text search index on, and keep the word list up to date using a periodic Incremental Map/Reduce as new documents are added.
Have your application generate a JSON document from the keywords collection with the unique keywords (perhaps limited to "popular" keywords based on word frequency to keep the list manageable/relevant).
You can then use the generated keywords JSON for client-side autocomplete with typeahead's prefetch feature:
$('.mysearch .typeahead').typeahead({
name: 'mysearch',
prefetch: '/data/keywords.json'
});
typeahead.js will cache the prefetch JSON data in localStorage for client-side searches. When the search form is submitted, your application can use the server-side MongoDB text search to return the full results in relevance order.
A simple workaround I am doing right now is to break the text into individual chars stored as a text indexed array.
Then when you do the $search query you simply break up the query into chars again.
Please note that this only works for short strings say length smaller than 32 otherwise the indexing building process will take really long thus performance will be down significantly when inserting new records.
You can not query for all the words in the index, but you can of course query the original document's fields. The words in the search index are also not always the full words, but are stemmed anyway. So you probably wouldn't find "blueberry" in the index, but just "blueberri".
Don't know if this might be useful to some new people facing this problem.
Depending on the size of your collection and how much RAM you have available, you can make a search by $regex, by creating the proper index. E.g:
db.collection.find( {query : {$regex: /querywords/}}).sort({'criteria': -1}).limit(limit)
You would need an index as follows:
db.collection.ensureIndex( { "query": 1, "criteria" : -1 } )
This could be really fast if you have enough memory.
Hope this helps.
For those who have not yet started implementing any database architecture and are here for a solution, go for Elasticsearch. Its a json document driven database similar to mongodb structurally. It has "edge-ngram" analyzer which is really really efficient and quick in giving you did you mean for mis-spelled searches. You can also search partially.
Following on from a question relating to count in full text searches. Does anyone have a way to skip records returned from a full text search for pagenation purposes?
Example text search -
db.jobs.runCommand("text", {search: "Australia"});
Regards,
Sean
The text command returns “a document that contains a field results that contains an array of highest scoring document, in descending order by score.” Please see the following link on text command details.
http://docs.mongodb.org/manual/reference/command/text/
Both limit and skip will not apply in this case since the returned document is neither a cursor nor an aggregation operation. You will have to improvise limit and skip operations in your application. There are plans to integrate text search into normal MongoDB query stream. You can follow the ticket and vote for the feature under the More Actions button.
https://jira.mongodb.org/browse/SERVER-9063
In addition, the returned document must be able to fit into 16 MB, the BSON document size. Consider using $project and $limit parameters to limit the size of results.
I have the following query (MongoMapper/Rails):
Card.where(:card_tags => {:$all => search_tags}
Where card_tags is an array of string tags and search_tags is in array of the search strings. At the moment if someone searches 'snow', no results with tag 'snowboarding' will be returned.
How can I modify this query to search whether any strings in card_tags contains any of the strings in search_tags? Regular expressions come to mind but not sure of the syntax given these are arrays...
Thanks
You can use regular expressions but you will be doing full collection scans - this is going to be bad for performance.
You can use regex with an index only if you "starts with" type of searches, but I doubt you want to limit yourself to that.
For fulltext searching, you are better off using some external search service for this - like Lucene, ElasticSearch, or Solr.
Refer to this post too: like query in mongoDB