Atlas Search
112 results found
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Faster Sorting with Atlas Search
I am looking to achieve a faster sort when using Atlas Search.
Please comment if you tried Stored Source Fields and it did not meet the performance you were looking for.
Stored Source Fields Docs:
Index - https://www.mongodb.com/docs/atlas/atlas-search/stored-source-definition/
Query - https://www.mongodb.com/docs/atlas/atlas-search/return-stored-source/38 votesThis work has begun. Please fill out this form to help us ensure we are addressing your use case.
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Multiple Capture Groups in RegEx Tokenizer
Currently the RegEx tokenizer only supports to either create a token from each match or for one capture group per match. This makes it impossible to reuse parts of the text for multiple tokens, for example when you want to tokenize "13.3" into "13" as well as "13.3" (our use case is searching products where we want to find a 13.3" device by searching for 13" as well as 13.3").
1 vote -
Ability to exclude documents matching a certain criteria from index
We don't do physical deletion of documents, but a logical one, flagging them by setting a value for a
deleted_atfield.We would like an option to exclude documents where that field exists and is not null from the index, because they will never be returned and are only consuming space of the index.
Currently we use a
mustNotcondition to exclude them, but of course they are still being indexed.The ideal would be to be able to define the exclusion criteria in the index definition.
1 vote -
$bucketAuto for number facets
As a developer, I would like to have functionality for NumberFacets similar to the $bucketAuto operator, so that I can define the number of buckets I want instead of setting the boundaries myself.
This function is helpful in situations where you don't know the boundaries or can't calculate them easily.
Example:
myNumberFacet: {
type: 'number'
path: 'path.to.my.field'
buckets: 1000
}7 votes -
Dedicated search nodes
Currently, Atlas Search (mongot) is collocated with Atlas (mongod) on the same database deployment. Today, I have to size their workload based on both search and database requirements, which introduces the possibility of resource contention between their database and search deployment. I'd like to scale my search deployment independently of my database deployment.
2 votes -
add a setting to ignore the corpus term frequency for score calculation
indexOption:docs omits per document frequencies, but it still uses the corpus frequency.
it would be good to have a setting to ignore the corpus frequency as well
2 votes -
.NET Driver
It would be great if the .NET driver would support $search along with all the associated operators.
1 vote -
Allow faceting on boolean fields
Right now you can only facet on string, number, date fields.
https://www.mongodb.com/docs/atlas/atlas-search/facet/#facet-definitionI would like to also be able to facet on boolean fields.
1 vote -
Duplicate search index
I want to be able to easily duplicate a search index in the Atlas UI.
1 vote -
Allow retrieval of individual score from embedded document search
When using the emeddedDocuments operator to search you get a score per document, but not per embedded document. The aggregated score is either min/max/sum/mean but what I really need is the individual score from the embedded documents in order to further filter out the best matches.
1 vote -
Grouping in $search
Add grouping capability to search so that it can be as performant as the search itself.
A separate group stage is not performant at all and is unusable.
1 vote -
Filtered Indexes
Provide capability to create filtered indexes. This would allow creating tenant-specific indexes in a multi-tenant database.
While the current implementation does support this feature in a way, it requires manual maintenance of such indexes as there is an implicit assumption that each tenant would have the same fields.
Our core requirement is that each tenant can have their own set of fields. Filtered indexes would help reduce the size, hence requiring fewer system resources and possibly helping the database perform better.
1 vote -
Hiearchical/Multi-Level filters/facets.
As a user, I'd like to be able to compute faceted counts on multi-levels of categorization.
7 votes -
Atlas full text search should support searching all field types
Atlas full text search should support searching all fields types including text, dates, numbers and booleans.
Atlas full text search at present supports searching in text values only. e.g. Searching for "2022" will not pick up documents that contain 2022 in the number fields.
The functionality in it's current form does not have any way of searching for a given string value (which can be numeric, boolean or part of a date).
1 vote -
Support full Lucene Query Parser syntax in $search
I’m looking to expose “power user” queries through our UI, but the queryString operator only works on string data types, and is somewhat too simplistic for this purpose.
Obviously, accepting raw user inputs and directly building a query from it is a security risk, but using something like queryString (which I do currently) seems like a safer and/or easier option.
I would like to see a new $search operator (perhaps "lucene" or "query") that accepts the full Lucene Query Parser Syntax.
5 votes -
Support for OR Conditions
We need support for matching for one condition out of several. This is an important usecase for my requirements.
e.g. $or: [{ "airlines": "United" }, { "ticket_price": { $lte: 600.00 } }]
Thanks!
1 vote -
Provide features for array comparisons
It would be very helpful if we can lookup documents that have certain array fields that match the provided array in the query. Exact match, Any match etc should be supported. All data types should be supported.
e.g { text: { path: "city", query: ["New York", "Los Angeles", "Kansas"] } } should return all documents that have the city as ["New York", "Los Angeles", "Kansas"].
1 vote -
Atlas Search vs find/match
Atlas Search is currently quite rigid and is not as awesome as find/match.
find/match supports a variety of operators that allow looking up documents in numerous ways and is meeting our requirements to be able to query using filters such as:
in, nin, eq, neq, gte, lte, all, any, gt, lt, size
These operators work with find/match for any and all data types including arrays. With arrays, find/match even does an exact match comparison which is one of our requirements.It would be great if we can combine the speed of Atlas Search with find/match features
1 vote -
Add storedSource parameter to atlas admin API search index create/update to use with terraform
Right now it is impossible to create atlas search index via terraform with "storedSource" parameter. This brings a lot of inconvenience and configuration-related bugs.
Related issue
https://github.com/mongodb/terraform-provider-mongodbatlas/issues/871
2 votes -
Allow faceting for embeddedDocuments
At the moment embeddedDocuments does not allow number or date faceting.
In my opinion, this does not make the operator useful, since Faceting is now the standard for every search.
2 votes
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