55 results found

1. Allow $count and $sort inside $search

   Make $count and $sort directly with mongot, and dont lose time between mongot and mongodb.

   118 votes

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   22 comments  ·  Delete…  ·  Admin →
   completed  ·  Elle responded

   At MongoDB World last week, we announced that faster counts are now available with sharded collections. 

   
   

   We also announced a feature called Stored Source Fields which help you achieve faster post-aggregation performance. You can use this feature to experience faster sorting with Atlas Search. 

   
   

   You can read more about these two features here.

   
   

   After trying Stored Source Fields, if it does not meet your performance requirements - please vote on this new feedback item. 

2. Faster Pagination

   I would like be able to paginate through search results faster.

   96 votes

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   10 comments  ·  Delete…  ·  Admin →
   completed  ·  AdminAmy (Admin, MongoDB) responded

   Performant sequential pagination in Atlas Search is now available on MongoDB clusters 6.0.13+ and 7.0.5+ to power Infinite Scroll, Load More, and Next/Previous Page application experiences. To specify where in your Atlas Search results to start returning results from, 1) generate Base64-encoded tokens for each document within your results using the new $meta keyword searchSequenceToken, and 2) use that token as a point of reference with the new searchBefore and searchAfter options within the $search stage. 

   
   

   For use cases not addressed by Sequential Pagination, please vote here.

3. Perform a search over multiple collections

   Right now you can only search over one collection. I'd like to be able to search over several collections at the same time.

   54 votes

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   2 comments  ·  Delete…  ·  Admin →
   completed  ·  Elle responded

   Leverage $unionWith and $lookup to run search queries against multiple collections or create a materialized view prior to indexing. View tutorials here. 

4. Add support for UUID datatypes in Atlas Search

   Currently, UUID is not one of the supported datatypes for Atlas Search. This is a feature request to add support for UUID datatypes in Atlas Search.

   52 votes

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   7 comments  ·  Delete…  ·  Admin →
   completed  ·  AdminAmy (Admin, MongoDB) responded

   This work is now complete. Update your search index to: 

   1. Index fields using the uuid field mapping type 

   2. Query using the equals or in operators

   3. You can also sort on UUID fields

5. The equals operator should support numeric datatypes

   Currently, for querying on "number" datatypes, we can only use "range" or "near" operators. The "equals" operator supports querying only "boolean" and "objectId" values, and not numeric values.

   If we want to do equality based matching for number datatypes, then we can leverage "range" using "gt" and "lt" to find it. However this might be sub-optimal in some cases (such as when performing equality match on decimals).

   Therefore, this is a feature request for having equals operator support numeric datatypes (in addition to boolean and objectId).

   48 votes

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   5 comments  ·  Delete…  ·  Admin →
   completed  ·  Elle responded

   Documentation can be found here

6. Allow indexing and querying for null datatype in Atlas Search

   The null datatype is not amongst the datatypes that Atlas Search supports at this time. As a result, if the use-case is to perform a text search on some fields and perform an equality/inequality check on other field(s) to see if it is/isn't null, then we need to have a $match stage following the $search stage, which is detrimental to the query performance as documented here. This is an enhancement request to allow indexing and querying for null datatype in Atlas Search, to avoid the above scenario.

   47 votes

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   6 comments  ·  Delete…  ·  Admin →
   completed  ·  AdminAmy (Admin, MongoDB) responded

   This work is now complete. Update your search index to search for null using the Atlas Search equals operator on any field that is statically or dynamically indexed. 

7. 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/

   46 votes

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   12 comments  ·  Delete…  ·  Admin →
   completed  ·  Elle responded

   Sort in Search is now GA -- see changelog here for documentation. 

8. Allow Atlas Search indexes to be restored across clusters

   Currently, when an Atlas backup snapshot from one environment is restored to another environment, it does not transfer or replicate the Atlas Search indexes from the source cluster to the destination cluster. As a result, after the snapshot is restored, the Atlas Search indexes have to be manually created on the collections in the destination cluster.

   This is a request for a functionality that will allow a snapshot-restore from one cluster to another to also replicate the Atlas Search indexes from the source cluster to the destination cluster.

   46 votes

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   2 comments  ·  Delete…  ·  Admin →
   completed  ·  AdminAmy (Admin, MongoDB) responded

   Atlas Search index definitions are now included in Cloud Backup snapshots of M10 or higher clusters. See Atlas Search Changelog.

9. Faster Faceting

   Current faceting solution is not fast enough for search use cases for larger datasets.

   38 votes

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   completed  ·  1 comment  ·  Delete…  ·  Admin →

10. Allow managing Atlas Search index via drivers

    Currently I need to manage my indexes via the Atlas Search API but I would like to manage them using drivers in the same way that I manage all of my other MongoDB indexes.

    34 votes

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    3 comments  ·  Delete…  ·  Admin →
    completed  ·  AdminAmy (Admin, MongoDB) responded

    Support is now available for:

    • NodeJS
    • C#
    • C 
    • C++
    • Java
    • PHP
    • Ruby
    • PyMongo

11. Be able to create Search indexes from Mongo shell

    Right now it seems like I can query indexes from the mongo shell but not create them, unless I am missing something in the docs?

    32 votes

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    4 comments  ·  Delete…  ·  Admin →
    completed  ·  AdminAmy (Admin, MongoDB) responded

    This feature is now available for Atlas M10+ clusters running MongoDB 6.0.8 or later. See July 10, 2023 changelog and documentation to learn more.

12. I need to be able to search for dates and numbers in arrays

    I have sets of results which contain dates and I need to be able to search from within them. For example:

    {
      experience: [
        { name: "Abc", startDate: ISODate("2019-01-01T00:00:00.000Z"), startDate: ISODate("2020-01-01T00:00:00.000Z") },
        { name: "Xyz", startDate: ISODate("2018-01-01T00:00:00.000Z"), startDate: ISODate("2019-01-01T00:00:00.000Z") }
      ]
    }
    

    So I need to be able to do a near search across experience.startDate values, for example.

    The Date mapping documentation (https://docs.atlas.mongodb.com/reference/atlas-search/index-definitions/#date) says:

    A date cannot be indexed if it is part of an array.

    And while the number documentation doesn't mention the same restriction by experimentation I have found it has the same resriction (strings dont however). Essentially this feature request is to remove this restriction for dates and numbers.

    I have sets of results which contain dates and I need to be able to search from within them. For example:

    {
      experience: [
        { name: "Abc", startDate: ISODate("2019-01-01T00:00:00.000Z"), startDate: ISODate("2020-01-01T00:00:00.000Z") },
        { name: "Xyz", startDate: ISODate("2018-01-01T00:00:00.000Z"), startDate: ISODate("2019-01-01T00:00:00.000Z") }
      ]
    }
    

    So I need to be able to do a near search across experience.startDate values, for example.

    The Date mapping documentation (https://docs.atlas.mongodb.com/reference/atlas-search/index-definitions/#date) says:

    A date cannot be indexed if it is part of an array.

    And while the number documentation doesn't mention the same restriction by experimentation I have found it has the same resriction (strings dont… more

    25 votes

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    3 comments  ·  Delete…  ·  Admin →
    completed  ·  Elle responded

    Complete, view changelog for more information

13. Allow autocomplete to work with special characters and Asia languages

    Hello,

    We are now using Atlas Search, with a deep dive in this feature, we found out that it will be very cool to support "special characters" (such as @,-) and "Asia languages (such as Chinese)" for autocomplete. I think this is a requirement for many world wide companies. We can't allow a search engine which only cover a part of our clients because our business is with people form the whole world.

    Thank you in advance,

    21 votes

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    2 comments  ·  Delete…  ·  Admin →
    completed  ·  Marcus Eagan responded

    This project was completed recently and you can read about it here: https://docs.atlas.mongodb.com/reference/atlas-search/autocomplete/

    Not only did we add support for most languages that we support, but we also introduced reverseEdgeGram to support languages like Kurdish and Urdu. Please don’t hesitate to reach out if you have any questions.

14. Allow autocomplete search on an array of strings

    Currently, one can't use the autocomplete type to index fields whose value is an array of strings. This is a feature request to allow autocomplete indexing and searching on an array of strings.

    17 votes

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    6 comments  ·  Delete…  ·  Admin →
    completed  ·  Elle responded

    Completed, view changelog for more info

15. Synonym support for search

    I'd like to be able to set synonyms for word in my search index, for example, making a search for "cerulean" redirect to "blue"

    17 votes

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    1 comment  ·  Delete…  ·  Admin →
    completed  ·  Marcus Eagan responded

    We have released synonyms.

    Index docs: https://docs.atlas.mongodb.com/reference/atlas-search/synonyms/

    Query docs: https://docs.atlas.mongodb.com/reference/atlas-search/text/#definition

16. Allow autocomplete to work with email addresses.

    At the moment, an autocomplete index does not tokenize the "@" in email addresses. So when using an autocomplete search on an email address field, the search breaks as soon as the "@" is entered.

    I started a thread in the community about this very issue.

    https://developer.mongodb.com/community/forums/t/mongo-search-autocomplete-type/10561/5

    16 votes

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    1 comment  ·  Delete…  ·  Admin →
    completed  ·  AdminAmy (Admin, MongoDB) responded

    You can achieve this functionality by using setting the autocomplete field mapping's `analyzer` field to lucene.keyword (see example) or a custom analyzer which uses the uaxUrlEmail tokenizer. 

17. 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

    15 votes

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    2 comments  ·  Delete…  ·  Admin →
    completed  ·  AdminZuhair (Admin, MongoDB) responded

    Stored Source Parameter in mongodbatlas_search_index resource and data source has now been released in Terraform. Users will need to upgrade to latest Terraform Atlas provider to be able to use.

    
    

    For more details see here: https://registry.terraform.io/providers/mongodb/mongodbatlas/latest/docs/resources/search_index#stored_source

18. Search Query Analytics

    For Atlas Search, I'd like to see data about what queries are run, and how many results are returned for a given query.

    15 votes

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    3 comments  ·  Delete…  ·  Admin →
    completed  ·  Elle responded

    In public preview, please let us know your feedback! See changelog here.

19. Functionality that provides details of how a score was calculated for an individual document

    Every document returned by an Atlas Search query is assigned a score based on relevance. Many factors can influence a document's score, including the position of the search term in the document, the frequency of occurrence of the search term in the document, the type of operator the query uses, the type of analyzer the query uses, etc.

    We do have an explain functionality in Atlas Search, which returns information about the $search query plan and execution statistics. The results returned by explain("executionStats") has a section on score, which provides statistics related to scoring documents in the result set. However, while the aforementioned statistics information provides details on the number of invocations and the nanos elapsed, it does not exactly tell "how" the score was calculated for each document.

    This is an enhancement request for introducing such a functionality that can provide the specific details on how the score(s) are calculated for individual document(s).

    Every document returned by an Atlas Search query is assigned a score based on relevance. Many factors can influence a document's score, including the position of the search term in the document, the frequency of occurrence of the search term in the document, the type of operator the query uses, the type of analyzer the query uses, etc.

    We do have an explain functionality in Atlas Search, which returns information about the $search query plan and execution statistics. The results returned by explain("executionStats") has a section on score, which provides statistics related to scoring documents in the result set. However,… more

    14 votes

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    4 comments  ·  Delete…  ·  Admin →
    completed  ·  Elle responded

    [Changelog] Added scoreDetails boolean option to retrieve a detailed breakdown of the score for each document in the query results.

20. 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.

    13 votes

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    1 comment  ·  Delete…  ·  Admin →
    completed  ·  AdminSeth (Admin, MongoDB) responded

    Dedicated search nodes have been delivered for GCP and AWS.  Azure will ship soon.