153 results found

1. Support unstructured text entity recognition

   We have unstructured text and would like Atlas Search to detect important entities so that we can use them for relevance and ranking

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2. Support filtering by empty array

   Atlas Search should support matching a fields set to an empty array. This behavior is not supported by either of the exists, equals, or in operators, and is a very common use case.

   https://search-playground.mongodb.com/tools/code-playground/snapshots/668bd0688e71d69d70fc71dd

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3. Support Collation for Atlas search sort

   I have a use case to sort by product names (strings). We have products that start with letters and some that start with numbers. Currently, the products that begin with numbers are always at the top when you sort in ascending order. We would like to sort alphanumerically so that the products beginning with letters are displayed first and those with numbers at the very end.

   It would therefore be nice if the $search operator could support collations with the sort parameter.
   See: https://www.mongodb.com/community/forums/t/atlas-search-sort-with-collation-locale/269296/5

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4. Increase the disk size limit of 3.2 TB on Search tier.

   Atlas search tier limits the disk size to 3.2 TB even on the highest search tier S110.

   •  

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5. Compatibility with shard reduction

   We are using Atlas Search (as a sidecar process) and aren't able to reduce the number of our shards without causing downtime to Atlas Search. A shard mechanism that's compatible with Atlas Search is necessary for us to optimize our costs.

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6. Improve the Search Playground
   2 votes

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7. expose json schema when doing dynamic mapping

   It would be really helpful to see the json schema when doing dynamic mapping so I’ll be able to alter it according to my needs. Building everything from scratch takes a lot of time.

   I use the json editor. I want to index a lot of fields and some of the fields contains arrays and documents that I want to index as well. Writing the schema to index all the fields takes a lot of time. When I do dynamic indexing I know that you have the schema in the backend. It will be very helpful to expose this schema to users

   It would be really helpful to see the json schema when doing dynamic mapping so I’ll be able to alter it according to my needs. Building everything from scratch takes a lot of time.

   I use the json editor. I want to index a lot of fields and some of the fields contains arrays and documents that I want to index as well. Writing the schema to index all the fields takes a lot of time. When I do dynamic indexing I know that you have the schema in the backend. It will be very helpful to expose this schema… more

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8. Feedback on the Atlas Search Visual Index Builder

   How can we improve?

   2 votes

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9. Allow indexing of synthetic fields

   In order to work around some of the inherent limitations of the Atlas Search capabilities, it would be very useful if we could define and index arbitrary synthetic fields using any normal MongoDB functions & operators. All other Atlas Search capabilities (query, sort, etc.) should support these synthetic fields the same as any other.

   This could possibly be implemented with a new field type and a custom analyzer that supports an aggregate pipeline on the input document and returning the field as its output. This is just an idea, there may be better ways to do it.

   {
     "mappings": {
       "dynamic": false,
       "fields": {
         "foobar": {
           "type": "synthetic",
           "analyzer": "my-aggregate-analyzer"
         }
       }
     },
     "analyzers": [
       {
         "name": "my-aggregate-analyzer",
         "aggregate": [
           { <stage> }, 
           ...
         ]
       }
     ]
   }
   

   In order to work around some of the inherent limitations of the Atlas Search capabilities, it would be very useful if we could define and index arbitrary synthetic fields using any normal MongoDB functions & operators. All other Atlas Search capabilities (query, sort, etc.) should support these synthetic fields the same as any other.

   This could possibly be implemented with a new field type and a custom analyzer that supports an aggregate pipeline on the input document and returning the field as its output. This is just an idea, there may be better ways to do it.

   {
     "mappings": {

   … more
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10. Sort by a specific array index

    When creating indexes and sorting with "normal" queries, it is possible to index/sort on a specific array index (e.g. foo.0.bar). I do this because the search results grid in our UI only has room to show the first foo.bar result, so it doesn't make sense visually to sort by additional objects which the user can't see.

    Since the new Atlas Search Sort syntax looks the same, I was hoping to do that with it as well, but it doesn't seem possible.

    Example:

    [
      { "xyzzy": "xyzzy",
        "foo": [ { "bar": "A" } ] },
    
      { "xyzzy": "xyzzy",
        "foo": [ { "bar": "B" }, { "bar": "D" } ] },
    
      { "xyzzy": "xyzzy",
        "foo": [ { "bar": "C" } ] }
    ]
    

    {
      index: "myindex",
      returnStoredSource: true,
      phrase: { path: "xyzzy", query: "xyzzy" },
      sort: { "foo.0.bar": -1 }
    }
    

    See: https://support.mongodb.com/case/01169701

    When creating indexes and sorting with "normal" queries, it is possible to index/sort on a specific array index (e.g. foo.0.bar). I do this because the search results grid in our UI only has room to show the first foo.bar result, so it doesn't make sense visually to sort by additional objects which the user can't see.

    Since the new Atlas Search Sort syntax looks the same, I was hoping to do that with it as well, but it doesn't seem possible.

    Example:

    [
      { "xyzzy": "xyzzy",
        "foo": [ { "bar": "A" } ] },
    
      { "xyzzy": "xyzzy",
        "foo": [

    … more
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11. Data type coercion when document field type doesn't match index field type

    When a document field type doesn't match the index field type, it seems to be indexed as "blank" and won't match anything. Many data types are readily convertible between type representations. It would be great if Atlas Search could do that for us and would open up richer functionality by allowing us to use operators/analyzers/etc. on types that don't normally support them.

    My particular use case is to allow searching & sorting on numbers stored as strings. When creating indexes and sorting with "normal" queries, it is possible to sort numbers stored as strings by their numerical ordering rather than alphabetical by using { collation: { locale: "en_US", numericOrdering: true } } on the index definition and applying query.collation(Collation.of(Locale.US).numericOrdering(true)) to the query itself. I was hoping to do this with Atlas Search Sort as well, but it isn't possible.

    Examples:
    string "1000.00" = number 1000.00
    boolean true = number 1
    boolean true = string "true"
    etc.

    See: https://support.mongodb.com/case/01169737

    When a document field type doesn't match the index field type, it seems to be indexed as "blank" and won't match anything. Many data types are readily convertible between type representations. It would be great if Atlas Search could do that for us and would open up richer functionality by allowing us to use operators/analyzers/etc. on types that don't normally support them.

    My particular use case is to allow searching & sorting on numbers stored as strings. When creating indexes and sorting with "normal" queries, it is possible to sort numbers stored as strings by their numerical ordering rather than… more

    2 votes

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12. Allow comments in JSON code

    It would be great if we could keep comments in JSON generated items such as indexes (both MongoDB and Atlas Search)

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13. Allow indexing of only part of a collection

    Would be great to be able to create an Atlas Search index that only indexes part of a collection (like partialFilterExpression for a regular index). This would be valuable in situations where a collection is quite large (which would create a lot of unnecessary overhead) but only a small fraction of it needs to be searchable.

    2 votes

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14. 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.

    2 votes

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15. 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

    2 votes

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16. Support Chinese Language Analyzer : Pinyin

    PinYin IKAnalyzer Support

    For most Chinese Speaking Customer,

    https://github.com/medcl/elasticsearch-analysis-pinyin

    Is also a popular analyzer that many of our customer is using it

    2 votes

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17. Pre-Compiled Synonyms Collections

    There are many instances where the synonym-related needs of users are similar. For instance, in the case of names, Robert, Rob, and Bob are considered synonymous for some use cases.

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18. atlas search null

    A string or number data type that has the value 'null' is returned and is not excluded even with filtering with query: 'null' entry. The $exists and $compound operators may benefit from excluding fields that have a value of 'null' but not exactly non-existent in a document.

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19. Allow scoring with real word frequency (instead of word frequency per shard)

    We are migrating from ES and there is an option when having a few documents to do a first query to return the term frequencies for all shards and then do the normal query using these frequencies to calculate the score.

    The option is called "?searchtype=dfsquerythenfetch" and it's documented here: https://www.elastic.co/guide/en/elasticsearch/guide/current/relevance-is-broken.html.

    It would be great to have a similar option in Atlas Search! Thank you

    2 votes

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20. nested facets

    in elastic we can do complex nested facet groups such as

    "aggs": {
    "resellers": {
    "nested": {
    "path": "resellers"
    },
    "aggs": {
    "min_price": {
    "min": {
    "field": "resellers.price"
    }
    }
    }
    }
    }

    It would be nice to see the same functionality in atlas search

    2 votes

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