154 results found

1. 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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2. Provide the ability to auto-scale dedicated search nodes

   Currently, dedicated search nodes in Atlas Search cannot be auto-scaled. This is a feature request to introduce the ability to auto-scale dedicated search nodes.

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3. Atlas can be configured to raise alert notification when the Atlas cluster already scales to the max tier.

   Atlas can be configured to raise alert notification only when the Atlas cluster already scales up to the max tier allowed. This can be help to avoid notification spams which does not require operation team actions and focus on the critical resource consumption alerts like cpu, memory, disk IO.

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4. Text Analysis for Field Mappings

   Show how an indexed document and query terms get analyzed to produce tokens based on my field mapping configuration.

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5. Feedback on the Atlas Search Visual Index Builder

   How can we improve?

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6. Synonyms support for autocomplete operator

   Hi.

   Having synonyms support for the autocomplete operator would be great! Is this possible?

   Best regards,
   Tim

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7. Add option for specifying OR or AND when using multiple terms in autocomplete search string

   Hi.

   Currently the autocomplete operator handles multiple terms in a query string as OR, not AND. That means that one of the terms should match, not all of them.

   An option for specifying how multiple terms should be handled by the autocomplete operator (if one of the terms should match (OR) or all of them should match (AND)) would be great!

   So having an AND handling would mean the more terms I add to the search string the more specific the results will be. With OR it's the other way around.

   Thanks!

   Best regards,
   Tim

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8. Support highlights in embeddedDocuments autocomplete

   According to docs, currently it is not possible to get highlights inside embeddedDocuments, in autocomplete requests.

   This makes array of objects (embeddedDocuments) autocomplete unusable in our use case.

   3 votes

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9. Add Atlas Search for Enterprise Advanced

   Due to customer/project constraints, I need to have the ability to use $search to query millions of historical data records with regex and wildcards queries at real-time, on a Enterprise Advanced environment.

   The data cannot be exported to Atlas and it cannot depend on Internet connection, so the functionality must be On-Premises only.

   3 votes

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10. Additional function scores decay functions: exp & linear

    Atlas Search currently only supports gaussian decay function for function scores. In 4 out of 5 of our use cases exp would be a much more natural choice.

    https://www.elastic.co/guide/en/elasticsearch/reference/current/query-dsl-function-score-query.html#function-decay

    Hopefully that is just a small task!

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11. Ruby on Rails support of Atlas Search index management

    Feedback from customer: "Currently we need to manage core DB indexes and atlas search indexes separately. We'd prefer to manage them all in the Rails model code but MongoID only supports core DB index configuration. We're having to use terraform for atlas search index management."

    1 vote

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12. Allow aggregate pipeline on input documents before Atlas Search indexing

    If Altas Search allowed us to apply an aggregate pipeline to input documents before they are sent to Atlas Search for indexing, it would open up a TON of new possibilities not currently supported. We could do data transformations, type conversions, synthetic fields, etc.. I've opened up a number of other suggestions for these things, but an input aggregate pipeline could solve all of them in one "easy" solution. Since aggregate pipelines already exist and are deeply embedded in MongoDB, I'm hoping it would be trivial to implement as well. Simply pick up one or more new documents to be indexed, run them through the pipeline and then send them to the Atlas Search engine for indexing.

    Here's what that might look like:

    {
      "mappings": {
        "dynamic": false,
        "aggregate": [
          { <stage> },
          ...,
          {
            "$addFields": {
              "my-synthetic-field": <expression>
            }
          }
        ],
        "fields": {
          "my-synthetic-field": {
            "type": "string"
          }
        }
      }
    }
    

    Here are some of the other suggestions I (or others) have made that could be solved with this approach:

    https://feedback.mongodb.com/forums/924868-atlas-search/suggestions/47049898-allow-indexing-of-synthetic-fields
    https://feedback.mongodb.com/forums/924868-atlas-search/suggestions/47049757-data-type-coercion-when-document-field-type-doesn
    https://feedback.mongodb.com/forums/924868-atlas-search/suggestions/47049775-allow-sort-by-boolean-fields
    https://feedback.mongodb.com/forums/924868-atlas-search/suggestions/47049775-allow-sort-by-boolean-fields
    https://feedback.mongodb.com/forums/924868-atlas-search/suggestions/40734700-support-decimal128

    If Altas Search allowed us to apply an aggregate pipeline to input documents before they are sent to Atlas Search for indexing, it would open up a TON of new possibilities not currently supported. We could do data transformations, type conversions, synthetic fields, etc.. I've opened up a number of other suggestions for these things, but an input aggregate pipeline could solve all of them in one "easy" solution. Since aggregate pipelines already exist and are deeply embedded in MongoDB, I'm hoping it would be trivial to implement as well. Simply pick up one or more new documents to be… more

    4 votes

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13. 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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14. 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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15. 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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16. Token filter that removes duplicated entries

    Create a token filter or a tokenizer or even an option that removes duplicate words in fields  to avoid misleading scoring. 
    For example: if I insert a document with a property "Testing testing document", another with "Testing example" and a third with "Testing foo" and I search for "Testing foo", the first document receives a higher score.
    

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17. 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)

    2 votes

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18. knnBeta Limitations and Syntax

    I tested the new knnBeta operator today and it worked so far.
    Can we expect the current operator limitations to be gone by release?
    The current limitations make it virtually impossible to use the knn operator as a replacement for previous text operators (like text).
    I would prefer the filter parameter to be omitted and knn not have to be a top-level operator.

    1 vote

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19. 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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20. Mutli-select faceting / facets should not affect their own filter field

    I want to build multi-select facet without having to run separate queries to calculate bucket counts for each active filter. Described in detail here: https://yonik.com/multi-select-faceting/

    9 votes

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