4 results found

1. Allow the ability to test Atlas Search locally

   We need text search to "somehow" work locally and ci.

   We've a multiregional team and development has to continue if there are internet problems in one of our offices.

   Our workflow consists of :

   • unitTest using in-memory-mongodb

   • local testing, using the developers local mongo instance

   • test env testing with a QA team (using atlas, but <30m)

   • production launch

   With the current feature set, the first time we can test a feature is on production. Even if low-tier availability was there the other two issues are blockers as we won't just ditch TDD for textSearch.

   364 votes

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   36 comments  ·  Delete…  ·  Admin →
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   started  ·  Elle responded

   Now in Public Preview: Introducing a Local Experience for Atlas, Atlas Search, and Atlas Vector Search with the Atlas CLI

   
   

   Relevant docs found here.

   
   

   Please feel to reply with feedback or leave comments. Happy to connect directly and include your team in our Early Access Program to provide additional help. 

2. Support Partial Indexing

   We have a large collection but would only like to index the most recent entries, which would reduce the amount of space and resources it would take to index and query.

   61 votes

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   started  ·  12 comments  ·  Delete…  ·  Admin →
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3. Support for nested datatype search

   It appears that Atlas Search does not yet support nested documents in arrays like MongoDB

   https://docs.mongodb.com/v4.2/reference/operator/query/elemMatch/

   41 votes

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   started  ·  Elle responded

   Tutorial for how to implement can be found here. 

4. 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

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