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Atlas Search

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  1. Atlas Search Local Deployment Lucene Indexing Latency of 1s

    We are unit testing our Java application using the (awesome!) Atlas Search Local Deployments.

    However, we are seeing a longer delay than we'd like between the time we add data to a collection and the time it is searchable in the Atlas Search Lucene index.

    It is almost always uniformly 1 second.

    Here's a unit test that demonstrates the issue:
    https://github.com/luketn/atlas-search-unit-test-latency-issue/blob/main/src/test/java/com/mycodefu/MainTest.java#L95

    This should take a few milliseconds to run, but it will take almost exactly a minute.

    Each iteration of the loop in the test will take almost exactly 1s.

    The first iteration will usually be shorter, because we start…

    3 votes

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  2. 2 votes

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  3. Atlas Search aggregation pipeline TypeScript type definitions

    It would be so much easier to write aggregation pipelines if we had type checking and type hinting.

    At this moment we can pass any JSON there. There is no driver or library that would check if it's correct or that would type check the input.

    I'm attaching some screenshots that show how it could work.

    2 votes

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  4. Ability to Upsert an Atlas Search Index

    Currently, it is possible to use createSearchIndex and updateSearchIndex to create and update search indexes, respectively. It would be beneficial if the updateSearchIndex allowed for upsert functionality, so that if the index does not exist, it can be created. This functionality would be useful in certain scenarios where the indexes are created (if they don't exist) or updated (if they do exist) programmatically, which have to rely on implementing a custom if-else logic by leveraging getSearchIndexes().

    3 votes

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  5. 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.

    4 votes

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  6. 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

    1 vote

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  7. 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.

    2 votes

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  8. 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.

    2 votes

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  9. 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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  10. allow atlas search for serverless instances

    As of now, atlas search is not allowed for serverless instances, but many people using serverless instances and they atlas search to perform some advanced search queries.

    1 vote

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  11. Non-sequential or Deep Pagination

    I want to be able to paginate results in non-sequential order, e.g. Skip from page 1 to 5, or skip from first to last page of results

    2 votes

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  12. 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…

    2 votes

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  13. 1 vote

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  14. Atlas search Index is not updating.

    Each time I perform CRUD operations in my collection, the Search Index doesn't update immediately. Instead, it takes a considerable amount of time. This issue significantly hampers the progress of my project. Any suggestions for improvement would be greatly appreciated.

    1 vote

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  15. 1 vote

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  16. 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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  17. 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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  18. Allow sort by boolean fields

    When creating indexes and sorting with "normal" queries, it is possible to index/sort on a boolean field. I was hoping to do this with Atlas Search Sort as well, but it only supports date, number and token (string).

    While workarounds are available (using custom scoring), these are not easily combined with multiple sort fields and make programmatically building a query vastly more complex.

    See: https://support.mongodb.com/case/01169728

    3 votes

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    started  ·  2 comments  ·  Admin →
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  19. 2 votes

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  20. 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…

    3 votes

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