Algolia search on nested objects in a record - multiple facetFilters in one object

Question

I’m migrating from Mongo to Firebase with Algolia on top to provide the search. But hitting a snag coming up with a comparable way to search in individual elements of a record.

I have an object that stores when a room is available: from and to. Each record can have many individual from/to combos (see the sample below with 2). I want to be able to run a search something like:

roomavailable.from <= 1522195200 AND roomavailable.to >=1522900799

But only have the query search a match within each element, not any facet in all elements. An element query in Mongo works like that. But if I run that query on the record listed below, it will return the record, because the two roomavailable objects satisfy the .from and .to query. I think.

Is there a way to ensure the search is looking only at matching a pair of .from and .to in an individual object/element?

Below is the pertinent part of the record stored in Algolia so you can see the structure.

"roomavailable": [
        {
          "_id": "rJbdWvY9M",
          "from": 1522195200,
          "to": 1522799999
        },
        {
          "_id": "r1H_-vKqz",
          "from": 1523923200,
          "to": 1524268799
        }
      ],

And here is the Mongo (mongoose) equivalent where its searching inside individual elements (this works):

$elemMatch: {
                    from: {
                        $lte: moment(dateArray[0]).utc().startOf('day').format()
                    },
                    to: {
                        $gte: moment(dateArray[1]).utc().endOf('day').format()
                    }
                }

I have also tried this query but it seems to still match either the .from AND .to but in any of the the individual roomavailable elements:

index.search({
  query: '',
  filters: filters,
  facetFilters: [roomavailable.from: 1522195200, roomavailable.to: 1524268799],
  attributesToRetrieve: [
    "roomavailable",
  ],
  restrictHighlightAndSnippetArrays: true
})

I found a couple posts on Algolia discussing using 1 bracket vs. 2 brackets in the facetFilters. I've tried both. Neither work.

Any suggestions would be awesome. Thanks!

Answer 1

Edit: See discussion on Algolia Discourse:

https://discourse.algolia.com/t/how-to-match-multiple-attributes-in-nested-object-with-numericfilters/4887/8

---

Hi @kanec, thanks for clarifying your question!

Indeed what @Alefort suggested (using roomavailable in a separate index) would be the easiest option since the query I mentioned above will definitely return the results you want. This will mean that you'll have to query the room availability index separately in order to get which IDs are available, so you'll have to use multiple-queries:

https://www.algolia.com/doc/api-reference/api-methods/multiple-queries/

That said, I asked our core API team to see if there's a more reasonable way to approach this issue, but I fear that this is a filter limit due to performance reasons with arrays. You could transform your data structure in the following and index your rooms as an object instead:

[
  {
    "roomavailable": {
      "0": {
        "_id": "rJbdWvY9M",
        "from": 1522195200,
        "to": 1522799999
      },
      "1": {
        "_id": "r1H_-vKqz",
        "from": 1523923200,
        "to": 1524268799
      }
    }
  }
]

So you can apply the following filter:

{
  "filters": "roomavailable.0.from <= 1522195200 AND roomavailable.0.to >= 1522799999 AND roomavailable.1.from <= 1522195200 AND roomavailable.1.to >=1522900799"
}

The downside of this is that you'll need to know the length of roomavailable in order to build the search query on the front-end (you can do so at indexing time by adding a roomavailable_count property) and also this will probably will be less performant with a considerable number of rooms per item; in this case, switching to a dedicated index makes totally sense for the following reasons:

1. If in your backend you frequently update available rooms you won't impact the other indices' build time
2. Filters will perform better (as explained above)
3. Indexing strategy will be simpler to handle

Let me know what you think about this and if it helps you out.