Challenges with Firebase Firestore Query Index when Using Multiple Filters and Combining Them

I am in the process of developing a website that involves pagination and filtering specific data.

if (eventType) query = query.where('general.eventType', '==', eventType); 
if (price) query = query.where('general.eventTicketPrice', price == "free" ? '==' : '>=', 0);
if (startDate) query = query.where('general.eventDates.start', '>=', new Date(startDate));
if (endDate) query = query.where('general.eventDates.start', '<=', new Date(endDate));
if (location) query = query.where('general.location.city', '==', location);
if (participation) query = query.where('general.locationType', '==', participation);
...
...

Including about 20 different filters, each filter selection requires me to generate a new index in firebase. It seems like I will have to create an index for every possible combination of filters. To make this process more efficient, I created a tool that automatically generates the necessary queries and provides me with the URL for creating the index, but there are a vast number of combinations to sift through.

Is there a solution to streamline this issue?

I considered retrieving all documents and manually applying the filters. While this method is straightforward to implement, it may result in higher costs and increased latency. Although currently my dataset is relatively small, I anticipate needing to interrogate hundreds, if not thousands, of documents in the future.

What recommendations do you have for resolving this challenge effectively?

Answer №1

When working with Firestore, it's important to remember that each query is executed against one or more indexes, but this doesn't mean you need a unique index for every query. According to the documentation on index merging:

Cloud Firestore uses an index for every query, but it doesn't always require a separate index for each query. For queries with multiple equality (==) conditions and possibly an orderBy condition, Cloud Firestore has the ability to reuse existing indexes. By combining simple equality filters, Cloud Firestore can create composite indexes needed for larger equality queries.

In your scenario, consider moving any relational conditions (>=, <=, etc) to the end of the query. This way, you may be able to rely on the existing single field indexes for most equality comparisons.

It's worth noting that queries using merged indexes may have slower performance compared to those utilizing dedicated composite indexes. Therefore, monitoring query performance and optimizing as necessary is crucial.

I shared a brief video highlighting an instance of this during Google I/O last year, which you can watch here.

Answer №2

Unclear about the issue in your situation, but generally:

Cloud Firestore guarantees query performance by mandating an index for each query. The necessary indexes for basic queries are automatically generated for you.

Learn more about indexing here

For additional information, visit this link ...

Restrictions on Queries

The following points outline Cloud Firestore's query restrictions:

  • Cloud Firestore offers support for logical OR queries using operators like or, in, and array-contains-any. However, these queries are restricted to 30 disjunctions based on the query's disjunctive normal form.
  • Each disjunction can have only one array-contains clause; combining array-contains with array-contains-any within the same disjunction is not allowed.
  • Combining not-in with in, array-contains-any, or or in a single query is prohibited.
  • Only one not-in or != is permitted per query, supporting up to 10 comparison values for not-in.
  • The total of filters, sort orders, and parent document path cannot exceed 100 in a query. This calculation is based on the query's disjunctive normal form.
  • An inequality filter on a field in a query implies ordering by that field and checks for the existence of that field.

Constraints on OR Queries

To prevent excessive computational load, Cloud Firestore imposes limits on the combination of AND and OR clauses in a query. To enforce this limit, queries involving logical OR operations (or, in, and array-contains-any) are converted to disjunctive normal form. Cloud Firestore restricts a query to a maximum of 30 disjunctions in disjunctive normal form.

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