In Firestore Standard edition, a query that needs an index the database does not have fails with a missing-index error; Firestore does not fall back to scanning the collection. For the common composite-index case, open the link in the error, check the proposed fields and scope against the query your app actually sends, create the index, and wait until its build finishes. Then save the index definition in your deployment configuration so the fix is repeatable.
Why Firestore reports a missing index
Firestore uses indexes to serve queries. It creates basic single-field indexes automatically, but it does not create every possible combination of fields. A query that combines filters, range constraints, or ordering can therefore need a composite index that has not been configured. In Standard edition, unsupported Core queries fail instead of falling back to a collection scan. See Firebase’s index overview and Standard edition documentation.
The required index depends on the query’s complete shape, not just the fields visible in its filter. Field mode and scope matter: ascending or descending modes support ordinary comparisons and ordering; array-contains mode supports array membership filters; vector mode supports nearest-neighbor queries. A collection-group query needs a collection-group-scoped index. Also, a document missing a value for a field in the index is not included in that index, which can affect which documents a query returns. Firebase documents these rules in its index overview.
Fix the ordinary missing composite index
- Open the generated error link. For a missing composite index, the link opens the Firebase console with index information populated. Compare the proposed collection, fields, modes, and scope with the query your application actually issues.
- Create the index. Submit it in the console once the definition matches the query. If you cannot use the link, open the Firestore Indexes tab and add an index for the collection and fields involved. For non-array and non-map fields, the management guide says to choose ascending or descending ordering even when the query does not order by that field; this selection does not change equality-filter behavior.
- Wait for the build to finish. Creating an index is not instantaneous: Firestore must build it and may backfill existing data. Check its status in the console before retrying. Firebase says creation can take a few minutes depending on the query and index build. See the index management guide.
- Check permissions if creation is rejected. The management guide lists Datastore owner, index admin, editor, or owner roles, as well as specified index permissions for custom roles. Consult the guide for the required permissions in your environment.
If the error concerns a vector index rather than an ordinary composite index, the error provides a Google Cloud CLI command. Follow that path rather than treating it as a console-created composite index; Firebase’s index management guide describes both cases.
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When the error persists: troubleshoot the exact mismatch
1. Verify the project and database
Confirm which Firebase or Google Cloud project and which Firestore database the running application targets. A correctly created index in a different project or database will not support the failing query. Treat the generated error definition as a starting point, then compare it with the query from the running code.
2. Compare every query property with the index
Write down the filters and operators, range constraints, ordering, array filters, and whether the query targets a single collection or a collection group. Check that the index has the corresponding fields, field modes, and scope. Composite indexes support at most one array field; see Firebase’s index overview.
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3. Confirm the index is ready
An index that was submitted successfully can still be building or backfilling. Check its state in the console and retry after the build completes. The management guide notes that build time varies with the query and index build.
4. Keep the fix in versioned configuration
For a team workflow, store index definitions in firestore.indexes.json and deploy them with firebase deploy --only firestore when appropriate. Terraform is another documented way to define indexes. If someone creates or edits an index in the console, synchronize that change with the local configuration so the deployed setup remains reproducible. Firebase documents configuration in its index configuration reference and index management guide.
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5. Use Query Explain for planning and performance questions
Query Explain can help when the index exists but the query’s plan or efficiency is unclear. Its default mode returns planner information without executing the query; analyze mode executes it and returns runtime and billing statistics. The guide says streaming queries are not yet supported. Explain helps show which indexes a query uses and assess index layout, but it does not replace a required index. See Firestore Query Explain.
Separate missing-index errors from index limits
Not every indexing problem is solved by adding a composite index. Firebase documents a maximum of 40,000 index entries per document and a maximum of one array field per composite index. Large arrays or maps can approach the entry limit. For fields that do not need indexing, the index guide recommends exemptions in relevant cases, including large unused values and some high-write sequential fields. These are index-design or index-build concerns, distinct from the usual missing-composite-index fix. See Firebase’s index overview.
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Know which edition the guidance applies to
The required-index behavior described here is for Firestore Standard edition Core queries. Firestore Enterprise documentation describes indexing as optional for Enterprise workflows, so do not assume the Standard-edition failure model applies unchanged there. See the Standard edition guide, Enterprise pipelines overview, and Enterprise indexing overview.
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