This section describes indexing for Cloud Firestore Enterprise edition. Cloud Firestore Enterprise edition does not create any indexes by default. To improve database performance, create indexes for your most commonly used queries.
Indexes have a large impact on the performance of a database. If an index exists for a query, the database can efficiently return results by reducing the amount of data that needs to be scanned and reducing the work needed to sort the results. However, index entries increase storage costs and the amount of work done during a write operation on indexed fields.
Differences between editions
The following table gives an overview of the major indexing differences between Cloud Firestore Standard edition and Cloud Firestore Enterprise edition.
| Feature | Cloud Firestore Standard edition | Cloud Firestore Enterprise edition |
|---|---|---|
| Indexing requirement | All queries require indexes to execute. Queries are generally performant due to this requirement. | Indexes are not required for queries. Unindexed reads are possible, removing a barrier for prototyping. |
| Automatic indexing | By default, single-field indexes are automatically created for all fields within documents. | No automatic indexes. You must manually manage all indexes. |
| Index density | Sparse by default. A document in a collection group is indexed only if the document contains a value for every indexed field. | Non-sparse by default. All documents in the collection group are indexed.
Indexed fields without a value are set to NULL. Behavior
can be changed with the sparse index option. |
| Supported index types and options |
|
|
Index definition and structure
An index consists of the following:
- a collection ID
- a list of fields in the given collection
- an order, either ascending or descending, for each field
An index can also enable the sparse or unique options.
Index ordering
The order and sort direction of each field uniquely defines the index. For example, the following indexes are two distinct indexes and not interchangeable:
| Collection | Fields |
|---|---|
| cities | country (ascending), population (descending) |
| cities | population (descending), country (ascending), |
When creating an index to support a query, include the fields in the same order as your query.
Index density
By default, index entries store data from all documents in a collection. This is known as a non-sparse index. An index entry will be added for a document regardless of whether the document contains any of the fields specified in the index. Non-existent fields are treated as having a NULL value when generating index entries. To change this behavior, you can define the index as a sparse index.
Sparse indexes
A sparse index indexes only the documents in the collection that contain a value (including null) for at least one of the indexed fields. A sparse index reduces storage costs and can improve performance.
Unique indexes
Set the unique index option to enforce unique values for the indexed fields. For indexes on multiple fields, each combination of values must be unique across the index. The database rejects any update and insert operations that attempt to create index entries with duplicate values. If the data of the indexed fields contains duplicate values and you attempt to create a unique index, then the index build fails with an error message in the operation details.
Absent fields in a unique index
If you insert a document with missing fields for the unique index, the index
sets null values for the missing fields. The resulting index entry must be
unique or the operation fails.
For example, with this index:
| Collection | Fields indexed | Query scope |
|---|---|---|
| cities | name (ascending) | Collection |
If you add the document {"abbreviation": "LA"} to the collection, the unique
index creates an entry with name set to null. If you then try to add the
document {"abbreviation": "NYC"}, the operation fails because the resulting
entry for the unique index is the same.
The same behavior applies to unique indexes with multiple fields.
When creating or updating a document, missing
indexed fields are set to null and the resulting index entry must be
unique in the index.
Troubleshoot index building errors
You might encounter index building errors when managing your indexes. An indexing operation can fail if the database encounters a problem with the data. Indexing operations can fail for the following reasons:
- You have reached an index limit. For example, the operation may have reached the maximum number of index entries per document. If index creation fails, you see an error message. If you have not reached an index limit, retry the index operation.
- You set the unique index option and the data of the indexed fields would create duplicate index entries. To proceed, remove duplicate combinations of values from the data.
What's next
Learn how to create and manage indexes.