Indexing your Data
Introduction
Before we begin querying documents, let’s briefly mention the importance of having an appropriate and balanced approach to indexes.
Creating indexes can speed up the performance of queries. A query will typically return results more quickly if it can take advantage of an existing database index to search, narrowing down the set of documents to be examined.
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Constraints
Couchbase Lite for android does not currently support partial value indexes; indexes with non-property expressions.
You should only index with properties that you plan to use in the query.
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Creating a new index
You can use SQL++ or QueryBuilder syntaxes to create an index
Example 2 creates a new index for the type and name properties, shown in this data model:
{
"_id": "hotel123",
"type": "hotel",
"name": "The Michigander",
"overview": "Ideally situated for exploration of the Motor City and the wider state of Michigan. Tripadvisor rated the hotel ...",
"state": "Michigan"
}N1QL
The code to create the index will look something like this:
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Kotlin
-
Java
database.createIndex(
"TypeNameIndex",
ValueIndexConfigurationFactory.create("type","name")
)
database.createIndex(ValueIndexConfiguration(["type", "name"]), "TypeNameIndex");QueryBuilder
The code to create the index will look something like this:
-
Kotlin
-
Java
database.createIndex(
"TypeNameIndex",
IndexBuilder.valueIndex(
ValueIndexItem.property("type"),
ValueIndexItem.property("name")
)
)database.createIndex(
"TypeNameIndex",
IndexBuilder.valueIndex(
ValueIndexItem.property("type"),
ValueIndexItem.property("name")));Summary
When planning the indexes you need for your database, remember that while indexes make queries faster, they may also:
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Make writes slightly slower, because each index must be updated whenever a document is updated
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Make your Couchbase Lite database slightly larger.
So too many indexes may hurt performance. Optimal performance depends on designing and creating the right indexes to go along with your queries.