Using Covering Indexes on a Multiple Document Type Bucket

In an effort to optimize slow N1QL queries on Couchbase Server 4.1, the author shares their experience of enhancing an internal Java application's performance hosted on a low-budget Amazon EC2 instance. Initially, the queries were sluggish due to reliance on a generic primary index. To improve query performance, the author implemented a covering index specifically tailored to the query's needs, targeting the "date" and "type" properties, but noticed no performance change initially. After running an "EXPLAIN" command, it was revealed that the primary index was still being used because not all documents contained the necessary properties. By revising the query to check for the presence of these properties, the author successfully utilized the covering index, resulting in a significant performance boost.

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