Querying and indexing document arrays in Couchbase, particularly for array entries within specific date ranges, is an advanced feature that enhances data retrieval efficiency. The process involves creating a secondary index on the date field of an embedded account history array, allowing for precise range queries. By using the DISTINCT function within the index creation, the index only includes entries that have a date field, thereby excluding irrelevant data. This functionality is demonstrated using N1QL's UNNEST feature, which integrates account history data with root document fields like email, without requiring additional JSON parsing. The document illustrates a query example that retrieves email and account information for entries dated between '2016-02-01' and '2017-06-01', showcasing the ease of extracting structured data from complex JSON documents. The text also encourages trying out the setup using Docker, with a GitHub repository providing resources to create a development environment featuring a single-node Couchbase cluster and a Node.js service for provisioning.