Secondary indexes in relational database systems are traditionally built under the assumption that one data record maps to one indexed value. Nowadays, particularly in NoSQL systems, single data records can hold collections of values that users want to access efficiently in an ad-hoc manner. Multi-valued indexes aim to give users the best of both worlds: (i) to keep a more natural data model of records with collections of values, and (ii) to reap the benefits of a secondary index. In this paper, we detail the steps taken to realize multi-valued indexes in AsterixDB, a Big Data management system with a structured query language operating over a collection of documents. This includes (a) creating the specification language for such indexes, (b) illustrating data flows for bulk-loading and maintaining an index, and (c) discussing query plans to take advantage of multi -valued indexes for use in predicates with existential and universal quantification. We conclude with experiments that measure the impact of maintaining an AsterixDB multi-valued index and experiments that compare the query performance our multi-valued indexes against similar indexes in MongoDB and Couchbase Server's Query Service.Published by Elsevier Ltd. This is an open access article under the CC BY license(http://creativecommons.org/licenses/by/4.0/).
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