  Query Auto-Completion (QAC) is an ubiquitous feature of modern textual search
systems, suggesting possible ways of completing the query being typed by the
user. Efficiency is crucial to make the system have a real-time responsiveness
when operating in the million-scale search space. Prior work has extensively
advocated the use of a trie data structure for fast prefix-search operations in
compact space. However, searching by prefix has little discovery power in that
only completions that are prefixed by the query are returned. This may impact
negatively the effectiveness of the QAC system, with a consequent monetary loss
for real applications like Web Search Engines and eCommerce. In this work we
describe the implementation that empowers a new QAC system at eBay, and discuss
its efficiency/effectiveness in relation to other approaches at the
state-of-the-art. The solution is based on the combination of an inverted index
with succinct data structures, a much less explored direction in the
literature. This system is replacing the previous implementation based on
Apache SOLR that was not always able to meet the required
service-level-agreement.
