The gap recovery is the weakest recovery class and it ensures neither input nor output preservation. Therefore, a system failure results in missing results for all incoming elements for all incoming elements before Odysseus can process them again (at-most-once). Gap recovery addresses the needs of applications that operate solely on the most recent information (e.g., sensor-based environment monitoring) where dropping old data is tolerable for reduced recovery time and run-time overhead. Because elements may be aggregated, missing elements may also result in incorrect output values. (Reference: J.H. Hwang et al., High-Availability Algorithms for Distributed Stream Processing, 2005)
Documentation under progress.