We propose two extensions for a state-of-the-art method of rollback-recovery in distributed CEP (complex event processing). In CEP, an operator network is used to search for patterns in events streams. Sometimes these operators fail and lose their state. Rollback-recovery is a method for dealing with such state losses. The type of rollback-recovery we consider is upstream backup, where the state of a failed operator is recovered by replaying to it the input events that led it to that state. These events are kept in upstream operators’ memory buffers, which are trimmed continuously as the downstream operator progresses. The first extension we propose saves memory and speeds up recovery by avoiding to store and retransmit unnecessary events. The second extension makes the base method of upstream backup compatible with data-parallel CEP, allowing that the windows into which operators partition their input be processed in parallel. We evaluated the proposed extensions through experiments that showed a significant reduction in memory usage and recovery time at the expense of a negligible processing overhead during normal operation.