A fault-tolerant strategy based on cache queue was proposed, aiming at the problem of low efficiency of stream processing job recovery due to global rollback after Flink task fails. In the job, the operator with the longest recovery time is taken as the key operator, the processed data are stored in the buffer queue, and active backup is performed for it. The backup operator will also accept the data from the upstream to reach the the effect that the job can be restored instantaneously after a failure. In order to solve the additional consumption caused by active backup, a data filtering algorithm was proposed. The backup operator will retrieve the current data from the cache component before processing the data each time to determine whether to continue processing. When the Flink operator itself fails, it will use the buffer queue in the strategy and Flink’s JobManager to send the data information at the time of the failure to the backup operator. When the backup operator receives the data, it will realize the effect of instant recovery. The strategy was evaluated on four evaluation indicators. Compared with the failure recovery mode of Flink1.8, the proposed strategy had a significant improvement in Flink task failure recovery. The recovery efficiency was increased by 56.3%, 51.3%, 46.2% and 45.8% under failure times of 1, 2, 3 and 4 separately. And the proposed strategy brings only a very small price in terms of processing delay, CPU utilization and memory usage.