Abstract: A system time window corresponding to data to be processed is determined based on a data time of the data to be processed when the data to be processed is received in a current system time window. If the data time is within a range of the current system time window, data to be processed having a system receiving time earlier than the synchronization time point is stored, and data to be processed having a system receiving time later than the synchronization time point is immediately processed. If the data time is within a range of a previous system time window, data to be processed having a system receiving time earlier than the closing time point is immediately processed, and data to be processed having a system receiving time later than the closing time point is discarded.

Abstract: An exception monitoring and alarming method and apparatus are provided. The method comprises: recording alarm information for a to-be-processed alarm item; determining whether the alarm information for the to-be-processed alarm item meets a fatigue condition; controlling the to-be-processed alarm item to enter a fatigue period when the alarm information for the to-be-processed alarm item meets the fatigue condition; and conducting alarm control on the to-be-processed alarm item in the fatigue period to reduce a number of alarms for the to-be-processed alarm item.

Abstract: The present disclosure discloses data aggregation methods and apparatuses. According to some embodiments of the present disclosure, when massive service data stored in a cloud environment needs to be aggregated, a data aggregation server first receives service data sent by a service data server. It can be detected in real time whether a time stamp carried in the service data is greater than a time stamp carried in service data that is received by the data aggregation server at a previous time. If so, data aggregation can be performed on service data having a time stamp that is the same as the time stamp carried in the service data that is received by the data aggregation server at the previous time. That way, precision and efficiency of data aggregation can be improved. Further, the real-time performance of data aggregation can be ensured.

Abstract: Embodiments of the disclosure provide methods and systems for monitoring client applications. The method can include: monitoring an event tracking log by calling an event tracking software development kit (SDK), wherein the event tracking log is created by a client application according to an event tracking attribute, and the client application predefines the event tracking attribute by calling an application programming interface (API) of the event tracking SDK; extracting event tracking information from the event tracking log; merging the event tracking information according to at least one dimension; and presenting the merged event tracking information according to a query request.

Abstract: A method for processing data after a restart of a node comprises: acquiring, by a processing node, a time point of current legacy data with the longest caching time in a distributed message queue after a restart of the processing node has completed; determining a recovery cycle according to a current time point and the time point of the legacy data; and processing the legacy data and newly added data in the distributed message queue within the recovery cycle. Thus, an interruption of data processing resulting from a restart may be avoided, an impact on the user's feeling may be eliminated, and user experience is improved.

Abstract: A data processing method is disclosed. A system time window corresponding to data to be processed is determined based on a data time of the data to be processed when the data to be processed is received in a current system time window. If the data time is within a range of the current system time window, data to be processed having a system receiving time earlier than the synchronization time point is stored, and data to be processed having a system receiving time later than the synchronization time point is immediately processed. If the data time is within a range of a previous system time window, data to be processed having a system receiving time earlier than the closing time point is immediately, and data to be processed having a system receiving time later than the closing time point is discarded.