In Stream Analytics, all data stream events have a timestamp associated with them. As all events are temporal in nature and timing of arrival of the event is how the timestamp is assigned, considerations exists for both the tolerance of out of order events and the late arrival of events to the Stream Analytics job. Contributors to Late Arrival and Out of Order event vary but generally are one or more of the following:
•Producers of the events have clock skews. This is common when producers are from different machines, so they have different clocks.
•Network delay from the producers sending the events to Event Hub.
•Clock skews between Event Hub partitions. This is also a factor because we first sort events from all Event Hub partitions by event enqueue time, and then examine the disordness.
Read about Azure Stream Analytics Time Skew Policies here
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