Streaming Processing Window Types¶
time¶
- Event time
- Arrival time
- Processing time
Window Types¶
- Tumbling Windows
- Flink: A tumbling windows assigner assigns each element to a window of a specified window size. Tumbling windows have a fixed size and do not overlap.
- Spark: Tumbling windows are a series of fixed-sized, non-overlapping and contiguous time intervals. An input can only be bound to a single window.
- Sliding Windows
- Flink: The sliding windows assigner assigns elements to windows of fixed length. Similar to a tumbling windows assigner, the size of the windows is configured by the window size parameter. An additional window slide parameter controls how frequently a sliding window is started. Hence, sliding windows can be overlapping if the slide is smaller than the window size. In this case elements are assigned to multiple windows.
- Spark: Sliding windows are similar to the tumbling windows from the point of being "fixed-sized", but windows can overlap if the duration of slide is smaller than the duration of window, and in this case an input can be bound to the multiple windows.
- Session Windows
- Flink: The session windows assigner groups elements by sessions of activity. Session windows do not overlap and do not have a fixed start and end time
- Spark: Session window has a dynamic size of the window length, depending on the inputs. A session window starts with an input, and expands itself if following input has been received within static or dynamic gap duration.
- Global Windows
