streaming execution plan. ▶ 2. Specify triggers to control when to update the results. • Each time a trigger fires, Spark checks for new data (new row in the input table), and incrementally updates the result streaming execution plan. ▶ 2. Specify triggers to control when to update the results. • Each time a trigger fires, Spark checks for new data (new row in the input table), and incrementally updates the result streaming execution plan. ▶ 2. Specify triggers to control when to update the results. • Each time a trigger fires, Spark checks for new data (new row in the input table), and incrementally updates the result

Time windows have a start and an end timestamp. • All built-in window assigners provide a default trigger that triggers the evaluation of a window once the (processing or event) time passes the end of window contents Vasiliki Kalavri | Boston University 2020 input stream window assigner ... trigger evictor evaluation function result stream Custom windows 20 • Describe each component Vasiliki suitable: • they provide access to record timestamps and watermarks • they can register timers that trigger at a specific time in the future ProcessFunction, KeyedProcessFunction, CoProcessFunction, ProcessJoinFunction

assume that no further events with timestamp less than T will be received. • It can then either trigger computation or order received events. 15 Evaluation of event-time windows Vasiliki Kalavri | Boston

Accessing Data on Table PyFlink Table is lazily evaluated and simply selecting a column does not trigger the computation but it returns a Column Expression instance. [15]: from pyflink.table.expressions

Accessing Data on Table PyFlink Table is lazily evaluated and simply selecting a column does not trigger the computation but it returns a Column Expression instance. [15]: from pyflink.table.expressions