different things • last 5 sec • last 10 events • last 1h every 10 min • last user session Window operators 2 Vasiliki Kalavri | Boston University 2020 object MaxSensorReadings { def main(args: 0)))
 .keyBy(_.id) .timeWindow(Time.minutes(1)) .max("temp")
 } } 3 Example: Window sensor readings Vasiliki Kalavri | Boston University 2020 In the DataStream API, you can use the or IngestionTime Vasiliki Kalavri | Boston University 2020 Window operators can be applied on a keyed or a non-keyed stream: • Window operators on keyed windows are evaluated in parallel • Non-keyed

Processing time • the time of the local clock where an event is being processed • a processing-time window wouldn’t account for game activity while the train is in the tunnel • results depend on the processing and aren’t deterministic • Event time • the time when an event actually happened • an event-time window would give you the extra life • results are deterministic and independent of the processing event-times of non-late data Watermark propagation 12 Vasiliki Kalavri | Boston University 2020 13 Event-time update Vasiliki Kalavri | Boston University 2020 1. Watermarks must be monotonically increasing

key MovingAverage average = averageState.value(); // create a new MovingAverage (with window size 2) if none exists for this key if (average == null) average = new MovingAverage(2); keyBy() .window(<window assigner>) .reduce|aggregate|process(<window function>) stream. .windowAll(<window assigner>) .reduce|aggregate|process(<window function>) ◦TumblingEventTimeWindows s.withGap(Time.minutes(30)) DataStream input = ... input .keyBy(“key”) .window(TumblingEventTimeWindows.of(Time.minutes(1))) .process(new MyWastefulMax()); public static class

DStream. 23 / 79 Window Operations (1/3) ▶ Spark provides a set of transformations that apply to a over a sliding window of data. ▶ A window is defined by two parameters: window length and slide interval interval. ▶ A tumbling window effect can be achieved by making slide interval = window length 24 / 79 Window Operations (2/3) ▶ window(windowLength, slideInterval) • Returns a new DStream which is computed based on windowed batches. ▶ countByWindow(windowLength, slideInterval) • Returns a sliding window count of elements in the stream. ▶ reduceByWindow(func, windowLength, slideInterval) • Returns

Migration / Upgrade 15 End-User License Agreement 16 Chapter 2 - User Interface 23 Main Window 23 Navigation Pane 24 Object Pane 25 Information Pane 27 Chapter 3 - Collaboration 29 Model (Available only in Navicat Premium and Enterprise Edition) 135 About Model 135 Model Window 136 Physical Models 138 Create Physical Models 138 Add Databases / Schemas 139 Add Tables Chapter 10 - Pub/Sub (Available only in Non-Essentials Edition) 161 About Pub/Sub 161 Pub/Sub Window 161 Subscribe Channels 162 Channel Colorings 163 Chapter 11 - Data Migration Tools 164

Migration / Upgrade 15 End-User License Agreement 16 Chapter 2 - User Interface 22 Main Window 22 Navigation Pane 23 Object Pane 24 Information Pane 26 Chapter 3 - Collaboration 28 Model (Available only in Navicat Premium and Enterprise Edition) 132 About Model 132 Model Window 133 Physical Models 135 Create Physical Models 135 Add Databases / Schemas 135 Add Tables Chapter 10 – Pub/Sub (Available only in Non-Essentials Edition) 156 About Pub/Sub 156 Pub/Sub Window 156 Subscribe Channels 157 Channel Colorings 158 Chapter 11 - Data Migration Tools 160

Migration / Upgrade 15 End-User License Agreement 16 Chapter 2 - User Interface 22 Main Window 22 Navigation Pane 23 Object Pane 24 Information Pane 26 Chapter 3 - Collaboration 28 Model (Available only in Navicat Premium and Enterprise Edition) 134 About Model 134 Model Window 135 Physical Models 137 Create Physical Models 137 Add Databases / Schemas 137 Add Tables Chapter 10 - Pub/Sub (Available only in Non-Essentials Edition) 160 About Pub/Sub 160 Pub/Sub Window 160 Subscribe Channels 161 Channel Colorings 162 Chapter 11 - Data Migration Tools 164

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14 3.2.2 Image Window . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16 3.2.3 Dialogs and . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 157 12.1.15 Window Management . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 158 12.1.16 Image . . . . . . . . . . . . . 160 12.1.17 Image Window Appearance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 161 12.1.18 Image Window Title and Statusbar . . . . . . . . . . . . .

526. DBeaver User Guide v.23.1 DBeaver User Guide 23.1. Page 2 of 526. Installation Application Window Overview Views Database Navigator Filter Database Objects Configure Filters Simple and Advanced closed to avoid data loss. Automatic updates DBeaver User Guide 23.1. Page 9 of 526. The DBeaver window contains a menu bar, a toolbar, a shortcut bar, a workspace with one or more editors and views, transactions, as well as reconnecting to and disconnecting from a database. Window menu includes items to manage the look of DBeaver window: show/hide and minimize/maximize views and editors, display bars, split

700. DBeaver User Guide v.23.2 DBeaver User Guide 23.2. Page 2 of 700. Installation Application Window Overview Views Database Navigator Filter Database Objects Configure Filters Simple and Advanced data loss. RPM Package Automatic updates DBeaver User Guide 23.2. Page 11 of 700. The DBeaver window contains a menu bar, a toolbar, a workspace with one or more editors and views, and a status bar: search The menu is for opening and managing its appearance. SQL Editor SQL Editor Application Window Overview Menu Bar DBeaver User Guide 23.2. Page 12 of 700. The menu allows the management of