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  • pdf文档 Course introduction - CS 591 K1: Data Stream Processing and Analytics Spring 2020

    The app allows transfers of up to €1000 and so the thief makes transfers of €1000 to a "fake account" until either you're out of money or the activity is detected. • Features to detect fraudulent activity transactions. • Whether money was sent to this recipient account for the first time in the past 24 hours (in other words, to an “unknown” recipient account). Read more: https://www.ververica.com/blog/rea
    0 码力 | 34 页 | 2.53 MB | 1 年前
    3
  • pdf文档 PyFlink 1.15 Documentation

    table import EnvironmentSettings, TableEnvironment env_settings = EnvironmentSettings.in_batch_mode() table_env = TableEnvironment.create(env_settings) table_env [1]: [2]: # Create a streaming TableEnvironment env_settings = EnvironmentSettings.in_streaming_mode() table_env = TableEnvironment.create(env_settings) table_env [2]: settings.py", line 267, in in_streaming_mode get_gateway().jvm.EnvironmentSettings.inStreamingMode()) File
    0 码力 | 36 页 | 266.77 KB | 1 年前
    3
  • pdf文档 PyFlink 1.16 Documentation

    table import EnvironmentSettings, TableEnvironment env_settings = EnvironmentSettings.in_batch_mode() table_env = TableEnvironment.create(env_settings) table_env [1]: [2]: # Create a streaming TableEnvironment env_settings = EnvironmentSettings.in_streaming_mode() table_env = TableEnvironment.create(env_settings) table_env [2]: settings.py", line 267, in in_streaming_mode get_gateway().jvm.EnvironmentSettings.inStreamingMode()) File
    0 码力 | 36 页 | 266.80 KB | 1 年前
    3
  • pdf文档 Notions of time and progress - CS 591 K1: Data Stream Processing and Analytics Spring 2020

    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 speed and
    0 码力 | 22 页 | 2.22 MB | 1 年前
    3
  • pdf文档 Flow control and load shedding - CS 591 K1: Data Stream Processing and Analytics Spring 2020

    Kalavri | Boston University 2020 Which tuples to drop? • Relevant when load shedding takes into account the semantic importance of tuples with respect to results quality • Drop at random: • Insert
    0 码力 | 43 页 | 2.42 MB | 1 年前
    3
  • pdf文档 Stream processing fundamentals - CS 591 K1: Data Stream Processing and Analytics Spring 2020

    the development of streaming algorithms With limited practical value in distributed, real-world settings Vasiliki Kalavri | Boston University 2020 Cash-Register Model: In this model, multiple updates
    0 码力 | 45 页 | 1.22 MB | 1 年前
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