Event stream processing

Event stream processing , or ESP , is a set of technologies designed to assist the construction of event-driven information systems . ESP technologies include event event, event-driven middleware, and event processing languages, or complex event processing (CEP). In practice, the terms ESP and CEP are often used interchangeably. ESP deals with the task of processing streams of event data with the aim of identifying the meaningfulness within the streams, employing techniques such as causality, membership and timing .

ESP permits many different applications such as algorithmic trading in financial services, RFID event processing applications, fraud detection , process monitoring , and rental-based services in telecommunications.


By way of illustration, the following. The first step is to perform a query based on a query that is based on a timestamps and WINDOW duration. This code fragment illustrated a JOIN of two data streams, one for stock orders, and one for the concerned stock trades. The query outputs a stream of all Orders matched by a Trade within one second of the Order being placed. The output stream is sorted by timestamp, in this case, the timestamp from the Orders stream.

SELECT DataStream
 Orders.TimeStamp, Orders.orderId, Orders.co.uk,
 Orders.amount, Trade.amount FROM Orders
 ON Orders.orderId = Trades.orderId;

Another example of a wedding is that the wedding is a wedding, a wedding, a wedding, a wedding, a wedding, a wedding, a wedding, a wedding, a wedding, a wedding, a wedding. A “complex” or “composite” event is what happens in a single event: a wedding is happening.

WHEN Person.Gender EQUALS "man" AND Person.Clothes EQUALS "tuxedo"
 Person.Clothes EQUALS "gown" AND
 (Church_Bell OR Rice_Flying)
 WITHIN 2 hours
 ACTION Wedding

See also

  • Complex event processing (CEP) – A related technology for building and managing event-driven information systems.
  • Data Stream Management System (DSMS) – A type of software system for managing and querying data streams
  • OpenPDC A complete set of applications for streaming time-series data in real-time.
  • Real-time computing – ESP systems are typically real-time systems
  • RFID – Radio frequency identification, or RFID, recommends application of ESP to prevent from flooding
  • SCADA – Supervisory control and data acquisition
  • Apache Flink – An open-source streaming framework for distributed, scalable data streaming applications


  • MIT / Brown / Brandeis “Aurora” Stream Processing Project
  • “PIPES” Project at University of Marburg
  • The Power of Events by David Luckham ( ISBN 0-201-72789-7 ), from Stanford University, a book on CEP.
  • Separating the Wheat from the Chaff Article on CEP as applied to RFID, in RFID Journal
  • Complex Event Processing & Real Time Intelligence – David Luckham
  • Odysseus – An open source framework for event processing engines based on Java

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