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https://issues.apache.org/jira/browse/BEAM-3767?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Ismaël Mejía updated BEAM-3767:
-------------------------------
Description:
Apache Beam [1] is a unified and portable programming model for data processing
jobs. The Beam model [2, 3, 4] has rich mechanisms to process endless streams
of events.
Complex Event Processing [5] lets you match patterns of events in streams to
detect important patterns in data and react to them.
Some examples of uses of CEP are fraud detection for example by detecting
unusual behavior (patterns of activity), e.g. network intrusion, suspicious
banking transactions, etc. Also trend detection is another interesting use case
in the context of sensors and IoT.
The goal of this issue is to implement an efficient pattern matching library
inspired by [6] and existing libraries like Apache Flink CEP [7] using the
Apache Beam Java SDK and the Beam style guides [8]. Because of the time
constraints of GSoC we will probably try to cover first simple patterns of the
‘a followed by b followed by c’ kind, and then if there is still time try to
cover more advanced ones e.g. optional, atLeastOne, oneOrMore, etc.
[1] [https://beam.apache.org/]
[2] [https://www.oreilly.com/ideas/the-world-beyond-batch-streaming-101]
[3] [https://www.oreilly.com/ideas/the-world-beyond-batch-streaming-102]
[4]
[https://static.googleusercontent.com/media/research.google.com/en//pubs/archive/43864.pdf]
[5] [https://en.wikipedia.org/wiki/Complex_event_processing]
[6] [https://people.cs.umass.edu/~yanlei/publications/sase-sigmod08.pdf]
[7] [https://ci.apache.org/projects/flink/flink-docs-stable/dev/libs/cep.html]
[8] [https://beam.apache.org/contribute/ptransform-style-guide/]
was:
Apache Beam [1] is a unified and portable programming model for data processing
jobs. The Beam model [2, 3, 4] has rich mechanisms to process endless streams
of events.
Complex Event Processing [5] lets you match patterns of events in streams to
detect important patterns in data and react to them.
Some examples of uses of CEP are fraud detection for example by detecting
unusual behavior (patterns of activity), e.g. network intrusion, suspicious
banking transactions, etc. Also trend detection is another interesting use case
in the context of sensors and IoT.
The goal of this issue is to implement an efficient pattern matching library
inspired by [6] and existing libraries like Apache Flink CEP [7] using the
Apache Beam Java SDK and the Beam style guides [8].
Given the time constraints of GSoC we will probably keep the implementation to
cover first simple patterns of the ‘a followed by b followed by c’ kind and if
the time is enough we will include more advanced ones e.g. optional,
atLeastOne, oneOrMore, etc.
[1] [https://beam.apache.org/]
[2] [https://www.oreilly.com/ideas/the-world-beyond-batch-streaming-101]
[3] [https://www.oreilly.com/ideas/the-world-beyond-batch-streaming-102]
[4]
[https://static.googleusercontent.com/media/research.google.com/en//pubs/archive/43864.pdf]
[5] [https://en.wikipedia.org/wiki/Complex_event_processing]
[6] [https://people.cs.umass.edu/~yanlei/publications/sase-sigmod08.pdf]
[7] [https://ci.apache.org/projects/flink/flink-docs-stable/dev/libs/cep.html]
[8] [https://beam.apache.org/contribute/ptransform-style-guide/]
> A Complex Event Processing (CEP) library/extension for Apache Beam
> ------------------------------------------------------------------
>
> Key: BEAM-3767
> URL: https://issues.apache.org/jira/browse/BEAM-3767
> Project: Beam
> Issue Type: New Feature
> Components: sdk-ideas
> Reporter: Ismaël Mejía
> Assignee: Ismaël Mejía
> Priority: Minor
> Labels: gsoc, gsoc2018, mentor
>
> Apache Beam [1] is a unified and portable programming model for data
> processing jobs. The Beam model [2, 3, 4] has rich mechanisms to process
> endless streams of events.
> Complex Event Processing [5] lets you match patterns of events in streams to
> detect important patterns in data and react to them.
> Some examples of uses of CEP are fraud detection for example by detecting
> unusual behavior (patterns of activity), e.g. network intrusion, suspicious
> banking transactions, etc. Also trend detection is another interesting use
> case in the context of sensors and IoT.
> The goal of this issue is to implement an efficient pattern matching library
> inspired by [6] and existing libraries like Apache Flink CEP [7] using the
> Apache Beam Java SDK and the Beam style guides [8]. Because of the time
> constraints of GSoC we will probably try to cover first simple patterns of
> the ‘a followed by b followed by c’ kind, and then if there is still time try
> to cover more advanced ones e.g. optional, atLeastOne, oneOrMore, etc.
> [1] [https://beam.apache.org/]
> [2] [https://www.oreilly.com/ideas/the-world-beyond-batch-streaming-101]
> [3] [https://www.oreilly.com/ideas/the-world-beyond-batch-streaming-102]
> [4]
> [https://static.googleusercontent.com/media/research.google.com/en//pubs/archive/43864.pdf]
> [5] [https://en.wikipedia.org/wiki/Complex_event_processing]
> [6] [https://people.cs.umass.edu/~yanlei/publications/sase-sigmod08.pdf]
> [7]
> [https://ci.apache.org/projects/flink/flink-docs-stable/dev/libs/cep.html]
> [8] [https://beam.apache.org/contribute/ptransform-style-guide/]
>
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