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D2IA: Data-driven Interval Analytics

D2IA is a Flink library that uses Flink CEP to declaratively define event intervals and reason about their relationships using Allen's interval algebra.

We provide three operators:

  • Homogeneous (HoIE) interval generator: this takes as input a single source stream, a condition, a number of occurrences or a time window,
  • Heterogeneous (HeIE) interval generator: this takes as input at least two source streams. Similarly, it takes a condition, or a time window,
  • Interval operator: this always finding matches between pairs of interval events or an interval event and an instantaneous

A condition can be either absolute, i.e., stateless or relative, i.e., stateful. An absolute condition, refers to properties of candidate events solely to determine their membership to the interval. A relative condition, on the other hand, compares the candidate event to expressions evaluated over the events added to the interval so far.

Example usage

You can run the test class on path ee.ut.cs.dsg.example.linearroad.LinearRoadRunner with the following parameters

--source [kafka|file] --jobType [ThresholdAbsolute|ThresholdRelative|Delta|Aggregate] --fileName [path to file] --kafka [comma separated list of [ip:port] for the bootstrap servers] --topic [kafka topic to read linear road data from]

This runs a predefined group of interval specifications against the linar road data set.

A data set containing about 24M records of linear road data can be found here

Parameters description

  1. Source: Identifies the source type, either a path or url to a csv file or, Kafka to point to the source of the data,
  2. JobType: you can choose from: ThresholdAbsolute, ThresholdRelative, Delta or Aggregate. These are predefined intervals created by the HoIE. To understand the concepts behind these different types of data driven intervals, you may want to check this paper,
  3. fileName: is the path to a csv file on the form VID,SPEED,ACCEL,XWay,Lane,Dir,Seg,Pos,T1,T2. An example file was ponited to above.
  4. Kafka: this is a comma separated list of ip:port for the bootstrap servers for Kafka,
  5. Topic: is the topic name from which the data on the same format as in point 3 will be pulled.