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Sliding window analytics

Sliding windows are useful to gain analytic insights over a period whereby some of the events contribute to the insight, these windows are either time-based or a fixed count of events.

This example provides a demonstration of the available OOTB aggregate functions Joule provides that work with sliding windows.
Use case configuration
File: app-slidingWindowAnalytics.env
SOURCEFILE=${PWD}/conf/sources/stockQuoteStream.yaml
ENGINEFILE=${PWD}/conf/usecases/slidingWindowAnalytics.yaml
PUBLISHFILE=${PWD}/conf/publishers/fileStandardAnalytics.yaml
Pipeline configuration
This pipeline will compute a sliding window function on a single event type based on symbol CVCO
stream:
  name: standardQuoteAnalyticsStream
  enabled: true
  validFrom: 2020-01-01
  validTo: 2025-12-31
  eventTimeType: EVENT_TIME
  sources: [ nasdaq_quotes_stream ]
​
  processing unit:
    pipeline:
      - time window:
          emitting type: slidingQuoteAnalytics
          aggregate functions:
            FIRST: [ask]
            LAST: [ ask ]
            MIN: [ ask ]
            MAX: [ bid ]
            SUM: [ volume ]
            MEAN: [ volatility ]
            HARMONIC_MEAN: [ volatility ]
            VARIANCE: [ volatility ]
            STDEV: [ volatility ]
          policy:
            type: slidingTime
            slide: 500
            window size: 2500
​
  select:
    expression: "symbol, ask_FIRST, ask_LAST, ask_MIN, bid_MAX, volume_SUM, volatility_MEAN, volatility_HARMONIC_MEAN, volatility_VARIANCE, volatility_STDEV"
​
  group by:
    - symbol
​

Tumbling window analytics

User defined analytics

Last modified 9mo ago