Hawkular Data Mining 0.1.0.Final Released

A blog post by Pavol Loffay

datamining | metrics

I am happy to announce the first release 0.1.0.Final of the Hawkular Data Mining project. It contains several time series models and utility classes for time series modelling.

Time series models

  • Simple exponential smoothing

  • Double exponential smoothing (Holt’s linear trend)

  • Seasonal triple exponential smoothing (Holt Winters)

  • Simple moving average (Weighted moving average)

  • AutomaticForecaster - which automatically selects the best model

  • Parameters of all models are estimated using maximum likelihood estimation and models are designed for online learning

Time series manipulation & Statistics

  • Augmented Dickey-Fuller test

  • Autocorrelation function (ACF)

  • Time series decomposition

  • Time series lagging

  • Time series differencing

  • Automatic period identification

Integration into Hawkular

The integration into Hawkular can be found in datamining branch in the main Hawkular repository. Predictive charts are located in Explorer tab. Predictions can be enabled for any number of steps in the future for any metric being collected. Prediction engine automatically selects the best model for given time series. Currently it selects from simple, double and triple exponential smoothing models. In the following charts predictions produced by these models are showed.

Figure 1. Model Triple exponential smoothing
Figure 2. Model Double exponential smoothing
Figure 3. Model Simple exponential smoothing

Note that currently there is an issue with querying historical data from Metrics due to authentication issues. However Data Mining still receives metrics from bus so it is important to enable predictions as soon as possible and wait for some time to collect data (or increase collection interval). This will be fixed in the next versions.

Next Steps

  • Fix querying historical metric data

  • Prediction intervals


Thanks goes to Jiri Kremser and UI team for helping with predictive charts.

Published by Pavol Loffay on 21 April 2016


© 2016 | Hawkular is released under Apache License v2.0