Time Series in Spark (Scala)
The company is working on physiological time-series signals ( eg. ECG, EEG ). The asked to do DTW, clustering and classification for Time Series data. Since, time-series signals like ECG or EEG are continuous in nature, there we need large scale distributed and parallel processing using Apache Spark.
We have created the algorithm for calculating the distance between pairs of Time Series in parallel way by using next methods:
- Naive DTW algorithm
- Locality Contraint DTW algorithm
- LB_Keogh DTW Algorithm