package recreationaltech.plugin

import nextflow.util.Duration

class K8sNoiseRuntimeEstimator extends K8sRuntimeEstimator {
    // Magnitude of the noise we add
    private long noiseMag

    private HashMap<String, ArrayList<Tuple2<Long, Long>>> data;
    private synchronized Random rnd;

    /**
     * Initialize the estimator with data recorded by K8sRuntimeRecorder
     * @param dataFilePath
     * @param noiseMagnitude magnitude of the noise added to recordings
     */
    K8sNoiseRuntimeEstimator(String dataFilePath, Duration noiseMagnitude) {
        this.data = parseDataFile(dataFilePath)
        this.noiseMag = noiseMagnitude.toMillis()
        this.rnd = new Random()
    }

    /**
     * Initializes the runtime estimator with statically known data.
     * @param data Map from task name to list of recordings, where each recording is a tuple (input-size, runtime-in-ms)
     */
    K8sNoiseRuntimeEstimator(HashMap<String, ArrayList<Tuple2<Long, Long>>> data, Duration noiseMagnitude) {
        this.data = data;
        this.noiseMag = noiseMagnitude.toMillis()
    }

    /**
     * Returns an estimation of the task runtime in milliseconds
     * @param taskName the name of the task
     * @param inputSize the total input size in bytes
     * @return estimated task runtime in milliseconds OR infinity if the task is unknown.
     */
    @Override
    double estimate(String taskName, long inputSize) {
        ArrayList recordings = data.get(taskName)
        for (Tuple2<Long, Long> recording : recordings) {
            if (recording.get(0).longValue() == inputSize) {
                double noise = rnd.nextDouble(-1.0, 1.0) * (double)noiseMag
                long ms = recording.get(1).longValue()
                return (double)ms + noise
            }
        }
        return 0
    }
}