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Prepare data: define intervals and its lenght
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// first find jumps to define the continuous periods of data | |
Long firstElement = times.first(); | |
Long lastElement = times.sortBy(time -> time, false, 1).first(); | |
JavaRDD<Long> firstRDD = timestamps.filter(record -> record > firstElement); | |
JavaRDD<Long> secondRDD = timestamps.filter(record -> record < lastElement); | |
// compute the difference between each timestamp | |
// and then if the difference is greater than 100 000 000, it must be different periods of recording, so we have a jump | |
// I have chosen 100 000 000 (the values are recording every 50 000 000 and around 0.05% are spaced by more than 100 000 000). | |
JavaPairRDD<Long, Long> jumps = firstRDD.zip(secondRDD) | |
.mapToPair(pair -> new Tuple2<>(new Long[]{pair._1, pair._2}, pair._1 - pair._2)) | |
.filter(pair -> pair._2 > 100000000) | |
.mapToPair(pair -> new Tuple2<>(pair._1[1], pair._1[0])); | |
// Now define the intervals | |
List<Long> flatten = tsJump.flatMap(pair -> Arrays.asList(pair._1, pair._2)) | |
.sortBy(t -> t, true, 1) | |
.collect(); | |
int size = flatten.size(); // always even | |
List<Long[]> results = new ArrayList<>(); | |
// init condition | |
results.add(new Long[]{firstElement, flatten.get(0), (long) Math.round((flatten.get(0) - firstElement) / windows)}); | |
for (int i = 1; i < size - 1; i+=2) { | |
results.add(new Long[]{flatten.get(i), flatten.get(i + 1), (long) Math.round((flatten.get(i + 1) - flatten.get(i)) / windows)}); | |
} | |
// end condition | |
results.add(new Long[]{flatten.get(size - 1), lastElement, (long) Math.round((lastElement - flatten.get(size - 1)) / windows)}); | |
return results; |
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