Apply a function into grouped dataframe using Scala Spark - dataframe

Question

I'm trying to do DBSCAN in each group of latitudes and longitudes from users. The implementation of this clustering algorithm was done by irvingc here. I bumped up all dependencies to make the code work properly in my env.
Describing the sistuation: I have a Dataframe which is composed by events from user, each event has an id, a lat, and a long, you can see the columns by this case class. By that, I transform the dataframe to dataset to use the groupbykey and mapgroups methods to apply the function to the grouped data. However, the DBSCAN I'm using receive an RDD[linalg.Vector], so I have to transform the group into Vector of lat/lon, and this transformation gives the error SPARK-28702. Can you give some advice how to handle this issue?
case class StayDataset(objectID: Long, latitude: Double, longitude: Double, timeStart: Long, timeEnd: Long)
var dfs: Array[DataFrame] = Array()
val s = dataset.groupByKey(k => k.objectID).mapGroups{
case(k, iter) => {
POIDetection.groupStayPointsFromUser(k, iter, dataset.sparkSession)
dfs = dfs ++ Array(df)
k
}
}
def groupStayPointsFromUser(k: Long, dataset: Iterator[StayDataset], spark: SparkSession): DataFrame = {
val points = dataset.map(row => Vectors.dense(Array(row.latitude, row.longitude))).toSeq
val rddVector = spark.sparkContext.parallelize(points)
val size = points.length
val model = DBSCAN.train(rddVector, eps = 20, minPoints = (size * 0.18).toInt, maxPointsPerPartition = (size / 4).toInt)
val pointRDD = new PointRDD(model.labeledPoints.map(p => {
val point = POIDetection.geoFactory.createPoint(new Coordinate(p.x, p.y))
point.setUserData(p.cluster.toString())
point
}))
val df = Adapter.toDf(pointRDD, Seq("cluster"), spark)
.select(col("cluster").cast("long"), col("geometry"))
df
}
I think this problem arises when we want to apply a KNN in a grouped data. How to do that?

Answer 1

I don't understand what you want to achieve but first, you need to create a RDD[linalg.Vector], I suppose that you have the dataset of StayDataset already, to retrieve the RDDs, you need to transform the Dataset of StayDataset to linalg.Vector
val dsVector = dataset.transform[linalg.Vector](rec => linalg.Vectors.dense(rec.latitude, rec.longitude))
and then you retrieve the rdd[linalg.Vector]:
val rdd = dsVector.rdd
and you pass the rdd to your DBSCAN:
DBSCAN.train(rdd, ...)
These are necessary for your to get the rdd to do the train.
I think you also need to do some aggregation beforehand. If it is true, you need to manipulate on the dataset you have