Issues with Max/Avg Per Property measure

[LorenzBuehmann]

SANSA-RDF/sansa-rdf-spark/src/main/scala/net/sansa_stack/rdf/spark/stats/RDFStatistics.scala

Lines 309 to 316 in 4b1e3ab

	def MaxPerProperty(triples: RDD[Triple]): (Triple, Int) = {
	val max_per_property_def = triples.filter(triple => (triple.getObject.toString().equals(XSD.xint)
	| triple.getObject.toString().equals(XSD.xfloat) | triple.getObject.toString().equals(XSD.dateTime)))
	val properties_fr = max_per_property_def.map(f => (f, 1)).reduceByKey(_ + _)
	val ordered = properties_fr.takeOrdered(1)(Ordering[Int].reverse.on(_._2))
	ordered.maxBy(_._2)
	}

does not what it should do:

1. the filter does filter for triples with an object having a URI xsd:int ,etc. - this is clearly wrong, it has to be filtered by the datatype of objects being a literal
2. right now, it looks more like computing a histogram, but still not on the property but on a whole triple. This in fact is always 1 for each triple in a single RDF graph
3. result of ordering is retrieved to driver, thus, no RDD anymore?
4. takeOrdered(1) returns exactly 1 element from the RDD w.r.t. the ordering, thus, you'll get only one pair with the highest value as second element among all pairs independently of the property
5. ordering is hard-coded for Int only, thus, only xsd:int would be covered - what about xsd:float and xsd:dateTime values?
6. (Triple, Int) is returned, but it should be (Node, Scalatype_of_Literal) - how do you want to do this generic? I guess we should return RDD[(Node, Node)]

the same holds for Avg Per Property measure.

In addition, what would be the avg. of some xsd:dateTime values?