I have a graph and am trying to take a random sample of vertices without replacement, using the RDD.sample() method
verts are the vertices in the graph > val verts = graph.vertices and executing this multiple times in a row > verts.sample(false, 10000.toDouble/v1.count.toDouble, > System.currentTimeMillis).count yields different results roughly each time (albeit +/- a small % of the target) why does this happen? Looked at PartionwiseSampledRDD but can't figure it out Also, is there another method/technique to yield the same result each time? My understanding is that grabbing random indices may not be the best use of the RDD model -- View this message in context: http://apache-spark-user-list.1001560.n3.nabble.com/Inconsistent-RDD-Sample-size-tp6197.html Sent from the Apache Spark User List mailing list archive at Nabble.com.
