I would also like to know if there is a way to predict a single vector with the new spark.ml API, although in my case it's because I want to do this within a map() to avoid calling groupByKey() after a flatMap():
*Current code (pyspark):* % Given 'model', 'rdd', and a function 'split_element' that splits an element of the RDD into a list of elements (and assuming % each element has both a value and a key so that groupByKey will work to merge them later) split_rdd = rdd.flatMap(split_element) split_results = model.transform(split_rdd.toDF()).rdd return split_results.groupByKey() *Desired code:* split_rdd = rdd.map(split_element) split_results = split_rdd.map(lambda elem_list: [model.transformOne(elem) for elem in elem_list]) return split_results -- View this message in context: http://apache-spark-user-list.1001560.n3.nabble.com/Mlib-RandomForest-Spark-2-0-predict-a-single-vector-tp27447p27931.html Sent from the Apache Spark User List mailing list archive at Nabble.com. --------------------------------------------------------------------- To unsubscribe e-mail: user-unsubscr...@spark.apache.org