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Patrick Wendell resolved SPARK-1212. ------------------------------------ Resolution: Fixed > Support sparse data in MLlib > ---------------------------- > > Key: SPARK-1212 > URL: https://issues.apache.org/jira/browse/SPARK-1212 > Project: Spark > Issue Type: Improvement > Components: MLlib > Affects Versions: 0.9.0 > Reporter: Xiangrui Meng > Assignee: Xiangrui Meng > Priority: Blocker > Fix For: 1.0.0 > > > MLlib's NaiveBayes, SGD, and KMeans accept RDD[LabeledPoint] for training and > RDD[Array[Double]] for prediction, where LabeledPoint is a wrapper of > (Double, Array[Double]). Using Array[Double] could have good performance, but > sparse data appears quite often in practice. So I created this JIRA to > discuss the plan of adding sparse data support to MLlib and track its > progress. > The goal is to support sparse data for training and prediction in all > existing algorithms in MLlib: > * Gradient Descent > * K-Means > * Naive Bayes > Previous discussions and pull requests: > * https://github.com/mesos/spark/pull/736 -- This message was sent by Atlassian JIRA (v6.2#6252)