Github user srowen commented on a diff in the pull request: https://github.com/apache/spark/pull/14335#discussion_r71990246 --- Diff: mllib/src/main/scala/org/apache/spark/mllib/clustering/LDAOptimizer.scala --- @@ -472,12 +473,13 @@ final class OnlineLDAOptimizer extends LDAOptimizer { gammaPart = gammad :: gammaPart } Iterator((stat, gammaPart)) - } + }.persist(StorageLevel.MEMORY_AND_DISK) val statsSum: BDM[Double] = stats.map(_._1).treeAggregate(BDM.zeros[Double](k, vocabSize))( _ += _, _ += _) - expElogbetaBc.unpersist() val gammat: BDM[Double] = breeze.linalg.DenseMatrix.vertcat( stats.map(_._2).flatMap(list => list).collect().map(_.toDenseMatrix): _*) --- End diff -- `.map(_._1)` above should be `.keys`; `.map(_._2)` can be `.values`; `list => list` can be `identity`. I wonder why this collects and then turns things into a dense matrix; can that be done non-locally?
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