[GitHub] spark pull request #16607: [SPARK-19247][ML] Save large word2vec models

[srowen <gi...@git.apache.org>]

Github user srowen commented on a diff in the pull request:

    https://github.com/apache/spark/pull/16607#discussion_r96307400
  
    --- Diff: mllib/src/main/scala/org/apache/spark/ml/feature/Word2Vec.scala ---
    @@ -320,14 +341,29 @@ object Word2VecModel extends MLReadable[Word2VecModel] {
         private val className = classOf[Word2VecModel].getName
     
         override def load(path: String): Word2VecModel = {
    +      val spark = sparkSession
    +      import spark.implicits._
    +
           val metadata = DefaultParamsReader.loadMetadata(path, sc, className)
    +
           val dataPath = new Path(path, "data").toString
    -      val data = sparkSession.read.parquet(dataPath)
    -        .select("wordIndex", "wordVectors")
    -        .head()
    -      val wordIndex = data.getAs[Map[String, Int]](0)
    -      val wordVectors = data.getAs[Seq[Float]](1).toArray
    -      val oldModel = new feature.Word2VecModel(wordIndex, wordVectors)
    +      val rawData = spark.read.parquet(dataPath)
    +
    +      val oldModel = if (rawData.columns.contains("wordIndex")) {
    --- End diff --
    
    Have a look for `SaveLoadV1_0` elsewhere in the code. I think there's a different standard approach to versioning. I am not so familiar with it but you can see who's written it with git. Maybe @jkbradley ?


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