RDD/DataSet/DataFrame

1.RDD&DataSet

Datasets are similar to RDDs, however, instead of using Java serialization or Kryo they use a specialized Encoder to serialize the objects for processing or transmitting over the network.

2.DataSet&DataFrame

//DataFrame

// Load a text file and interpret each line as a java.lang.String
val ds = sqlContext.read.text("/home/spark/1.6/lines").as[String]
val result = ds
  .flatMap(_.split(" "))               // Split on whitespace
  .filter(_ != "")                     // Filter empty words
  .toDF()                              // Convert to DataFrame to perform aggregation / sorting
  .groupBy($"value")                   // Count number of occurences of each word
  .agg(count("*") as "numOccurances")
  .orderBy($"numOccurances" desc)      // Show most common words first

//DataSet,完全使用scala编程，不要切换到DataFrame

val wordCount = 
  ds.flatMap(_.split(" "))
    .filter(_ != "")
    .groupBy(_.toLowerCase()) // Instead of grouping on a column expression (i.e. $"value") we pass a lambda function
    .count()

DataFrame和DataSet可以相互转化， df.as[ElementType] 这样可以把DataFrame转化为DataSet， ds.toDF() 这样可以把DataSet转化为DataFrame。