Apache Spark的Some过滤器

Question

I have the following leftOuterJoin operation:

val totalsAndProds = transByProd.leftOuterJoin(products)
println(totalsAndProds.first())

which prints:

(19,([Ljava.lang.String;@261ea657,Some([Ljava.lang.String;@25290bca)))

then I try to apply the following filter operations:

totalsAndProds.filter(x => x._2 == Some).first

but it fails with the following exception:

Exception in thread "main" java.lang.UnsupportedOperationException: empty collection
    at org.apache.spark.rdd.RDD$$anonfun$first$1.apply(RDD.scala:1380)
    at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
    at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112)
    at org.apache.spark.rdd.RDD.withScope(RDD.scala:363)
    at org.apache.spark.rdd.RDD.first(RDD.scala:1377)
    at com.example.spark.WordCount$.main(WordCount.scala:98)
    at com.example.spark.WordCount.main(WordCount.scala)

what am I doing wrong and the filter operation returns the empty collection?

Answer 1

Your predicate is wrong:

1. Your RDD type is (Int, (Array[String], Option[Array[String]])) , therefore _._2 is of type (Array[String], Option[Array[String]]) , not Option[Array[String]]
2. You do not check Option types using equals.

Try

totalsAndProds.filter{ case (_, (_, s)) => s.isDefined }

Example below:

scala> val rdd = sc.parallelize(List((19, (Array("a"), Some(Array("a"))))))
rdd: org.apache.spark.rdd.RDD[(Int, (Array[String], Some[Array[String]]))] = ParallelCollectionRDD[0] at parallelize at <console>:24

scala> rdd.filter{ case (_, (_, s)) => s.isDefined }
res0: org.apache.spark.rdd.RDD[(Int, (Array[String], Some[Array[String]]))] = MapPartitionsRDD[1] at filter at <console>:27

scala> rdd.filter{ case (_, (_, s)) => s.isDefined }.collect
res1: Array[(Int, (Array[String], Some[Array[String]]))] = Array((19,(Array(a),Some([Ljava.lang.String;@5307fee))))