How to use if to filter in a map function in scala?

Question

I've got a hadoopFiles object which is generated from sc.newAPIHadoopFile.

scala> hadoopFiles
res1: org.apache.spark.rdd.RDD[(org.apache.hadoop.io.LongWritable, org.apache.hadoop.io.Text)] = UnionRDD[64] at union at <console>:24

I intend to iterate through all the lines in hadoopFiles with operation and filter on it, In which, a if check is applied and will throw an exception:

scala> val rowRDD = hadoopFiles.map(line =>
     |           line._2.toString.split("\\^") map {
     |             field => {
     |               var pair = field.split("=", 2)
     |               if(pair.length == 2)
     |                 (pair(0) -> pair(1))
     |             }
     |           } toMap
     |         ).map(kvs => Row(kvs("uuid"), kvs("ip"), kvs("plt").trim))
<console>:33: error: Cannot prove that Any <:< (T, U).
                 } toMap
                   ^

However, if I remove the if(pair.length == 2) part, it will works fine:

scala>     val rowRDD = hadoopFiles.map(line =>
     |           line._2.toString.split("\\^") map {
     |             field => {
     |               var pair = field.split("=", 2)
     |               (pair(0) -> pair(1))
     |             }
     |           } toMap
     |         ).map(kvs => Row(kvs("uuid"), kvs("ip"), kvs("plt").trim))
warning: there was one feature warning; re-run with -feature for details
rowRDD: org.apache.spark.rdd.RDD[org.apache.spark.sql.catalyst.expressions.Row] = MappedRDD[66] at map at <console>:33

Could anyone tell me the reason for this phenomenon, and show me the correct way to apply the if statement. Thanks a lot!

P.S. We could use this simplified example to test:

"1=a^2=b^3".split("\\^") map {
            field => {
              var pair = field.split("=", 2)
              if(pair.length == 2)
                pair(0) -> pair(1)
              else
                return
            }
          } toMap

What if pair.length != 2. You have provide something for that case too. — sarveshseri
– sarveshseri, Commented Feb 4, 2015 at 1:14
Just filter it out. I only look for key-value pairs which is exactly composed of 2 parts. @SarveshKumarSingh — Judking
– Judking, Commented Feb 4, 2015 at 1:21

Kim Stebel · Accepted Answer · 2015-02-04 01:19:45Z

3

To map over a collection and only keep some of the mapped elements, you can use flatMap. flatMap takes a function that returns a collection, e.g. instance an Option. Now the if expression needs to have an else part that returns an empty Option, i.e. None.

scala> val rowRDD = hadoopFiles.map(line =>
     |           line._2.toString.split("\\^") flatMap {
     |             field => {
     |               var pair = field.split("=", 2)
     |               if (pair.length == 2)
     |                 Some(pair(0) -> pair(1))
     |               else
     |                 None
     |             }
     |           } toMap
     |         ).map(kvs => Row(kvs("uuid"), kvs("ip"), kvs("plt").trim))

edited Feb 4, 2015 at 1:19

answered Feb 4, 2015 at 1:12

Kim Stebel

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4 Comments

Judking Over a year ago

That is to say, if my line looks like '1=a^2=b^3', the above flatMap function will just return (1->a) and (2->b) ? I'm new to scala as well as Spark, what does the Some and None keyword serves here interacting with flatMap? Why not the map function?

Judking Over a year ago

Well, it throws another error: error: value flatmap is not a member of Array[String]

Kim Stebel Over a year ago

Some and None aren't keywords. They are subclasses of Option, which is a container that can have zero elements(None) or one element (Some).

Judking Over a year ago

When revising to flatMap, it is just what I expected. Thanks for your detailed explanation :]

user5102379 · Accepted Answer · 2015-02-04 08:33:49Z

You can use collect:

val res = "1=a^2=b^3".split("\\^") collect {
  _.split("=", 2) match {
    case Array(a, b) => a -> b
  }
} toMap

println(res) // Map(1 -> a, 2 -> b)

In your particular case the following happens:

case class Row(uuid: String, ip: String, plt: String)
val hadoopFiles = List(("", "uuid=a^ip=b^plt"))

val rowRDD = hadoopFiles.map(line =>
  line._2.toString.split("\\^") map {
    field =>
      {
        var pair = field.split("=", 2)
        val res = if (pair.length == 2)
          (pair(0) -> pair(1))
        res  // res: Any (common super class for (String, String)
             // which is Tuple2 and Unit (result for case when 
             // pair.length != 2)
      }
  } /* <<< returns Array[Any] */ /*toMap*/ ) 
  //.map(kvs => Row(kvs("uuid"), kvs("ip"), kvs("plt").trim))

The result of inner map is Any and map yields Array[Any]. If you look at toMap definition you will see:

  def toMap[T, U](implicit ev: A <:< (T, U)): immutable.Map[T, U] = {
    val b = immutable.Map.newBuilder[T, U]
    for (x <- self)
      b += x // <<< implicit conversion from each `x` of class `A` in `self`
             // to (T, U) because we have `implicit ev: A <:< (T, U)`
    b.result()
  }

For your Array[Any] there is no implicit conversion from Any to (T, U) in current context. Because of this your code fails. If you add else alternative:

  val rowRDD = hadoopFiles.map(line =>
    (line._2.toString.split("\\^") map {
      field =>
        {
          var pair = field.split("=", 2)
          val res = if (pair.length == 2)
            (pair(0) -> pair(1))
          else ("" -> "") // dummy, just for demo
          res // res: (String, String)
        }
    } toMap) withDefaultValue ("") 
           /*withDefaultValue just to avoid Exception for this demo*/ )
    .map(kvs => Row(kvs("uuid"), kvs("ip"), kvs("plt").trim))

  println(rowRDD) // List(Row(a,b,))

Here your result will be Array[(String, String)] and there is an implicit conversion from (String, String) to (T, U). So the code compiles and works.

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