Writing an RDD to multiple files in PySpark

Question

I have an rdd which contains key value pairs. There are just 3 keys, and I would like to write all the elements for a given key to a textfile. Currently I am doing this in 3 passes, but I wanted to see if I could do it in one pass.

Here is what I have so far:

# I have an rdd (called my_rdd) such that a record is a key value pair, e.g.: 
# ('data_set_1','value1,value2,value3,...,value100')

my_rdd.cache()
my_keys = ['data_set_1','data_set_2','data_set_3']
for key in my_keys:
    my_rdd.filter(lambda l: l[0] == key).map(lambda l: l[1]).saveAsTextFile(my_path+'/'+key)

this works, however caching it and iterating through three times can be a lengthy process. I am wondering if there is any way to simultaneously write all three files?

Answer 1

Alternative approach by using customized Partitioner(which partition your dataset before writing to output file, compared to the approach provided by Def_Os)

For Example:
RDD[(K, W)].partitionBy(partitioner: Partitioner)

class CustmozedPartitioner extends Partitioner {

  override def numPartitions: Int = 4

  override def getPartition(key: Any): Int = {
    key match {
      case "data_set_1" => 0
      case "data_set_2" => 1
      case "data_set_3" => 2
      case _ => 3
    } 
  }
}