Spark-Scala: Map the first element of list with every other element of list when lists are of varyin-CodePudding

I have dataset of the following type in a textile:

1004,bb5469c5|2021-09-19 01:25:30,4f0d-bb6f-43cf552b9bc6|2021-09-25 05:12:32,1954f0f|2021-09-19 01:27:45,4395766ae|2021-09-19 01:29:13,
1018,36ba7a7|2021-09-19 01:33:00,
1020,23fe40-4796-ad3d-6d5499b|2021-09-19 01:38:59,77a90a1c97b|2021-09-19 01:34:53,
1022,3623fe40|2021-09-19 01:33:00,
1028,6c77d26c-6fb86|2021-09-19 01:50:50,f0ac93b3df|2021-09-19 01:51:11,
1032,ac55-4be82f28d|2021-09-19 01:54:20,82229689e9da|2021-09-23 01:19:47,

I read the file using sc.textFile which returns an RDD of type Array[String] after which I perform the operations .map(x=>x.substring(1,x.length()-1)).map(x=>x.split(",").toList)

After split.toList I want to map the first element of each of the lists obtained to every other element of the list for which I use .map(x=>(x(0),x(1))).toDF("c1","c2")

This works fine for those lists which have only one value after split but skips on all other elements of the lists having more than one value for obvious reasons. For eg: .map(x=>(x(0),x(1))) returns [1020,23fe40-4796-ad3d-6d5499b|2021-09-19 01:38:59] but skips out on the third element here 77a90a1c97b|2021-09-19 01:34:53

How can I write a map function which returns [1020,23fe40-4796-ad3d-6d5499b|2021-09-19 01:38:59], [1020,77a90a1c97b|2021-09-19 01:34:53] given that all the lists created using .map(x=>x.split(",").toList) are of varying lengths (have varying number of elements)?

CodePudding user response：

I noted the ',' at the end of the file, but split ignores nulls.

The solution is as follows, just try it and you will see it works:

// x._n cannot work here initially.
val rdd = spark.sparkContext.textFile("/FileStore/tables/oddfile_01.txt")
val rdd2 = rdd.map(line => line.split(','))
val rdd3 = rdd2.map(x => (x(0), x.tail.toList)) 
val rdd4 = rdd3.flatMap{case (x, y) => y.map((x, _))}
rdd4.collect

Cardinality does change in this approach though.