Depends on your Spark version, have you considered the Dataset api?
You can do something like:
val df1 = rdd1.toDF("userid")
val listRDD = sc.parallelize(listForRule77)
val listDF = listRDD.toDF("data")
df1.crossJoin(listDF).orderBy("userid").show(60, truncate=false)
+------+----------------------+
|userid|data |
+------+----------------------+
|1 |1,1,100.00|1483891200,|
|1 |1,1,100.00|1483804800,|
...
|1 |1,1,100.00|1488902400,|
|1 |1,1,100.00|1489075200,|
|1 |1,1,100.00|1488470400,|
...
On Wed, Aug 9, 2017 at 10:44 AM, Ryan <[email protected]> wrote:
> It's just sort of inner join operation... If the second dataset isn't very
> large it's ok(btw, you can use flatMap directly instead of map followed by
> flatmap/flattern), otherwise you can register the second one as a
> rdd/dataset, and join them on user id.
>
> On Wed, Aug 9, 2017 at 4:29 PM, <[email protected]> wrote:
>
>> hello guys:
>> I have a simple rdd like :
>> val userIDs = 1 to 10000
>> val rdd1 = sc.parallelize(userIDs , 16) //this rdd has 10000 user id
>> And I have a List[String] like below:
>> scala> listForRule77
>> res76: List[String] = List(1,1,100.00|1483286400, 1,1,100.00|1483372800,
>> 1,1,100.00|1483459200, 1,1,100.00|1483545600, 1,1,100.00|1483632000,
>> 1,1,100.00|1483718400, 1,1,100.00|1483804800, 1,1,100.00|1483891200,
>> 1,1,100.00|1483977600, 3,1,200.00|1485878400, 1,1,100.00|1485964800,
>> 1,1,100.00|1486051200, 1,1,100.00|1488384000, 1,1,100.00|1488470400,
>> 1,1,100.00|1488556800, 1,1,100.00|1488643200, 1,1,100.00|1488729600,
>> 1,1,100.00|1488816000, 1,1,100.00|1488902400, 1,1,100.00|1488988800,
>> 1,1,100.00|1489075200, 1,1,100.00|1489161600, 1,1,100.00|1489248000,
>> 1,1,100.00|1489334400, 1,1,100.00|1489420800, 1,1,100.00|1489507200,
>> 1,1,100.00|1489593600, 1,1,100.00|1489680000, 1,1,100.00|1489766400)
>>
>> scala> listForRule77.length
>> res77: Int = 29
>>
>> I need to create a rdd containing 290000 records. for every userid
>> in rdd1 , I need to create 29 records according to listForRule77, each
>> record start with the userid, for example 1(the
>> userid),1,1,100.00|1483286400.
>> My idea is like below:
>> 1.write a udf
>> to add the userid to the beginning of every string element
>> of listForRule77.
>> 2.use
>> val rdd2 = rdd1.map{x=> List_udf(x))}.flatmap()
>> , the result rdd2 maybe what I need.
>>
>> My question: Are there any problems in my idea? Is there a better
>> way to do this ?
>>
>>
>>
>> --------------------------------
>>
>> Thanks&Best regards!
>> San.Luo
>>
>
>
