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From Sanjay Subramanian <sanjaysubraman...@yahoo.com.INVALID>
Subject Re: FlatMapValues
Date Wed, 31 Dec 2014 15:45:00 GMT
Hey Kapil, Fernando
Thanks for your mail.
[1] Fernando, if I don't use an "if" logic inside the "map" then if I have lines of input
data that have less fields than I am expecting I get ArrayOutOfBounds exception. so the "if"
is to safeguard against that. 
[2] Kapil, I am sorry I did not clarify. Yes my code "DID NOT" compile saying that flatMapValues is
not defined.
In fact when I used your snippet , the code still does not compile 
Error:(36, 57) value flatMapValues is not a member of org.apache.spark.rdd.RDD[(String, String)] 
              }).filter(pair => pair._1.length() > 0).flatMapValues(skus =>
skus.split('\t')).saveAsTextFile("/data/vaers/msfx/reac/" + outFile)               
                                        ^ 

My pom.xml looks like this 
<dependency>
   <groupId>org.apache.spark</groupId>
   <artifactId>spark-core_2.10</artifactId>
   <version>1.2.0</version>
</dependency>
<dependency>
   <groupId>org.apache.spark</groupId>
   <artifactId>spark-sql_2.10</artifactId>
   <version>1.2.0</version>
</dependency>

[3] To summarize all I want is to convert 

SUMMARY=======when a dataset looks like the following 
1,red,blue,green2,yellow,violet,pink
I want to output the following and currently not able to
1,red1,blue1,green2,yellow2,violet2,pink

thanks

regards
sanjay

      From: Fernando O. <fotero@gmail.com>
 To: Kapil Malik <kmalik@adobe.com> 
Cc: Sanjay Subramanian <sanjaysubramanian@yahoo.com>; "user@spark.apache.org" <user@spark.apache.org>

 Sent: Wednesday, December 31, 2014 6:06 AM
 Subject: Re: FlatMapValues
   
Hi Sanjay,
Doing an if inside a Map sounds like a bad idea, it seems like you actually want to filter
and then apply map



On Wed, Dec 31, 2014 at 9:54 AM, Kapil Malik <kmalik@adobe.com> wrote:

Hi Sanjay, I tried running your code on spark shell piece by piece – // Setupval line1
= “025126,Chills,8.10,Injection site oedema,8.10,Injection site reaction,8.10,Malaise,8.10,Myalgia,8.10”val
line2 = “025127,Chills,8.10,Injection site oedema,8.10,Injection site reaction,8.10,Malaise,8.10,Myalgia,8.10”val
lines = Array[String](line1, line2) val r1 = sc.parallelize(lines, 2)// r1 is the original
RDD[String] to begin with val r2 = r1.map(line => line.split(','))// RDD[Array[String]]
– so far, so goodval r3 = r2.map(fields => {  if (fields.length >= 11 &&
!fields(0).contains("VAERS_ID")) {    (fields(0),(fields(1)+"\t"+fields(3)+"\t"+fields(5)+"\t"+fields(7)+"\t"+fields(9)))//
Returns a pair (String, String), good  }  else {    ""// Returns a String, bad  } 
})// RDD[Serializable] – PROBLEM I was not even able to apply flatMapValues since the filtered
RDD passed to it is RDD[Serializable] and not a pair RDD. I am surprised how your code compiled
correctly.  The following changes in your snippet make it work as intended - reacRdd.map(line
=> line.split(',')).map(fields => {
  if (fields.length >= 11 && !fields(0).contains("VAERS_ID")) {
    (fields(0),(fields(1)+"\t"+fields(3)+"\t"+fields(5)+"\t"+fields(7)+"\t"+fields(9)))
  }
  else {
    ("","")
  }
  }).filter(pair => pair._1.length() > 0).flatMapValues(skus => skus.split('\t')).saveAsTextFile("/data/vaers/msfx/reac/"
+ outFile) Please note that this too saves lines like (025126,Chills),i.e. with opening and
closing brackets ( and ). If you want to get rid of them, better do another map operation
to map pair to String. Kapil From: Sanjay Subramanian [mailto:sanjaysubramanian@yahoo.com.INVALID]
Sent: 31 December 2014 13:42
Cc: user@spark.apache.org
Subject: FlatMapValues hey guys  My dataset is like this  025126,Chills,8.10,Injection
site oedema,8.10,Injection site reaction,8.10,Malaise,8.10,Myalgia,8.10 Intended output is ==================025126,Chills025126,Injection
site oedema025126,Injection site reaction025126,Malaise025126,Myalgia My code is as follows
but the flatMapValues does not work even after I have created the pair RDD.************************************************************************reacRdd.map(line
=> line.split(',')).map(fields => {
  if (fields.length >= 11 && !fields(0).contains("VAERS_ID")) {
    (fields(0),(fields(1)+"\t"+fields(3)+"\t"+fields(5)+"\t"+fields(7)+"\t"+fields(9)))
  }
  else {
    ""
  }
  }).filter(line => line.toString.length() > 0).flatMapValues(skus => skus.split('\t')).saveAsTextFile("/data/vaers/msfx/reac/"
+ outFile)************************************************************************ thanks sanjay



  
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