Re: SPARK LIMITATION - more than one case class is not allowed !!

2014-12-05 Thread Imran Rashid
> It's an easy mistake to make... I wonder if an assertion could be
implemented that makes sure the type parameter is present.

We could use the "NotNothing" pattern

http://blog.evilmonkeylabs.com/2012/05/31/Forcing_Compiler_Nothing_checks/

but I wonder if it would just make the method signature very confusing for
the avg user ...


Re: SPARK LIMITATION - more than one case class is not allowed !!

2014-12-05 Thread Daniel Darabos
On Fri, Dec 5, 2014 at 7:12 AM, Tobias Pfeiffer  wrote:

> Rahul,
>
> On Fri, Dec 5, 2014 at 2:50 PM, Rahul Bindlish <
> rahul.bindl...@nectechnologies.in> wrote:
>>
>> I have done so thats why spark is able to load objectfile [e.g.
>> person_obj]
>> and spark has maintained serialVersionUID [person_obj].
>>
>> Next time when I am trying to load another objectfile [e.g. office_obj]
>> and
>> I think spark is matching serialVersionUID [person_obj] with previous
>> serialVersionUID [person_obj] and giving mismatch error.
>>
>> In my first post, I have give statements which can be executed easily to
>> replicate this issue.
>>
>
> Can you post the Scala source for your case classes? I have tried the
> following in spark-shell:
>
> case class Dog(name: String)
> case class Cat(age: Int)
> val dogs = sc.parallelize(Dog("foo") :: Dog("bar") :: Nil)
> val cats = sc.parallelize(Cat(1) :: Cat(2) :: Nil)
> dogs.saveAsObjectFile("test_dogs")
> cats.saveAsObjectFile("test_cats")
>
> This gives two directories "test_dogs/" and "test_cats/". Then I restarted
> spark-shell and entered:
>
> case class Dog(name: String)
> case class Cat(age: Int)
> val dogs = sc.objectFile("test_dogs")
> val cats = sc.objectFile("test_cats")
>
> I don't get an exception, but:
>
> dogs: org.apache.spark.rdd.RDD[Nothing] = FlatMappedRDD[1] at objectFile
> at :12
>

You need to specify the type of the RDD. The compiler does not know what is
in "test_dogs".

val dogs = sc.objectFile[Dog]("test_dogs")
val cats = sc.objectFile[Cat]("test_cats")

It's an easy mistake to make... I wonder if an assertion could be
implemented that makes sure the type parameter is present.


Re: SPARK LIMITATION - more than one case class is not allowed !!

2014-12-05 Thread Rahul Bindlish
Tobias,

Understand and thanks for quick resolution of problem.

Thanks
~Rahul



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Re: SPARK LIMITATION - more than one case class is not allowed !!

2014-12-04 Thread Tobias Pfeiffer
Rahul,

On Fri, Dec 5, 2014 at 3:51 PM, Rahul Bindlish <
rahul.bindl...@nectechnologies.in> wrote:
>
> 1. Copy csv files in current directory.
> 2. Open spark-shell from this directory.
> 3. Run "one_scala" file which will create object-files from csv-files in
> current directory.
> 4. Restart spark-shell
> 5. a. Run "two_scala" file, while running it is giving error during loading
> of office_csv
> b. If we edit "two_scala" file by below contents
>
> ---
> case class person(id: Int, name: String, fathername: String, officeid: Int)
> case class office(id: Int, name: String, landmark: String, areacode:
> String)
> sc.objectFile[office]("office_obj").count
> sc.objectFile[person]("person_obj").count
>
> 
> while running it is giving error during loading of person_csv
>

One good news is: I can reproduce the error you see.

Another good news is: I can tell you how to fix this. In your one.scala
file, define all case classes *before* you use saveAsObjectFile() for the
first time. With
  case class person(id: Int, name: String, fathername: String, officeid:
Int)
  case class office(id: Int, name: String, landmark: String, areacode:
String)
  val baseperson =
sc.textFile("person_csv")saveAsObjectFile("person_obj")
  val baseoffice =
sc.textFile("office_csv")saveAsObjectFile("office_obj")
I can deserialize the obj files (in any order).

The bad news is: I have no idea about the reason for this. I blame it on
the REPL/shell and assume it would not happen for a compiled application.

Tobias


Re: SPARK LIMITATION - more than one case class is not allowed !!

2014-12-04 Thread Rahul Bindlish
Tobias,

Find csv and scala files and below are steps:

1. Copy csv files in current directory.
2. Open spark-shell from this directory.
3. Run "one_scala" file which will create object-files from csv-files in
current directory.
4. Restart spark-shell
5. a. Run "two_scala" file, while running it is giving error during loading
of office_csv
b. If we edit "two_scala" file by below contents 

---
case class person(id: Int, name: String, fathername: String, officeid: Int) 
case class office(id: Int, name: String, landmark: String, areacode: String) 
sc.objectFile[office]("office_obj").count
sc.objectFile[person]("person_obj").count 

while running it is giving error during loading of person_csv

Regards,
Rahul

sample.gz
  



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Re: SPARK LIMITATION - more than one case class is not allowed !!

2014-12-04 Thread Tobias Pfeiffer
Rahul,

On Fri, Dec 5, 2014 at 2:50 PM, Rahul Bindlish <
rahul.bindl...@nectechnologies.in> wrote:
>
> I have done so thats why spark is able to load objectfile [e.g. person_obj]
> and spark has maintained serialVersionUID [person_obj].
>
> Next time when I am trying to load another objectfile [e.g. office_obj] and
> I think spark is matching serialVersionUID [person_obj] with previous
> serialVersionUID [person_obj] and giving mismatch error.
>
> In my first post, I have give statements which can be executed easily to
> replicate this issue.
>

Can you post the Scala source for your case classes? I have tried the
following in spark-shell:

case class Dog(name: String)
case class Cat(age: Int)
val dogs = sc.parallelize(Dog("foo") :: Dog("bar") :: Nil)
val cats = sc.parallelize(Cat(1) :: Cat(2) :: Nil)
dogs.saveAsObjectFile("test_dogs")
cats.saveAsObjectFile("test_cats")

This gives two directories "test_dogs/" and "test_cats/". Then I restarted
spark-shell and entered:

case class Dog(name: String)
case class Cat(age: Int)
val dogs = sc.objectFile("test_dogs")
val cats = sc.objectFile("test_cats")

I don't get an exception, but:

dogs: org.apache.spark.rdd.RDD[Nothing] = FlatMappedRDD[1] at objectFile at
:12

Trying to access the elements of the RDD gave:

scala> dogs.collect()
14/12/05 15:08:58 INFO FileInputFormat: Total input paths to process : 8
...
org.apache.spark.SparkDriverExecutionException: Execution error
at
org.apache.spark.scheduler.DAGScheduler.handleTaskCompletion(DAGScheduler.scala:980)
...
at
scala.concurrent.forkjoin.ForkJoinWorkerThread.run(ForkJoinWorkerThread.java:107)
Caused by: java.lang.ArrayStoreException: [Ljava.lang.Object;
at scala.runtime.ScalaRunTime$.array_update(ScalaRunTime.scala:88)
at
org.apache.spark.SparkContext$$anonfun$runJob$3.apply(SparkContext.scala:1129)
...
org.apache.spark.scheduler.DAGScheduler.handleTaskCompletion(DAGScheduler.scala:976)
... 10 more

So even in the simplest of cases, this doesn't work for me in the
spark-shell, but with a different error. I guess we need to see more of
your code to help.

Tobias


Re: SPARK LIMITATION - more than one case class is not allowed !!

2014-12-04 Thread Rahul Bindlish
Tobias,

Thanks for quick reply.

Definitely, after restart case classes need to be defined again.

I have done so thats why spark is able to load objectfile [e.g. person_obj]
and spark has maintained serialVersionUID [person_obj].

Next time when I am trying to load another objectfile [e.g. office_obj] and
I think spark is matching serialVersionUID [person_obj] with previous
serialVersionUID [person_obj] and giving mismatch error.

In my first post, I have give statements which can be executed easily to
replicate this issue.

Thanks
~Rahul








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Re: SPARK LIMITATION - more than one case class is not allowed !!

2014-12-04 Thread Tobias Pfeiffer
Rahul,

On Fri, Dec 5, 2014 at 1:29 PM, Rahul Bindlish <
rahul.bindl...@nectechnologies.in> wrote:
>
> I have created  objectfiles [person_obj,office_obj] from
> csv[person_csv,office_csv] files using case classes[person,office] with API
> (saveAsObjectFile)
>
> Now I restarted spark-shell and load objectfiles using API(objectFile).
>
> *Once any of one object-class is loaded successfully, rest of object-class
> gives serialization error.*
>

I have not used saveAsObjectFile, but I think that if you define your case
classes in the spark-shell and serialized the objects, and then you restart
the spark-shell, the *classes* (structure, names etc.) will not be known to
the JVM any more. So if you try to restore the *objects* from a file, the
JVM may fail in restoring them, because there is no class it could create
objects of. Just a guess. Try to write a Scala program, compile it and see
if it still fails when executed.

Tobias


Re: SPARK LIMITATION - more than one case class is not allowed !!

2014-12-04 Thread Rahul Bindlish
Hi Tobias,

Thanks Tobias for your response.

I have created  objectfiles [person_obj,office_obj] from
csv[person_csv,office_csv] files using case classes[person,office] with API
(saveAsObjectFile)

Now I restarted spark-shell and load objectfiles using API(objectFile).

*Once any of one object-class is loaded successfully, rest of object-class
gives serialization error.*

So my understanding is that more than one case class is not allowed.

Hope, I am able to clarify myself.

Regards,
Rahul





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Re: SPARK LIMITATION - more than one case class is not allowed !!

2014-12-04 Thread Tobias Pfeiffer
On Fri, Dec 5, 2014 at 12:53 PM, Rahul Bindlish <
rahul.bindl...@nectechnologies.in> wrote:

> Is it a limitation that spark does not support more than one case class at
> a
> time.
>

What do you mean? I do not have the slightest idea what you *could*
possibly mean by "to support a case class".

Tobias


SPARK LIMITATION - more than one case class is not allowed !!

2014-12-04 Thread Rahul Bindlish
Is it a limitation that spark does not support more than one case class at a
time.

Regards,
Rahul



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