I think that you have two options:
- to run your code locally, you can use local mode by using the 'local'
master like so:
new SparkConf().setMaster("local[4]") where 4 is the number of cores
assigned to the local mode.
- to run your code remotely you need to build the jar with dependencies and
add it to your context.
new SparkConf().setMaster("spark://uri
").addJars(Array("/path/to/target/jar-with-dependencies.jar")
You will need to run maven before running your program to ensure the latest
version of your jar is built.
-regards, Gerard.
On Sat, Jun 7, 2014 at 3:10 AM, Wei Tan <w...@us.ibm.com> wrote:
> Hi,
>
> I am trying to write and debug Spark applications in scala-ide and
> maven, and in my code I target at a Spark instance at spark://xxx
>
> object App {
>
>
> def main(args : Array[String]) {
> println( "Hello World!" )
> val sparkConf = new
> SparkConf().setMaster("spark://xxx:7077").setAppName("WordCount")
>
> val spark = new SparkContext(sparkConf)
> val file = spark.textFile("hdfs://xxx:9000/wcinput/pg1184.txt")
> val counts = file.flatMap(line => line.split(" "))
> .map(word => (word, 1))
> .reduceByKey(_ + _)
> counts.saveAsTextFile("hdfs://flex05.watson.ibm.com:9000/wcoutput")
> }
>
> }
>
> I added spark-core and hadoop-client in maven dependency so the code
> compiles fine.
>
> When I click run in Eclipse I got this error:
>
> 14/06/06 20:52:18 WARN scheduler.TaskSetManager: Loss was due to
> java.lang.ClassNotFoundException
> java.lang.ClassNotFoundException: samples.App$$anonfun$2
>
> I googled this error and it seems that I need to package my code into a
> jar file and push it to spark nodes. But since I am debugging the code, it
> would be handy if I can quickly see results without packaging and uploading
> jars.
>
> What is the best practice of writing a spark application (like wordcount)
> and debug quickly on a remote spark instance?
>
> Thanks!
> Wei
>
>
> ---------------------------------
> Wei Tan, PhD
> Research Staff Member
> IBM T. J. Watson Research Center
> *http://researcher.ibm.com/person/us-wtan*
> <http://researcher.ibm.com/person/us-wtan>
