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spark:using-scala [2018/11/24 22:42]
straka [Usage Examples] 		spark:using-scala [2024/09/27 09:21] (current)
straka [Usage Examples]
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 </file> </file>
  
-  * run interactive shell using existing Spark cluster (i.e., inside ''spark-qrsh''), or start local Spark cluster using as many threads as there are cores if there is none:+  * run interactive shell using existing Spark cluster (i.e., inside ''spark-srun''), or start local Spark cluster using as many threads as there are cores if there is none:
   <file>spark-shell</file>   <file>spark-shell</file>
   * run interactive shell with local Spark cluster using one thread:   * run interactive shell with local Spark cluster using one thread:
   <file>MASTER=local spark-shell</file>   <file>MASTER=local spark-shell</file>
-  * start Spark cluster (10 machines, 1GB RAM each) on SGE and run interactive shell: +  * start Spark cluster (10 machines, 2GB RAM each) via Slurm and run interactive shell: 
-  <file>spark-qrsh 10 1G spark-shell</file>+  <file>spark-srun 10 2G spark-shell</file>
  
  
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 version := "1.0" version := "1.0"
  
-scalaVersion := "2.11.12" +scalaVersion := "2.12.20" 
- +  
-libraryDependencies += "org.apache.spark" %% "spark-core" % "2.3.2"+libraryDependencies += "org.apache.spark" %% "spark-core" % "3.5.3"
 </file> </file>
  
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   <file>sbt package</file>   <file>sbt package</file>
  
-  * run ''word_count'' application inside existing Spark cluster (i.e., inside ''spark-qsub'' or ''spark-qrsh''), or start local Spark cluster using as many threads as there are cores if there is none: +  * run ''word_count'' application inside existing Spark cluster (i.e., inside ''spark-sbatch'' or ''spark-srun''), or start local Spark cluster using as many threads as there are cores if there is none: 
-  <file>spark-submit target/scala-2.11/word_count_2.11-1.0.jar /net/projects/spark-example-data/wiki-cs outdir</file>+  <file>spark-submit target/scala-2.12/word_count_2.12-1.0.jar /net/projects/spark-example-data/wiki-cs outdir</file>
   * run ''word_count'' application with local Spark cluster using one thread:   * run ''word_count'' application with local Spark cluster using one thread:
-  <file>MASTER=local spark-submit target/scala-2.11/word_count_2.11-1.0.jar /net/projects/spark-example-data/wiki-cs outdir</file> +  <file>MASTER=local spark-submit target/scala-2.12/word_count_2.12-1.0.jar /net/projects/spark-example-data/wiki-cs outdir</file> 
-  * start Spark cluster (10 machines, 1GB RAM each) on SGE and run ''word_count'' application: +  * start Spark cluster (10 machines, 2GB RAM each) on Slurm and run ''word_count'' application: 
-  <file>spark-qsub 10 1G spark-submit target/scala-2.11/word_count_2.11-1.0.jar /net/projects/spark-example-data/wiki-cs outdir</file>+  <file>spark-sbatch 10 2G spark-submit target/scala-2.12/word_count_2.12-1.0.jar /net/projects/spark-example-data/wiki-cs outdir</file>
  

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