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spark:using-python [2022/12/14 13:00]
straka [Usage Examples] 		spark:using-python [2022/12/14 13:25] (current)
straka [Usage Examples]
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 Consider the following simple script computing 10 most frequent words of Czech Wikipedia: Consider the following simple script computing 10 most frequent words of Czech Wikipedia:
 <file python> <file python>
-(sc.textFile("/lnet/troja/data/npfl118/wiki/cs/wiki.txt", 3*sc.defaultParallelism)+(sc.textFile("/net/projects/spark-example-data/wiki-cs", 3*sc.defaultParallelism)
    .flatMap(lambda line: line.split())    .flatMap(lambda line: line.split())
    .map(lambda word: (word, 1))    .map(lambda word: (word, 1))
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   * run interactive shell with local Spark cluster using one thread:   * run interactive shell with local Spark cluster using one thread:
   <file>MASTER=local PYSPARK_DRIVER_PYTHON=ipython3 pyspark</file>   <file>MASTER=local PYSPARK_DRIVER_PYTHON=ipython3 pyspark</file>
-  * start Spark cluster (10 machines, 1GB RAM each) on SGE and run interactive shell: +  * start Spark cluster (10 machines, 2GB RAM each) on Slurm and run interactive shell: 
-  <file>PYSPARK_DRIVER_PYTHON=ipython3 spark-qrsh 10 1G pyspark</file>+  <file>PYSPARK_DRIVER_PYTHON=ipython3 spark-srun 10 2G pyspark</file>
  
 Note that ''PYSPARK_DRIVER_PYTHON'' variable can be left out or specified in ''.bashrc'' (or other configuration files). Note that ''PYSPARK_DRIVER_PYTHON'' variable can be left out or specified in ''.bashrc'' (or other configuration files).
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    .flatMap(lambda line: line.split())    .flatMap(lambda line: line.split())
    .map(lambda token: (token, 1))    .map(lambda token: (token, 1))
-   .reduceByKey(lambda x,y: x + y)+   .reduceByKey(lambda x, y: x + y)
    .sortBy(lambda word_count: word_count[1], ascending=False)    .sortBy(lambda word_count: word_count[1], ascending=False)
    .saveAsTextFile(output))    .saveAsTextFile(output))
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 </file> </file>
  
-  * run ''word_count.py'' script 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.py'' script 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 word_count.py /net/projects/spark-example-data/wiki-cs outdir</file>   <file>spark-submit word_count.py /net/projects/spark-example-data/wiki-cs outdir</file>
   * run ''word_count.py'' script with local Spark cluster using one thread:   * run ''word_count.py'' script with local Spark cluster using one thread:
   <file>MASTER=local spark-submit word_count.py /net/projects/spark-example-data/wiki-cs outdir</file>   <file>MASTER=local spark-submit word_count.py /net/projects/spark-example-data/wiki-cs outdir</file>
-  * start Spark cluster (10 machines, 1GB RAM each) on SGE and run ''word_count.py'' script: +  * start Spark cluster (10 machines, @GB RAM each) using Slurm and run ''word_count.py'' script: 
-  <file>spark-qsub 10 1G spark-submit word_count.py /net/projects/spark-example-data/wiki-cs outdir</file>+  <file>spark-sbatch 10 2G spark-submit word_count.py /net/projects/spark-example-data/wiki-cs outdir</file>
  
 ===== Using Virtual Environments ===== ===== Using Virtual Environments =====

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