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doku:bigdata [2021/06/23 09:35]
dieter [Background]
doku:bigdata [2023/05/11 08:52] (current)
katrin
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 === Example slurm & python scripts === === Example slurm & python scripts ===
  
-Let us calculate the value of pi by means of the following Python script <html><span style="color:#cc3300;font-size:100%;">&dzigrarr;</span> </html> ''pi.py'' (from the Spark distribution): +Let us calculate the value of pi by means of the following Python script ''pi.py'' (example originally taken from the Spark distribution):
-<code> +
-from __future__ import print_function+
  
 +<code python>
 +from operator import add
 +from random import random
 import sys import sys
-from random import random + 
-from operator import add +
 from pyspark.sql import SparkSession from pyspark.sql import SparkSession
 + 
 if __name__ == "__main__": if __name__ == "__main__":
     """     """
Line 58: Line 57:
         .appName("PythonPi")\         .appName("PythonPi")\
         .getOrCreate()         .getOrCreate()
 + 
     partitions = int(sys.argv[1]) if len(sys.argv) > 1 else 2     partitions = int(sys.argv[1]) if len(sys.argv) > 1 else 2
     n = 100000 * partitions     n = 100000 * partitions
 + 
     def f(_):     def f(_):
         x = random() * 2 - 1         x = random() * 2 - 1
         y = random() * 2 - 1         y = random() * 2 - 1
         return 1 if x ** 2 + y ** 2 <= 1 else 0         return 1 if x ** 2 + y ** 2 <= 1 else 0
- +  
-    count = spark.sparkContext.parallelize(range(1, n + 1), partitions). +    count = spark.sparkContext
-            map(f).reduce(add) +        .parallelize(range(1, n + 1), partitions)\ 
-    print("Pi is roughly %f" % (4.0 * count / n)+        .map(f)
- +        .reduce(add) 
-    spark.stop()</code>+    pi = 4.0 * count / n 
 +    print(f"Pi is roughly {pi}"
 +  
 +    spark.stop() 
 +</code>
 The idea of the calculation is to check (very often) whether a random point in the area [-1,-1; 1,1] is within a unit circle (i.e. has a distance less than 1 from origin). Since we know formulas for the area of the square as well as the circle we can estimate pi. The idea of the calculation is to check (very often) whether a random point in the area [-1,-1; 1,1] is within a unit circle (i.e. has a distance less than 1 from origin). Since we know formulas for the area of the square as well as the circle we can estimate pi.
  
-In order to submit a batch job to the queuing system we use the SLURM script <html><span style="color:#cc3300;font-size:100%;">&dzigrarr;</span> </html> ''pi.slrm'':+Assuming that the script is saved to ''$HOME/pi.py''' we can use the following SLURM script ''pi.slrm'' to run the code on VSC-4:
  
-<code>+<code bash>
 #!/bin/bash #!/bin/bash
 #SBATCH --nodes=1 #SBATCH --nodes=1
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 #SBATCH --error=err_spark-yarn-pi-%A #SBATCH --error=err_spark-yarn-pi-%A
 #SBATCH --output=out_spark-yarn-pi-%A #SBATCH --output=out_spark-yarn-pi-%A
 +#SBATCH --partition=skylake_0096
 +#SBATCH --qos=skylake_0096
  
 module purge module purge
-module load python/3.8.0-gcc-9.1.0-wkjbtaa + 
-module load openjdk/11.0.2-gcc-9.1.0-ayy5f5t+# you can choose one of the following python versions 
 +# with the current hadoop/spark installation on VSC-4 
 +# note: the current spark version does NOT work with python 3.11 
 +module load python/3.10.7-gcc-12.2.0-5a2kkeu 
 +module load python/3.9.13-gcc-12.2.0-ctxezzj 
 +# module load python/3.8.12-gcc-12.2.0-tr7w5qy 
 + 
 +module load openjdk
 module load hadoop module load hadoop
 module load spark module load spark
 +
 +export PDSH_RCMD_TYPE=ssh
  
 prolog_create_key.sh prolog_create_key.sh
 . vsc_start_hadoop.sh . vsc_start_hadoop.sh
 . vsc_start_spark.sh . vsc_start_spark.sh
- 
-export SPARK_EXAMPLES=${HOME}/BigData/SparkDistributionExamples/ 
  
 spark-submit --master yarn --deploy-mode client --num-executors 140 \ spark-submit --master yarn --deploy-mode client --num-executors 140 \
-      --executor-memory 2G $SPARK_EXAMPLES/src/main/python/pi.py 1000+      --executor-memory 2G $HOME/pi.py 1000 
 + 
 +. vsc_stop_spark.sh 
 +. vsc_stop_hadoop.sh
  
 epilog_discard_key.sh epilog_discard_key.sh
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 In this slurm script we have  In this slurm script we have 
-  * slurm commands, starting with #SBATCH to set the job name, the maximum execution time and where the output files will go,+  * slurm commands, starting with #SBATCH to set the job name, the maximum execution time and where the output files will go, as well as the slurm qos and partition that should be used,
   * module commands, loading all the modules which are required by our job: python, Java (Hadoop is written in Java), Hadoop, and Spark,   * module commands, loading all the modules which are required by our job: python, Java (Hadoop is written in Java), Hadoop, and Spark,
   * setup scripts which create temporary ssh keys, and start Hadoop and Spark services in user context on the nodes of the job,   * setup scripts which create temporary ssh keys, and start Hadoop and Spark services in user context on the nodes of the job,
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   * a script to discard the temporary ssh keys.   * a script to discard the temporary ssh keys.
  
-The script is submitted to the slurm scheduler by  +The script is submitted to the slurm scheduler by executing: 
- +<code> 
-  sbatch pi.slrm+sbatch pi.slrm 
 +</code>
  
 ==== MapReduce: Concepts and example ==== ==== MapReduce: Concepts and example ====
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 An example is  An example is 
  
-<code>+<code bash>
 #!/bin/bash #!/bin/bash
 #SBATCH --job-name=simple_mapreduce #SBATCH --job-name=simple_mapreduce
Line 130: Line 146:
  
 module purge module purge
-module load openjdk/11.0.2-gcc-9.1.0-ayy5f5t+module load openjdk
 module load hadoop module load hadoop
 +
 +export PDSH_RCMD_TYPE=ssh
  
 prolog_create_key.sh prolog_create_key.sh
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 To use Big Data on VSC use those modules: To use Big Data on VSC use those modules:
  
-  * python/3.8.0-gcc-9.1.0-wkjbtaa +  * python (note: the current spark version does NOT work with python 3.11) 
-  * openjdk/11.0.2-gcc-9.1.0-ayy5f5t +    * python/3.10.7-gcc-12.2.0-5a2kkeu 
-  * hadoop +    * python/3.9.13-gcc-12.2.0-ctxezzj 
-  * spark+    * python/3.8.12-gcc-12.2.0-tr7w5qy 
 +  * openjdk/11.0.15_10-gcc-11.3.0-ih4nksq 
 +  * hadoop (hadoop/3.3.2-gcc-11.3.0-ypaxzwt) 
 +  * spark (spark/3.1.1-gcc-11.3.0-47oqksq)
   * r   * r
 +
  
 Depending on the application, choose the right combination: Depending on the application, choose the right combination:
  • doku/bigdata.1624440938.txt.gz
  • Last modified: 2021/06/23 09:35
  • by dieter