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spark:using-python [2017/10/16 20:58]
ufal [Using Python] 		spark:using-python [2019/11/12 13:37]
straka
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 <file>pyspark</file> <file>pyspark</file>
  
-Better interactive shell with code completion using ''ipython'' (installed everywhere on cluster; ask our IT if you want to have it installed on your workstations too) can be started using: +Better interactive shell with code completion using ''ipython3'' (do `pip3 install --user ipython` if you do not have it) can be started using: 
-<file>PYSPARK_DRIVER_PYTHON=ipython pyspark</file>+<file>PYSPARK_DRIVER_PYTHON=ipython3 pyspark</file>
  
 As described in [[running-spark-on-single-machine-or-on-cluster|Running Spark on Single Machine or on Cluster]], environmental variable ''MASTER'' specifies which Spark master to use (or whether to start a local one). As described in [[running-spark-on-single-machine-or-on-cluster|Running Spark on Single Machine or on Cluster]], environmental variable ''MASTER'' specifies which Spark master to use (or whether to start a local one).
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    .map(lambda word: (word, 1))    .map(lambda word: (word, 1))
    .reduceByKey(lambda c1,c2: c1+c2)    .reduceByKey(lambda c1,c2: c1+c2)
-   .sortBy(lambda (word,count): count, ascending=False)+   .sortBy(lambda word_count: word_count[1], ascending=False)
    .take(10))    .take(10))
 </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-qrsh''), or start local Spark cluster using as many threads as there are cores if there is none:
-  <file>PYSPARK_DRIVER_PYTHON=ipython pyspark</file>+  <file>PYSPARK_DRIVER_PYTHON=ipython3 pyspark</file>
   * 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=ipython 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, 1GB RAM each) on SGE and run interactive shell:
-  <file>PYSPARK_DRIVER_PYTHON=ipython spark-qrsh 10 1G pyspark</file>+  <file>PYSPARK_DRIVER_PYTHON=ipython3 spark-qrsh 10 1G pyspark</file>
  
 Note that ''PYSPARK_DRIVER_PYTHON'' variable can be left out or specified in ''.bashrc'' (or similar). Note that ''PYSPARK_DRIVER_PYTHON'' variable can be left out or specified in ''.bashrc'' (or similar).
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    .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): count, ascending=False)+   .sortBy(lambda word_count: word_count[1], ascending=False)
    .saveAsTextFile(output))    .saveAsTextFile(output))
 sc.stop() sc.stop()

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