If I start up pyspark and then run this command:
import my_script; spark = my_script.Sparker(sc); spark.collapse('./data/')
Everything is A-ok. If, however, I try to do the same thing through the commandline and spark-submit, I get an error:
Command: /usr/local/spark/bin/spark-submit my_script.py collapse ./data/
File "/usr/local/spark/python/pyspark/rdd.py", line 352, in func
return f(iterator)
File "/usr/local/spark/python/pyspark/rdd.py", line 1576, in combineLocally
merger.mergeValues(iterator)
File "/usr/local/spark/python/pyspark/shuffle.py", line 245, in mergeValues
for k, v in iterator:
File "/.../my_script.py", line 173, in _json_args_to_arr
js = cls._json(line)
RuntimeError: uninitialized staticmethod object
my_script:
...
if __name__ == "__main__":
args = sys.argv[1:]
if args[0] == 'collapse':
directory = args[1]
from pyspark import SparkContext
sc = SparkContext(appName="Collapse")
spark = Sparker(sc)
spark.collapse(directory)
sc.stop()
Why is this happening? What's the difference between running pyspark and running spark-submit that would cause this divergence? And how can I make this work in spark-submit?
EDIT: I tried running this from the bash shell by doing pyspark my_script.py collapse ./data/
and I got the same error. The only time when everything works is when I am in a python shell and import the script.
The spark-submit command is a utility to run or submit a Spark or PySpark application program (or job) to the cluster by specifying options and configurations, the application you are submitting can be written in Scala, Java, or Python (PySpark).
The spark-submit script in Spark's bin directory is used to launch applications on a cluster. It can use all of Spark's supported cluster managers through a uniform interface so you don't have to configure your application especially for each one.
Spark is an awesome framework and the Scala and Python APIs are both great for most workflows. PySpark is more popular because Python is the most popular language in the data community. PySpark is a well supported, first class Spark API, and is a great choice for most organizations.
If you built a spark application, you need to use spark-submit to run the application
The code can be written either in python/scala
The mode can be either local/cluster
If you just want to test/run few individual commands, you can use the shell provided by spark
pyspark command is REPL (read–eval–print loop) which is used to start an interactive shell to test few PySpark commands. This is used during development time. We are talking about Python here.
To run spark application written in Scala or Python on a cluster or locally, you can use spark-submit.
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