Github user megatron-me-uk commented on the pull request:
https://github.com/apache/spark/pull/6262#issuecomment-103441329
A simple test of this:
```python
a = sc.parallelize([1, 2, 3])
b = a.pipe('cc') # a clearly incorrect pipe command
b.collect()
```
The old behaviour is to return an empty list (`[]`) with no errors and
fairly quiet logs if running on a distributed cluster.
The new behaviour is for the Job to fail with the following text in the
logs:
: org.apache.spark.SparkException: Job aborted due to stage failure: Task 2
in stage 0.0 failed 1 times, most recent failure: Lost task 2.0 in stage 0.0
(TID 2, localhost): org.apache.spark.api.python.PythonException: Traceback
(most recent call last):
File
"/usr/local/Cellar/apache-spark/1.3.0/libexec/python/pyspark/worker.py", line
101, in main
process()
File
"/usr/local/Cellar/apache-spark/1.3.0/libexec/python/pyspark/worker.py", line
96, in process
serializer.dump_stream(func(split_index, iterator), outfile)
File
"/usr/local/Cellar/apache-spark/1.3.0/libexec/python/pyspark/rdd.py", line 270,
in func
return f(iterator)
File
"/usr/local/Cellar/apache-spark/1.3.0/libexec/python/pyspark/rdd.py", line 666,
in func
raise Exception("Pipe function `%s' exited with error code %d"
%(command, pipe.returncode) )
Exception: Pipe function `cc' exited with error code 1
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