[jira] [Created] (SPARK-5464) Calling help() on a Python DataFrame fails with "cannot resolve column name __name__" error

["Josh Rosen (JIRA)" <ji...@apache.org>]

Josh Rosen created SPARK-5464:
---------------------------------

             Summary: Calling help() on a Python DataFrame fails with "cannot resolve column name __name__" error
                 Key: SPARK-5464
                 URL: https://issues.apache.org/jira/browse/SPARK-5464
             Project: Spark
          Issue Type: Bug
          Components: PySpark, SQL
    Affects Versions: 1.3.0
            Reporter: Josh Rosen
            Priority: Blocker


Trying to call {{help()}} on a Python DataFrame fails with an exception:

{code}
>>> help(df)
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/Users/joshrosen/anaconda/lib/python2.7/site.py", line 464, in __call__
    return pydoc.help(*args, **kwds)
  File "/Users/joshrosen/anaconda/lib/python2.7/pydoc.py", line 1787, in __call__
    self.help(request)
  File "/Users/joshrosen/anaconda/lib/python2.7/pydoc.py", line 1834, in help
    else: doc(request, 'Help on %s:')
  File "/Users/joshrosen/anaconda/lib/python2.7/pydoc.py", line 1571, in doc
    pager(render_doc(thing, title, forceload))
  File "/Users/joshrosen/anaconda/lib/python2.7/pydoc.py", line 1545, in render_doc
    object, name = resolve(thing, forceload)
  File "/Users/joshrosen/anaconda/lib/python2.7/pydoc.py", line 1540, in resolve
    name = getattr(thing, '__name__', None)
  File "/Users/joshrosen/Documents/Spark/python/pyspark/sql.py", line 2154, in __getattr__
    return Column(self._jdf.apply(name))
  File "/Users/joshrosen/Documents/Spark/python/lib/py4j-0.8.2.1-src.zip/py4j/java_gateway.py", line 538, in __call__
  File "/Users/joshrosen/Documents/Spark/python/lib/py4j-0.8.2.1-src.zip/py4j/protocol.py", line 300, in get_return_value
py4j.protocol.Py4JJavaError: An error occurred while calling o31.apply.
: java.lang.RuntimeException: Cannot resolve column name "__name__"
	at org.apache.spark.sql.DataFrame$$anonfun$resolve$1.apply(DataFrame.scala:123)
	at org.apache.spark.sql.DataFrame$$anonfun$resolve$1.apply(DataFrame.scala:123)
	at scala.Option.getOrElse(Option.scala:120)
	at org.apache.spark.sql.DataFrame.resolve(DataFrame.scala:122)
	at org.apache.spark.sql.DataFrame.apply(DataFrame.scala:237)
	at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
	at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:57)
	at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
	at java.lang.reflect.Method.invoke(Method.java:606)
	at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:231)
	at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:379)
	at py4j.Gateway.invoke(Gateway.java:259)
	at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:133)
	at py4j.commands.CallCommand.execute(CallCommand.java:79)
	at py4j.GatewayConnection.run(GatewayConnection.java:207)
	at java.lang.Thread.run(Thread.java:745)
{code}

Here's a reproduction:

{code}
>>> from pyspark.sql import SQLContext, Row
>>> sqlContext = SQLContext(sc)
>>> rdd = sc.parallelize(['{"foo":"bar"}', '{"foo":"baz"}'])
>>> df = sqlContext.jsonRDD(rdd)
>>> help(df)
{code}

I think the problem here is that we don't throw the expected exception from our overloaded {{getattr}} if a column can't be found.

We should be able to fix this by only attempting to call {{apply}} after checking that the column name is valid (e.g. check against {{columns}}).



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