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}}). -- This message was sent by Atlassian JIRA (v6.3.4#6332) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org