Oli Hall created SPARK-23299:
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Summary: __repr__ broken for Rows instantiated with *args
Key: SPARK-23299
URL: https://issues.apache.org/jira/browse/SPARK-23299
Project: Spark
Issue Type: Bug
Components: PySpark
Affects Versions: 2.2.0, 1.5.0
Environment: Tested on OS X with Spark 1.5.0 as well as pip-installed
`pyspark` 2.2.0. Code in question appears to still be in error on the master
branch of the GitHub repository.
Reporter: Oli Hall
PySpark Rows throw an exception if instantiated without column names when
`__repr__` is called. The most minimal reproducible example I've found is this:
{code:java}
> from pyspark.sql.types import Row
> Row(123)
<stack-trace snipped for brevity>
<v-env location>/lib/python2.7/site-packages/pyspark/sql/types.pyc in
__repr__(self)
-> 1524 return "<Row(%s)>" % ", ".join(self)
TypeError: sequence item 0: expected string, int found{code}
This appears to be due to the implementation of `__repr__`, which works
excellently for Rows created with column names, but for those without, assumes
all values are strings ([link
here|https://github.com/apache/spark/blob/master/python/pyspark/sql/types.py#L1584]).
This should be an easy fix, if the values are mapped to `str` first, all should
be well (last line is the only modification):
{code:java}
def __repr__(self):
"""Printable representation of Row used in Python REPL."""
if hasattr(self, "__fields__"):
return "Row(%s)" % ", ".join("%s=%r" % (k, v)
for k, v in zip(self.__fields__,
tuple(self)))
else:
"<Row(%s)>" % ", ".join(map(str, self))
{code}
This will yield the following:
{code:java}
> from pyspark.sql.types import Row
> Row('aaa', 123)
<Row(aaaa, 123)>
{code}
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