Yes this looks like https://issues.apache.org/jira/browse/BEAM-11929, I removed it from the release blockers since there is a workaround (use a NamedTuple type), but it's probably worth cherrypicking the fix.
On Thu, Mar 25, 2021 at 4:44 PM Robert Bradshaw <[email protected]> wrote: > This could be https://issues.apache.org/jira/browse/BEAM-11929 > > On Thu, Mar 25, 2021 at 4:26 PM Robert Bradshaw <[email protected]> > wrote: > >> This is definitely wrong. Looking into what's going on here, but this >> seems severe enough to be a blocker for the next release. >> >> On Thu, Mar 25, 2021 at 3:39 PM Xinyu Liu <[email protected]> wrote: >> >>> Hi, folks, >>> >>> I am playing around with the Python Dataframe API, and seemly got an >>> schema issue when converting pcollection to dataframe. I wrote the >>> following code for a simple test: >>> >>> import apache_beam as beam >>> from apache_beam.dataframe.convert import to_dataframe >>> from apache_beam.dataframe.convert import to_pcollection >>> >>> p = beam.Pipeline() >>> data = p | beam.Create([('a', '1111'), ('b', '2222')]) | beam.Map(lambda >>> x : beam.Row(word=x[0], val=x[1])) >>> _ = data | beam.Map(print) >>> p.run() >>> >>> This shows the following: >>> Row(val='1111', word='a') Row(val='2222', word='b') >>> >>> But if I use to_dataframe() to convert it into a df, seems the schema >>> was reversed: >>> >>> df = to_dataframe(data) >>> dataCopy = to_pcollection(df) >>> _ = dataCopy | beam.Map(print) >>> p.run() >>> >>> I got: >>> BeamSchema_4100b64e_16e9_467d_932e_5fc2e4acaca7(word='1111', val='a') >>> BeamSchema_4100b64e_16e9_467d_932e_5fc2e4acaca7(word='2222', val='b') >>> >>> Seems now the column 'word' and 'val' is swapped. The problem seems to >>> happen during to_dataframe(). If I print out df['word'], I got '1111' and >>> '2222'. I am not sure whether I am doing something wrong or there is an >>> issue in the schema conversion. Could someone help me take a look? >>> >>> Thanks, Xinyu >>> >>
