still feels like a bug to have to create unique names before a join.
On Fri, Jun 26, 2015 at 9:51 PM, ayan guha <guha.a...@gmail.com> wrote:
> You can declare the schema with unique names before creation of df.
> On 27 Jun 2015 13:01, "Axel Dahl" <a...@whisperstream.com> wrote:
>
>>
>> I have the following code:
>>
>> from pyspark import SQLContext
>>
>> d1 = [{'name':'bob', 'country': 'usa', 'age': 1}, {'name':'alice',
>> 'country': 'jpn', 'age': 2}, {'name':'carol', 'country': 'ire', 'age': 3}]
>> d2 = [{'name':'bob', 'country': 'usa', 'colour':'red'}, {'name':'alice',
>> 'country': 'ire', 'colour':'green'}]
>>
>> r1 = sc.parallelize(d1)
>> r2 = sc.parallelize(d2)
>>
>> sqlContext = SQLContext(sc)
>> df1 = sqlContext.createDataFrame(d1)
>> df2 = sqlContext.createDataFrame(d2)
>> df1.join(df2, df1.name == df2.name and df1.country == df2.country,
>> 'left_outer').collect()
>>
>>
>> When I run it I get the following, (notice in the first row, all join
>> keys are take from the right-side and so are blanked out):
>>
>> [Row(age=2, country=None, name=None, colour=None, country=None,
>> name=None),
>> Row(age=1, country=u'usa', name=u'bob', colour=u'red', country=u'usa',
>> name=u'bob'),
>> Row(age=3, country=u'ire', name=u'alice', colour=u'green',
>> country=u'ire', name=u'alice')]
>>
>> I would expect to get (though ideally without duplicate columns):
>> [Row(age=2, country=u'ire', name=u'Alice', colour=None, country=None,
>> name=None),
>> Row(age=1, country=u'usa', name=u'bob', colour=u'red', country=u'usa',
>> name=u'bob'),
>> Row(age=3, country=u'ire', name=u'alice', colour=u'green',
>> country=u'ire', name=u'alice')]
>>
>> The workaround for now is this rather clunky piece of code:
>> df2 = sqlContext.createDataFrame(d2).withColumnRenamed('name',
>> 'name2').withColumnRenamed('country', 'country2')
>> df1.join(df2, df1.name == df2.name2 and df1.country == df2.country2,
>> 'left_outer').collect()
>>
>> So to me it looks like a bug, but am I doing something wrong?
>>
>> Thanks,
>>
>> -Axel
>>
>>
>>
>>
>>
