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From Nirav Patel <npa...@xactlycorp.com>
Subject Re: How to avoid duplicate column names after join with multiple conditions
Date Thu, 12 Jul 2018 17:23:32 GMT
Hi Prem, dropping column, renaming column are working for me as a
workaround. I thought it just nice to have generic api that can handle that
for me. or some intelligence that since both columns are same it shouldn't
complain in subsequent Select clause that it doesn't know if I mean a#12 or
a#81. They are both same just pick one.

On Thu, Jul 12, 2018 at 9:38 AM, Prem Sure <sparksure542@gmail.com> wrote:

> Hi Nirav, did you try
> .drop(df1(a) after join
>
> Thanks,
> Prem
>
> On Thu, Jul 12, 2018 at 9:50 PM Nirav Patel <npatel@xactlycorp.com> wrote:
>
>> Hi Vamshi,
>>
>> That api is very restricted and not generic enough. It imposes that all
>> conditions of joins has to have same column on both side and it also has to
>> be equijoin. It doesn't serve my usecase where some join predicates don't
>> have same column names.
>>
>> Thanks
>>
>> On Sun, Jul 8, 2018 at 7:39 PM, Vamshi Talla <vamshi_t@hotmail.com>
>> wrote:
>>
>>> Nirav,
>>>
>>> Spark does not create a duplicate column when you use the below join
>>> expression,  as an array of column(s) like below but that requires the
>>> column name to be same in both the data frames.
>>>
>>> Example: *df1.join(df2, [‘a’])*
>>>
>>> Thanks.
>>> Vamshi Talla
>>>
>>> On Jul 6, 2018, at 4:47 PM, Gokula Krishnan D <email2dgk@gmail.com>
>>> wrote:
>>>
>>> Nirav,
>>>
>>> withColumnRenamed() API might help but it does not different column and
>>> renames all the occurrences of the given column. either use select() API
>>> and rename as you want.
>>>
>>>
>>>
>>> Thanks & Regards,
>>> Gokula Krishnan* (Gokul)*
>>>
>>> On Mon, Jul 2, 2018 at 5:52 PM, Nirav Patel <npatel@xactlycorp.com>
>>> wrote:
>>>
>>>> Expr is `df1(a) === df2(a) and df1(b) === df2(c)`
>>>>
>>>> How to avoid duplicate column 'a' in result? I don't see any api that
>>>> combines both. Rename manually?
>>>>
>>>>
>>>>
>>>> [image: What's New with Xactly]
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>>>>
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>>>>
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>>>
>>>
>>>
>>>
>>
>>
>>
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>>
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>
>

-- 


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