If I run as
val rs = s.join(t,"time_id").join(c,"channel_id")
It takes as inner join.
On Wed, May 18, 2016 at 2:31 AM, Mich Talebzadeh <mich.talebza...@gmail.com>
wrote:
> pretty simple, a similar construct to tables projected as DF
>
> val c = HiveContext.table("channels").select("CHANNEL_ID","CHANNEL_DESC")
> val t = HiveContext.table("times").select("TIME_ID","CALENDAR_MONTH_DESC")
> val rs = s.join(t,"time_id").join(c,"channel_id")
>
> HTH
>
> Dr Mich Talebzadeh
>
>
>
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> On 17 May 2016 at 21:52, Bijay Kumar Pathak <bkpat...@mtu.edu> wrote:
>
>> Hi,
>>
>> Try this one:
>>
>>
>> df_join = df1.*join*(df2, 'Id', "fullouter")
>>
>> Thanks,
>> Bijay
>>
>>
>> On Tue, May 17, 2016 at 9:39 AM, ram kumar <ramkumarro...@gmail.com>
>> wrote:
>>
>>> Hi,
>>>
>>> I tried to join two dataframe
>>>
>>> df_join = df1.*join*(df2, ((df1("Id") === df2("Id")), "fullouter")
>>>
>>> df_join.registerTempTable("join_test")
>>>
>>>
>>> When querying "Id" from "join_test"
>>>
>>> 0: jdbc:hive2://> *select Id from join_test;*
>>> *Error*: org.apache.spark.sql.AnalysisException: Reference 'Id' is
>>> *ambiguous*, could be: Id#128, Id#155.; line 1 pos 7 (state=,code=0)
>>> 0: jdbc:hive2://>
>>>
>>> Is there a way to merge the value of df1("Id") and df2("Id") into one
>>> "Id"
>>>
>>> Thanks
>>>
>>
>>
>
