Hi, Ashish,
Will take a look at this soon.
Thanks for reporting this,
Xiao
2016-09-29 14:26 GMT-07:00 Ashish Shrowty <ashish.shro...@gmail.com>:
> If I try to inner-join two dataframes which originated from the same initial
> dataframe that was loaded using spark.sql() call, it results in an error -
>
> // reading from Hive .. the data is stored in Parquet format in Amazon
> S3
> val d1 = spark.sql("select * from <hivetable>")
> val df1 =
> d1.groupBy("key1","key2").agg(avg("totalprice").as("avgtotalprice"))
> val df2 = d1.groupBy("key1","key2").agg(avg("itemcount").as("avgqty"))
> df1.join(df2, Seq("key1","key2")) gives error -
> org.apache.spark.sql.AnalysisException: using columns ['key1,'key2] can
> not be resolved given input columns: [key1, key2, avgtotalprice, avgqty];
>
> If the same Dataframe is initialized via spark.read.parquet(), the above
> code works. This same code above also worked with Spark 1.6.2. I created a
> JIRA too .. SPARK-17709 <https://issues.apache.org/jira/browse/SPARK-17709>
>
> Any help appreciated!
>
> Thanks,
> Ashish
>
>
>
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