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Posted to user@spark.apache.org by Ashish Shrowty <as...@gmail.com> on 2016/09/29 21:26:48 UTC

Spark 2.0 issue

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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Re: Spark 2.0 issue

Posted by Xiao Li <ga...@gmail.com>.
Hi, Ashish,

Will take a look at this soon.

Thanks for reporting this,

Xiao

2016-09-29 14:26 GMT-07:00 Ashish Shrowty <as...@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
>
>
>
> --
> View this message in context: http://apache-spark-user-list.1001560.n3.nabble.com/Spark-2-0-issue-tp27818.html
> Sent from the Apache Spark User List mailing list archive at Nabble.com.
>
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