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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