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From "Aravind B (JIRA)" <j...@apache.org>
Subject [jira] [Created] (SPARK-12556) Pyspark dataframe unionAll call accepts incorrect input
Date Tue, 29 Dec 2015 13:08:49 GMT
Aravind  B created SPARK-12556:
----------------------------------

             Summary: Pyspark dataframe unionAll call accepts incorrect input
                 Key: SPARK-12556
                 URL: https://issues.apache.org/jira/browse/SPARK-12556
             Project: Spark
          Issue Type: Bug
          Components: PySpark
    Affects Versions: 1.4.1
            Reporter: Aravind  B


I actually encountered this problem with two dataframes that have 8 and 10 columns each. The
below is a made up example that reproduces what I observed going wrong.

Consider the two dataframes:

df1:

+-------+----------+
|id     |     count|
+-------+----------+
+-------+----------+

df2:

+-------+---------+----------+
|id     |new_count|     count|
+-------+---------+----------+
|      1|        4|         6|
|      1|        5|         6|
|      3|        6|         6|
|      2|        7|         6|
+-------+---------+----------+

The call:

df3 = df1.unionAll(df2)

returns successfully with df3 containing 2 cloumns. However, some columns now have swapped
values (with other columns). Based on my previous experience I would say that df3's count
column will actually be the new_count column.

I believe that this call should never complete successfully in the first place and should
throw an exception instead.



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