[jira] [Updated] (SPARK-11757) Incorrect join output for joining two dataframes loaded from Parquet format

["Xiao Li (JIRA)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/SPARK-11757?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Xiao Li updated SPARK-11757:
----------------------------
    Component/s: SQL

> Incorrect join output for joining two dataframes loaded from Parquet format
> ---------------------------------------------------------------------------
>
>                 Key: SPARK-11757
>                 URL: https://issues.apache.org/jira/browse/SPARK-11757
>             Project: Spark
>          Issue Type: Bug
>          Components: PySpark, SQL
>    Affects Versions: 1.5.0
>         Environment: Python 2.7, Spark 1.5.0, Amazon linux ami https://aws.amazon.com/amazon-linux-ami/2015.03-release-notes/
>            Reporter: Petri Kärkäs
>            Assignee: Dilip Biswal
>              Labels: dataframe, emr, join, pyspark
>             Fix For: 2.0.0
>
>
> Reading in dataframes from Parquet format in s3, and executing a join between them fails when evoked by column name. Works correctly if a join condition is used instead:
> {code:none}
> sqlContext = SQLContext(sc)
> a = sqlContext.read.parquet('s3://path-to-data-a/')
> b = sqlContext.read.parquet('s3://path-to-data-b/')
> # result 0 rows
> c = a.join(b, on='id', how='left_outer')
> c.count() 
> # correct output
> d = a.join(b, a['id']==b['id'], how='left_outer')
> d.count() 
> {code}



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