[
https://issues.apache.org/jira/browse/SPARK-8685?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Yin Huai updated SPARK-8685:
----------------------------
Issue Type: Sub-task (was: Bug)
Parent: SPARK-6116
> dataframe left joins are not working as expected in pyspark
> -----------------------------------------------------------
>
> Key: SPARK-8685
> URL: https://issues.apache.org/jira/browse/SPARK-8685
> Project: Spark
> Issue Type: Sub-task
> Components: PySpark, SQL
> Affects Versions: 1.4.0
> Environment: ubuntu 14.04
> Reporter: axel dahl
> Priority: Critical
>
> I have the following code:
> {code}
> from pyspark import SQLContext
> d1 = [{'name':'bob', 'country': 'usa', 'age': 1},
> {'name':'alice', 'country': 'jpn', 'age': 2},
> {'name':'carol', 'country': 'ire', 'age': 3}]
> d2 = [{'name':'bob', 'country': 'usa', 'colour':'red'},
> {'name':'carol', 'country': 'ire', 'colour':'green'}]
> r1 = sc.parallelize(d1)
> r2 = sc.parallelize(d2)
> sqlContext = SQLContext(sc)
> df1 = sqlContext.createDataFrame(d1)
> df2 = sqlContext.createDataFrame(d2)
> df1.join(df2, df1.name == df2.name and df1.country == df2.country,
> 'left_outer').collect()
> {code}
> When I run it I get the following, (notice in the first row, all join keys
> are take from the right-side and so are blanked out):
> {code}
> [Row(age=2, country=None, name=None, colour=None, country=None, name=None),
> Row(age=1, country=u'usa', name=u'bob', colour=u'red', country=u'usa',
> name=u'bob'),
> Row(age=3, country=u'ire', name=u'carol', colour=u'green', country=u'ire',
> name=u'alice')]
> {code}
> I would expect to get (though ideally without duplicate columns):
> {code}
> [Row(age=2, country=u'ire', name=u'alice', colour=None, country=None,
> name=None),
> Row(age=1, country=u'usa', name=u'bob', colour=u'red', country=u'usa',
> name=u'bob'),
> Row(age=3, country=u'ire', name=u'carol', colour=u'green', country=u'ire',
> name=u'alice')]
> {code}
> The workaround for now is this rather clunky piece of code:
> {code}
> df2 = sqlContext.createDataFrame(d2).withColumnRenamed('name',
> 'name2').withColumnRenamed('country', 'country2')
> df1.join(df2, df1.name == df2.name2 and df1.country == df2.country2,
> 'left_outer').collect()
> {code}
--
This message was sent by Atlassian JIRA
(v6.3.4#6332)
---------------------------------------------------------------------
To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org
For additional commands, e-mail: issues-h...@spark.apache.org
