wuchang created SPARK-19860:
-------------------------------
Summary: DataFrame join get conflict error if two frames has a
same name column.
Key: SPARK-19860
URL: https://issues.apache.org/jira/browse/SPARK-19860
Project: Spark
Issue Type: Bug
Components: PySpark
Affects Versions: 2.1.0
Reporter: wuchang
>>> print df1.collect()
[Row(fdate=u'20170223', in_amount1=7758588), Row(fdate=u'20170302',
in_amount1=7656414), Row(fdate=u'20170207', in_amount1=7836305),
Row(fdate=u'20170208', in_amount1=14887432), Row(fdate=u'20170224',
in_amount1=16506043), Row(fdate=u'20170201', in_amount1=7339381),
Row(fdate=u'20170221', in_amount1=7490447), Row(fdate=u'20170303',
in_amount1=11142114), Row(fdate=u'20170202', in_amount1=7882746),
Row(fdate=u'20170306', in_amount1=12977822), Row(fdate=u'20170227',
in_amount1=15480688), Row(fdate=u'20170206', in_amount1=11370812),
Row(fdate=u'20170217', in_amount1=8208985), Row(fdate=u'20170203',
in_amount1=8175477), Row(fdate=u'20170222', in_amount1=11032303),
Row(fdate=u'20170216', in_amount1=11986702), Row(fdate=u'20170209',
in_amount1=9082380), Row(fdate=u'20170214', in_amount1=8142569),
Row(fdate=u'20170307', in_amount1=11092829), Row(fdate=u'20170213',
in_amount1=12341887), Row(fdate=u'20170228', in_amount1=13966203),
Row(fdate=u'20170220', in_amount1=9397558), Row(fdate=u'20170210',
in_amount1=8205431), Row(fdate=u'20170215', in_amount1=7070829),
Row(fdate=u'20170301', in_amount1=10159653)]
>>> print df2.collect()
[Row(fdate=u'20170223', in_amount2=7072120), Row(fdate=u'20170302',
in_amount2=5548515), Row(fdate=u'20170207', in_amount2=5451110),
Row(fdate=u'20170208', in_amount2=4483131), Row(fdate=u'20170224',
in_amount2=9674888), Row(fdate=u'20170201', in_amount2=3227502),
Row(fdate=u'20170221', in_amount2=5084800), Row(fdate=u'20170303',
in_amount2=20577801), Row(fdate=u'20170202', in_amount2=4024218),
Row(fdate=u'20170306', in_amount2=8581773), Row(fdate=u'20170227',
in_amount2=5748035), Row(fdate=u'20170206', in_amount2=7330154),
Row(fdate=u'20170217', in_amount2=6838105), Row(fdate=u'20170203',
in_amount2=9390262), Row(fdate=u'20170222', in_amount2=3800662),
Row(fdate=u'20170216', in_amount2=4338891), Row(fdate=u'20170209',
in_amount2=4024611), Row(fdate=u'20170214', in_amount2=4030389),
Row(fdate=u'20170307', in_amount2=5504936), Row(fdate=u'20170213',
in_amount2=7142428), Row(fdate=u'20170228', in_amount2=8618951),
Row(fdate=u'20170220', in_amount2=8172290), Row(fdate=u'20170210',
in_amount2=8411312), Row(fdate=u'20170215', in_amount2=5302422),
Row(fdate=u'20170301', in_amount2=9475418)]
>>> ht_net_in_df = df1.join(df2,df1.fdate == df2.fdate,'inner')
2017-03-08 10:27:34,357 WARN [Thread-2] sql.Column: Constructing trivially
true equals predicate, 'fdate#42 = fdate#42'. Perhaps you need to use aliases.
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/home/spark/python/pyspark/sql/dataframe.py", line 652, in join
jdf = self._jdf.join(other._jdf, on._jc, how)
File "/home/spark/python/lib/py4j-0.10.1-src.zip/py4j/java_gateway.py", line
933, in __call__
File "/home/spark/python/pyspark/sql/utils.py", line 69, in deco
raise AnalysisException(s.split(': ', 1)[1], stackTrace)
pyspark.sql.utils.AnalysisException: u"
Failure when resolving conflicting references in Join:
'Join Inner, (fdate#42 = fdate#42)
:- Aggregate [fdate#42], [fdate#42, cast(sum(cast(inoutmoney#47 as double)) as
int) AS in_amount1#97]
: +- Filter (inorout#44 = A)
: +- Project [firm_id#40, partnerid#45, inorout#44, inoutmoney#47, fdate#42]
: +- Filter (((partnerid#45 = pmec) && NOT (firm_id#40 = NULL)) && (NOT
(firm_id#40 = -1) && (fdate#42 >= 20170201)))
: +- SubqueryAlias history_transfer_v
: +- Project [md5(cast(firmid#41 as binary)) AS FIRM_ID#40,
fdate#42, ftime#43, inorout#44, partnerid#45, realdate#46, inoutmoney#47,
bankwaterid#48, waterid#49, waterstate#50, source#51]
: +- SubqueryAlias history_transfer
: +-
Relation[firmid#41,fdate#42,ftime#43,inorout#44,partnerid#45,realdate#46,inoutmoney#47,bankwaterid#48,waterid#49,waterstate#50,source#51]
parquet
+- Aggregate [fdate#42], [fdate#42, cast(sum(cast(inoutmoney#47 as double)) as
int) AS in_amount2#145]
+- Filter (inorout#44 = B)
+- Project [firm_id#40, partnerid#45, inorout#44, inoutmoney#47, fdate#42]
+- Filter (((partnerid#45 = pmec) && NOT (firm_id#40 = NULL)) && (NOT
(firm_id#40 = -1) && (fdate#42 >= 20170201)))
+- SubqueryAlias history_transfer_v
+- Project [md5(cast(firmid#41 as binary)) AS FIRM_ID#40,
fdate#42, ftime#43, inorout#44, partnerid#45, realdate#46, inoutmoney#47,
bankwaterid#48, waterid#49, waterstate#50, source#51]
+- SubqueryAlias history_transfer
+-
Relation[firmid#41,fdate#42,ftime#43,inorout#44,partnerid#45,realdate#46,inoutmoney#47,bankwaterid#48,waterid#49,waterstate#50,source#51]
parquet
Conflicting attributes: fdate#42
Only when I use .withColumnRenamed('fdate','fdate2') method to change df1's
column fdate to fdate1 and df2's column fdate to fdate2 , the join is ok.
So ,my question is ,why the conflict happened?
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