[ https://issues.apache.org/jira/browse/SPARK-11757?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Petri Kärkäs updated SPARK-11757: --------------------------------- Description: 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} was: 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: sqlContext = SQLContext(sc) a = sqlContext.read.parquet('s3://path-to-data-a/') b = sqlContext.read.parquet('s3://path-to-data-b/') # results 0 rows c = a.join(b, on='id', how='left_outer') c.count() # correct result d = a.join(b, a['id']==b['id'], how='left_outer') d.count() > 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 > 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 > Labels: dataframe, emr, join, pyspark > > 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} -- 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