Hi, I am trying to port some code that was working in Spark 1.2.0 on the latest version, Spark 1.3.0. This code involves a left outer join between two SchemaRDDs which I am now trying to change to a left outer join between 2 DataFrames. I followed the example for left outer join of DataFrame at https://databricks.com/blog/2015/02/17/introducing-dataframes-in-spark-for-large-scale-data-science.html
Here's my code, where df1 and df2 are the 2 dataframes I am joining on the "country" field: val join_df = df1.join( df2, df1.country == df2.country, "left_outer") But I got a compilation error that value country is not a member of sql.DataFrame I also tried the following: val join_df = df1.join( df2, df1("country") == df2("country"), "left_outer") I got a compilation error that it is a Boolean whereas a Column is required. So what is the correct Column expression I need to provide for joining the 2 dataframes on a specific field ? thanks -- View this message in context: http://apache-spark-user-list.1001560.n3.nabble.com/column-expression-in-left-outer-join-for-DataFrame-tp22209.html Sent from the Apache Spark User List mailing list archive at Nabble.com. --------------------------------------------------------------------- To unsubscribe, e-mail: user-unsubscr...@spark.apache.org For additional commands, e-mail: user-h...@spark.apache.org