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Graeme Edwards commented on SPARK-17618: ---------------------------------------- Thanks Josh, that perfectly explains what we saw. Thanks for the quick response! > Dataframe except returns incorrect results when combined with coalesce > ---------------------------------------------------------------------- > > Key: SPARK-17618 > URL: https://issues.apache.org/jira/browse/SPARK-17618 > Project: Spark > Issue Type: Bug > Components: SQL > Affects Versions: 1.6.1, 1.6.2 > Reporter: Graeme Edwards > Assignee: Josh Rosen > Priority: Blocker > Labels: correctness > > We were getting incorrect results from the DataFrame except method - all rows > were being returned instead of the ones that intersected. Calling subtract on > the underlying RDD returned the correct result. > We tracked it down to the use of coalesce - the following is the simplest > example case we created that reproduces the issue: > {code} > val schema = new StructType().add("test", types.IntegerType ) > val t1 = sql.createDataFrame(sql.sparkContext.parallelize(1 to 100).map(i=> > Row(i)), schema) > val t2 = sql.createDataFrame(sql.sparkContext.parallelize(5 to 10).map(i=> > Row(i)), schema) > val t3 = t1.join(t2, t1.col("test").equalTo(t2.col("test")), "leftsemi") > println("Count using normal except = " + t1.except(t3).count()) > println("Count using coalesce = " + > t1.coalesce(8).except(t3.coalesce(8)).count()) > {code} > We should get the same result from both uses of except, but the one using > coalesce returns 100 instead of 94. -- 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