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Dylan Guedes commented on SPARK-20169: -------------------------------------- Hi, I also reproduced it in v2.3 and master. I think that it is something related to the String type because if I cast the jr dataframe column to long it works fine - However, if I cast it to String, the bug still happens. I don't know the catalyst codebase that well (never touched it actually), do you guys have a suggestion to where to start looking after I call _jdf? I don't know how to follow the trace after converting to the JVM. Thank you! > Groupby Bug with Sparksql > ------------------------- > > Key: SPARK-20169 > URL: https://issues.apache.org/jira/browse/SPARK-20169 > Project: Spark > Issue Type: Bug > Components: SQL > Affects Versions: 2.0.0, 2.1.0 > Reporter: Bin Wu > Priority: Major > > We find a potential bug in Catalyst optimizer which cannot correctly > process "groupby". You can reproduce it by following simple example: > ========================= > from pyspark.sql.functions import * > #e=sc.parallelize([(1,2),(1,3),(1,4),(2,1),(3,1),(4,1)]).toDF(["src","dst"]) > e = spark.read.csv("graph.csv", header=True) > r = sc.parallelize([(1,),(2,),(3,),(4,)]).toDF(['src']) > r1 = e.join(r, 'src').groupBy('dst').count().withColumnRenamed('dst','src') > jr = e.join(r1, 'src') > jr.show() > r2 = jr.groupBy('dst').count() > r2.show() > ========================= > FYI, "graph.csv" contains exactly the same data as the commented line. > You can find that jr is: > |src|dst|count| > | 3| 1| 1| > | 1| 4| 3| > | 1| 3| 3| > | 1| 2| 3| > | 4| 1| 1| > | 2| 1| 1| > But, after the last groupBy, the 3 rows with dst = 1 are not grouped together: > |dst|count| > | 1| 1| > | 4| 1| > | 3| 1| > | 2| 1| > | 1| 1| > | 1| 1| > If we build jr directly from raw data (commented line), this error will not > show up. So > we suspect that there is a bug in the Catalyst optimizer when multiple joins > and groupBy's > are being optimized. -- This message was sent by Atlassian JIRA (v7.6.3#76005) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org