[ https://issues.apache.org/jira/browse/SPARK-10892?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16865246#comment-16865246 ]
Tony Zhang commented on SPARK-10892: ------------------------------------ This issue still exists in latest code as of today's Spark code (Spark 3.0.0). Took some time debugging and here are my observations: prcp("value") and tmin("value") are referring to the same Column instance thus `select` on the joined Dataframe returns the same value `3`. The same Column instance is from the same LogicalPlan held by the Dataframe instance, which is created in the `load()` method. This LogicalPlan instance is reused in each `filter()` call, then provides the same Column instance with the same column name, like "value". This can be confirmed with statement below: {code:java} scala> prcp("value").expr == tmin("value").expr res5: Boolean = true {code} {code:java} scala> prcp.join(tmin, "date_str").select(prcp("value"), tmin("value")).explain(true) == Parsed Logical Plan == Project [value#9L, value#9L] {code} {code:java} scala> prcp.explain(true) == Parsed Logical Plan == 'Filter ('metric = PRCP) +- RelationV2[date_str#7, metric#8, value#9L] scala> tmin.explain(true) == Parsed Logical Plan == 'Filter ('metric = TMIN) +- RelationV2[date_str#7, metric#8, value#9L]{code} This also explains why there's no such problem if you join the two Dataset created seperately (using 2 toDF() calls, or using 2 different load() calls etc.), because in that case, 2 different LogicalPlan instances will be created thus prcp("value") and tmin("value") will refer to the different column instance. I made a local hack to create a new LogicalPlan when user calls `filter()` with different condition expression, then the problem is gone. However I think there should be a thorough fix that properly manipulate LogicalPlan instances in Dataset, instead of reusing the same instance across all functions. I will leave it to spark SQL experts. Hope my debugging above helps a little. I'm new to spark, so please let me know if I missed sth here :) > Join with Data Frame returns wrong results > ------------------------------------------ > > Key: SPARK-10892 > URL: https://issues.apache.org/jira/browse/SPARK-10892 > Project: Spark > Issue Type: Bug > Components: SQL > Affects Versions: 1.4.1, 1.5.0 > Reporter: Ofer Mendelevitch > Priority: Critical > Attachments: data.json > > > I'm attaching a simplified reproducible example of the problem: > 1. Loading a JSON file from HDFS as a Data Frame > 2. Creating 3 data frames: PRCP, TMIN, TMAX > 3. Joining the data frames together. Each of those has a column "value" with > the same name, so renaming them after the join. > 4. The output seems incorrect; the first column has the correct values, but > the two other columns seem to have a copy of the values from the first column. > Here's the sample code: > {code} > import org.apache.spark.sql._ > val sqlc = new SQLContext(sc) > val weather = sqlc.read.format("json").load("data.json") > val prcp = weather.filter("metric = 'PRCP'").as("prcp").cache() > val tmin = weather.filter("metric = 'TMIN'").as("tmin").cache() > val tmax = weather.filter("metric = 'TMAX'").as("tmax").cache() > prcp.filter("year=2012 and month=10").show() > tmin.filter("year=2012 and month=10").show() > tmax.filter("year=2012 and month=10").show() > val out = (prcp.join(tmin, "date_str").join(tmax, "date_str") > .select(prcp("year"), prcp("month"), prcp("day"), prcp("date_str"), > prcp("value").alias("PRCP"), tmin("value").alias("TMIN"), > tmax("value").alias("TMAX")) ) > out.filter("year=2012 and month=10").show() > {code} > The output is: > {code} > +--------+---+------+-----+-----------+-----+----+ > |date_str|day|metric|month| station|value|year| > +--------+---+------+-----+-----------+-----+----+ > |20121001| 1| PRCP| 10|USW00023272| 0|2012| > |20121002| 2| PRCP| 10|USW00023272| 0|2012| > |20121003| 3| PRCP| 10|USW00023272| 0|2012| > |20121004| 4| PRCP| 10|USW00023272| 0|2012| > |20121005| 5| PRCP| 10|USW00023272| 0|2012| > |20121006| 6| PRCP| 10|USW00023272| 0|2012| > |20121007| 7| PRCP| 10|USW00023272| 0|2012| > |20121008| 8| PRCP| 10|USW00023272| 0|2012| > |20121009| 9| PRCP| 10|USW00023272| 0|2012| > |20121010| 10| PRCP| 10|USW00023272| 0|2012| > |20121011| 11| PRCP| 10|USW00023272| 3|2012| > |20121012| 12| PRCP| 10|USW00023272| 0|2012| > |20121013| 13| PRCP| 10|USW00023272| 0|2012| > |20121014| 14| PRCP| 10|USW00023272| 0|2012| > |20121015| 15| PRCP| 10|USW00023272| 0|2012| > |20121016| 16| PRCP| 10|USW00023272| 0|2012| > |20121017| 17| PRCP| 10|USW00023272| 0|2012| > |20121018| 18| PRCP| 10|USW00023272| 0|2012| > |20121019| 19| PRCP| 10|USW00023272| 0|2012| > |20121020| 20| PRCP| 10|USW00023272| 0|2012| > +--------+---+------+-----+-----------+-----+——+ > +--------+---+------+-----+-----------+-----+----+ > |date_str|day|metric|month| station|value|year| > +--------+---+------+-----+-----------+-----+----+ > |20121001| 1| TMIN| 10|USW00023272| 139|2012| > |20121002| 2| TMIN| 10|USW00023272| 178|2012| > |20121003| 3| TMIN| 10|USW00023272| 144|2012| > |20121004| 4| TMIN| 10|USW00023272| 144|2012| > |20121005| 5| TMIN| 10|USW00023272| 139|2012| > |20121006| 6| TMIN| 10|USW00023272| 128|2012| > |20121007| 7| TMIN| 10|USW00023272| 122|2012| > |20121008| 8| TMIN| 10|USW00023272| 122|2012| > |20121009| 9| TMIN| 10|USW00023272| 139|2012| > |20121010| 10| TMIN| 10|USW00023272| 128|2012| > |20121011| 11| TMIN| 10|USW00023272| 122|2012| > |20121012| 12| TMIN| 10|USW00023272| 117|2012| > |20121013| 13| TMIN| 10|USW00023272| 122|2012| > |20121014| 14| TMIN| 10|USW00023272| 128|2012| > |20121015| 15| TMIN| 10|USW00023272| 128|2012| > |20121016| 16| TMIN| 10|USW00023272| 156|2012| > |20121017| 17| TMIN| 10|USW00023272| 139|2012| > |20121018| 18| TMIN| 10|USW00023272| 161|2012| > |20121019| 19| TMIN| 10|USW00023272| 133|2012| > |20121020| 20| TMIN| 10|USW00023272| 122|2012| > +--------+---+------+-----+-----------+-----+——+ > +--------+---+------+-----+-----------+-----+----+ > |date_str|day|metric|month| station|value|year| > +--------+---+------+-----+-----------+-----+----+ > |20121001| 1| TMAX| 10|USW00023272| 322|2012| > |20121002| 2| TMAX| 10|USW00023272| 344|2012| > |20121003| 3| TMAX| 10|USW00023272| 222|2012| > |20121004| 4| TMAX| 10|USW00023272| 189|2012| > |20121005| 5| TMAX| 10|USW00023272| 194|2012| > |20121006| 6| TMAX| 10|USW00023272| 200|2012| > |20121007| 7| TMAX| 10|USW00023272| 167|2012| > |20121008| 8| TMAX| 10|USW00023272| 183|2012| > |20121009| 9| TMAX| 10|USW00023272| 194|2012| > |20121010| 10| TMAX| 10|USW00023272| 183|2012| > |20121011| 11| TMAX| 10|USW00023272| 139|2012| > |20121012| 12| TMAX| 10|USW00023272| 161|2012| > |20121013| 13| TMAX| 10|USW00023272| 211|2012| > |20121014| 14| TMAX| 10|USW00023272| 189|2012| > |20121015| 15| TMAX| 10|USW00023272| 233|2012| > |20121016| 16| TMAX| 10|USW00023272| 211|2012| > |20121017| 17| TMAX| 10|USW00023272| 278|2012| > |20121018| 18| TMAX| 10|USW00023272| 294|2012| > |20121019| 19| TMAX| 10|USW00023272| 194|2012| > |20121020| 20| TMAX| 10|USW00023272| 183|2012| > +--------+---+------+-----+-----------+-----+——+ > {code} > And the join output is: > {code} > +----+-----+---+--------+----+----+----+ > |year|month|day|date_str|PRCP|TMIN|TMAX| > +----+-----+---+--------+----+----+----+ > |2012| 10| 1|20121001| 0| 0| 0| > |2012| 10| 2|20121002| 0| 0| 0| > |2012| 10| 3|20121003| 0| 0| 0| > |2012| 10| 4|20121004| 0| 0| 0| > |2012| 10| 5|20121005| 0| 0| 0| > |2012| 10| 6|20121006| 0| 0| 0| > |2012| 10| 7|20121007| 0| 0| 0| > |2012| 10| 8|20121008| 0| 0| 0| > |2012| 10| 9|20121009| 0| 0| 0| > |2012| 10| 10|20121010| 0| 0| 0| > |2012| 10| 11|20121011| 3| 3| 3| > |2012| 10| 12|20121012| 0| 0| 0| > |2012| 10| 13|20121013| 0| 0| 0| > |2012| 10| 14|20121014| 0| 0| 0| > |2012| 10| 15|20121015| 0| 0| 0| > |2012| 10| 16|20121016| 0| 0| 0| > |2012| 10| 17|20121017| 0| 0| 0| > |2012| 10| 18|20121018| 0| 0| 0| > |2012| 10| 19|20121019| 0| 0| 0| > |2012| 10| 20|20121020| 0| 0| 0| > +----+-----+---+--------+----+----+——+ > {code} > Attachment: > - data.json file that is read from HDFS -- 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