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Posted to issues@spark.apache.org by "Mark Sirek (Jira)" <ji...@apache.org> on 2020/02/06 01:09:00 UTC
[jira] [Comment Edited] (SPARK-28067) Incorrect results in decimal
aggregation with whole-stage code gen enabled
[ https://issues.apache.org/jira/browse/SPARK-28067?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16879735#comment-16879735 ]
Mark Sirek edited comment on SPARK-28067 at 2/6/20 1:08 AM:
------------------------------------------------------------
I tried the test on 4 different systems, all immediately after downloading Spark, and changing no settings, so they should all be the defaults. None of the tests return null. I'm not sure which config settings I should change. I wouldn't think it's expected behavior for Spark to return an incorrect answer with a certain config setting, unless there's a setting which controls the hiding of overflows.
was (Author: msirek):
I tried the test on 4 different systems, all immediately after downloading Spark, and changing no settings, so they should all be the defaults. None of the tests return null. I'm not sure which config settings I should change. I wouldn't think it's expected behavior for Spark to return an incorrect answer with a certain config setting, unless there's a setting which controls the hiding or overflows.
> Incorrect results in decimal aggregation with whole-stage code gen enabled
> --------------------------------------------------------------------------
>
> Key: SPARK-28067
> URL: https://issues.apache.org/jira/browse/SPARK-28067
> Project: Spark
> Issue Type: Bug
> Components: SQL
> Affects Versions: 2.0.2, 2.1.3, 2.2.3, 2.3.4, 2.4.4, 3.0.0
> Reporter: Mark Sirek
> Priority: Blocker
> Labels: correctness
>
> The following test case involving a join followed by a sum aggregation returns the wrong answer for the sum:
>
> {code:java}
> val df = Seq(
> (BigDecimal("10000000000000000000"), 1),
> (BigDecimal("10000000000000000000"), 1),
> (BigDecimal("10000000000000000000"), 2),
> (BigDecimal("10000000000000000000"), 2),
> (BigDecimal("10000000000000000000"), 2),
> (BigDecimal("10000000000000000000"), 2),
> (BigDecimal("10000000000000000000"), 2),
> (BigDecimal("10000000000000000000"), 2),
> (BigDecimal("10000000000000000000"), 2),
> (BigDecimal("10000000000000000000"), 2),
> (BigDecimal("10000000000000000000"), 2),
> (BigDecimal("10000000000000000000"), 2)).toDF("decNum", "intNum")
> val df2 = df.withColumnRenamed("decNum", "decNum2").join(df, "intNum").agg(sum("decNum"))
> scala> df2.show(40,false)
> ---------------------------------------
> sum(decNum)
> ---------------------------------------
> 40000000000000000000.000000000000000000
> ---------------------------------------
>
> {code}
>
> The result should be 1040000000000000000000.0000000000000000.
> It appears a partial sum is computed for each join key, as the result returned would be the answer for all rows matching intNum === 1.
> If only the rows with intNum === 2 are included, the answer given is null:
>
> {code:java}
> scala> val df3 = df.filter($"intNum" === lit(2))
> df3: org.apache.spark.sql.Dataset[org.apache.spark.sql.Row] = [decNum: decimal(38,18), intNum: int]
> scala> val df4 = df3.withColumnRenamed("decNum", "decNum2").join(df3, "intNum").agg(sum("decNum"))
> df4: org.apache.spark.sql.DataFrame = [sum(decNum): decimal(38,18)]
> scala> df4.show(40,false)
> -----------
> sum(decNum)
> -----------
> null
> -----------
>
> {code}
>
> The correct answer, 1000000000000000000000.0000000000000000, doesn't fit in the DataType picked for the result, decimal(38,18), so an overflow occurs, which Spark then converts to null.
> The first example, which doesn't filter out the intNum === 1 values should also return null, indicating overflow, but it doesn't. This may mislead the user to think a valid sum was computed.
> If whole-stage code gen is turned off:
> spark.conf.set("spark.sql.codegen.wholeStage", false)
> ... incorrect results are not returned because the overflow is caught as an exception:
> java.lang.IllegalArgumentException: requirement failed: Decimal precision 39 exceeds max precision 38
>
>
>
>
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>
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