[jira] (SPARK-35563) [SQL] Window operations with over Int.MaxValue + 1 rows can silently drop rows
[ https://issues.apache.org/jira/browse/SPARK-35563 ]
Sean R. Owen deleted comment on SPARK-35563:
--
was (Author: JIRAUSER295436):
Thank you for sharing such good information. Very informative and effective
post.
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Course|https://www.igmguru.com/digital-marketing-programming/ruby-on-rails-certification-training/]
> [SQL] Window operations with over Int.MaxValue + 1 rows can silently drop rows
> --
>
> Key: SPARK-35563
> URL: https://issues.apache.org/jira/browse/SPARK-35563
> Project: Spark
> Issue Type: Bug
> Components: SQL
>Affects Versions: 3.0.2
>Reporter: Robert Joseph Evans
>Priority: Major
> Labels: data-loss
>
> I think this impacts a lot more versions of Spark, but I don't know for sure
> because it takes a long time to test. As a part of doing corner case
> validation testing for spark rapids I found that if a window function has
> more than {{Int.MaxValue + 1}} rows the result is silently truncated to that
> many rows. I have only tested this on 3.0.2 with {{row_number}}, but I
> suspect it will impact others as well. This is a really rare corner case, but
> because it is silent data corruption I personally think it is quite serious.
> {code:scala}
> import org.apache.spark.sql.expressions.Window
> val windowSpec = Window.partitionBy("a").orderBy("b")
> val df = spark.range(Int.MaxValue.toLong + 100).selectExpr(s"1 as a", "id as
> b")
> spark.time(df.select(col("a"), col("b"),
> row_number().over(windowSpec).alias("rn")).orderBy(desc("a"),
> desc("b")).select((col("rn") < 0).alias("dir")).groupBy("dir").count.show(20))
> +-+--+
>
> | dir| count|
> +-+--+
> |false|2147483647|
> | true| 1|
> +-+--+
> Time taken: 1139089 ms
> Int.MaxValue.toLong + 100
> res15: Long = 2147483747
> 2147483647L + 1
> res16: Long = 2147483648
> {code}
> I had to make sure that I ran the above with at least 64GiB of heap for the
> executor (I did it in local mode and it worked, but took forever to run)
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[jira] (SPARK-35563) [SQL] Window operations with over Int.MaxValue + 1 rows can silently drop rows
[ https://issues.apache.org/jira/browse/SPARK-35563 ]
Jungtaek Lim deleted comment on SPARK-35563:
--
was (Author: JIRAUSER294516):
Alternately, simply perform the int overflow check. Personally, I don't think
it's a problem that Spark doesn't support really huge windows. I simply want to
prevent data loss or corruption.
Thank you.
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> [SQL] Window operations with over Int.MaxValue + 1 rows can silently drop rows
> --
>
> Key: SPARK-35563
> URL: https://issues.apache.org/jira/browse/SPARK-35563
> Project: Spark
> Issue Type: Bug
> Components: SQL
>Affects Versions: 3.0.2
>Reporter: Robert Joseph Evans
>Priority: Blocker
> Labels: data-loss
>
> I think this impacts a lot more versions of Spark, but I don't know for sure
> because it takes a long time to test. As a part of doing corner case
> validation testing for spark rapids I found that if a window function has
> more than {{Int.MaxValue + 1}} rows the result is silently truncated to that
> many rows. I have only tested this on 3.0.2 with {{row_number}}, but I
> suspect it will impact others as well. This is a really rare corner case, but
> because it is silent data corruption I personally think it is quite serious.
> {code:scala}
> import org.apache.spark.sql.expressions.Window
> val windowSpec = Window.partitionBy("a").orderBy("b")
> val df = spark.range(Int.MaxValue.toLong + 100).selectExpr(s"1 as a", "id as
> b")
> spark.time(df.select(col("a"), col("b"),
> row_number().over(windowSpec).alias("rn")).orderBy(desc("a"),
> desc("b")).select((col("rn") < 0).alias("dir")).groupBy("dir").count.show(20))
> +-+--+
>
> | dir| count|
> +-+--+
> |false|2147483647|
> | true| 1|
> +-+--+
> Time taken: 1139089 ms
> Int.MaxValue.toLong + 100
> res15: Long = 2147483747
> 2147483647L + 1
> res16: Long = 2147483648
> {code}
> I had to make sure that I ran the above with at least 64GiB of heap for the
> executor (I did it in local mode and it worked, but took forever to run)
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