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https://issues.apache.org/jira/browse/SPARK-34843?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17307477#comment-17307477
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Jason Yarbrough commented on SPARK-34843:
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>From what I can see, there is protection in the code above the stride formula
>that makes sure the partition count isn't greater than upperBound -
>lowerBound. There is also code above that to make sure that someone doesn't
>pass in a numPartition of 1.
I'm having a hard time wrapping my head around where this proposed formula
would cause an issue, but I'm hoping you, or someone, could help clarify. Would
you be able to provide an example of the overflow issue in this case?
> JDBCRelation columnPartition function improperly determines stride size
> -----------------------------------------------------------------------
>
> Key: SPARK-34843
> URL: https://issues.apache.org/jira/browse/SPARK-34843
> Project: Spark
> Issue Type: Improvement
> Components: SQL
> Affects Versions: 3.0.0
> Reporter: Jason Yarbrough
> Priority: Minor
> Attachments: SPARK-34843.patch
>
>
> Currently, in JDBCRelation (line 123), the stride size is calculated as
> follows:
> val stride: Long = upperBound / numPartitions - lowerBound / numPartitions
>
> Due to truncation happening on both divisions, the stride size can fall short
> of what it should be. This can lead to a big difference between the provided
> upper bound and the actual start of the last partition.
> I propose this formula, as it is much more accurate and leads to better
> distribution:
> val stride: Long = (upperBound - lowerBound) / (numPartitions - 2)
>
> An example (using a date column):
> Say you're creating 1,000 partitions. If you provide a lower bound of
> 1927-04-05 (this gets translated to -15611), and an upper bound of 2020-10-27
> (translated to 18563), Spark determines the stride size as follows:
>
> (18563L / 1000L) - (-15611 / 1000L) = 33
> Starting from the lower bound, doing 998 strides of 33, you end up at
> 2017-06-05 (17323). This is over 3 years of extra data that will go into the
> last partition, and depending on the shape of the data could cause a very
> long running task at the end of a job.
>
> Using the formula I'm proposing, you'd get:
> (18563L - -15611) / (1000L - 2) = 34
> This would put the upper bound at 2020-02-28 (18321), which is much closer to
> the original supplied upper bound. This is the best you can do to get as
> close as possible to the upper bound (without adjusting the number of
> partitions). For example, a stride size of 35 would go well past the supplied
> upper bound (over 2 years, 2022-11-22).
>
> In the above example, there is only a difference of 1 between the stride size
> using the current formula and the stride size using the proposed formula, but
> with greater distance between the lower and upper bounds, or a lower number
> of partitions, the difference can be much greater.
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