[ https://issues.apache.org/jira/browse/SPARK-17074?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15570366#comment-15570366 ]
Zhenhua Wang edited comment on SPARK-17074 at 10/22/16 12:52 PM:
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Well, I've got stuck here for a few days. I went through the QuantileSummaries paper and our code in Spark, and I still don't have any clue how to implement the second method and get its bounds.
So I decide to adopt the first method for now, such that it won't block our progress on CBO work. We can implement the other one in the future.
A PR for a new agg function for counting ndv's of multiple intervals is already sent.
was (Author: zenwzh):
Well, I've got stuck here for a few days. I went through the QuantileSummaries paper and our code in Spark, and I still don't have any clue how to implement the second method and get its bounds.
So I decide to adopt the first method for now, such that it won't block our progress on CBO work. We can implement the other one in the future.
A PR for a new agg function for string histogram (equi-width) is already sent. I'll start to work on this one today and send a pr in the following days. Thanks!
> generate histogram information for column
> -----------------------------------------
>
> Key: SPARK-17074
> URL: https://issues.apache.org/jira/browse/SPARK-17074
> Project: Spark
> Issue Type: Sub-task
> Components: Optimizer
> Affects Versions: 2.0.0
> Reporter: Ron Hu
>
> We support two kinds of histograms:
> - Equi-width histogram: We have a fixed width for each column interval in the histogram. The height of a histogram represents the frequency for those column values in a specific interval. For this kind of histogram, its height varies for different column intervals. We use the equi-width histogram when the number of distinct values is less than 254.
> - Equi-height histogram: For this histogram, the width of column interval varies. The heights of all column intervals are the same. The equi-height histogram is effective in handling skewed data distribution. We use the equi- height histogram when the number of distinct values is equal to or greater than 254.
> We first use [SPARK-18000] and [SPARK-17881] to compute equi-width histograms (for both numeric and string types) or endpoints of equi-height histograms (for numeric type only). Then, if we get endpoints of a equi-height histogram, we need to compute ndv's between those endpoints by [SPARK-17997] to form the equi-height histogram.
> This Jira incorporates three Jiras mentioned above to support needed aggregation functions. We need to resolve them before this one.
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