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Zhenhua Wang commented on SPARK-16283:
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[~erlu] I think it's been made clear from above discussions,
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chenerlu commented on SPARK-16283:
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Hi, I am little confused about percentile_approx, is it different
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Apache Spark commented on SPARK-16283:
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User 'lw-lin' has created a pull request for this issue:
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Apache Spark commented on SPARK-16283:
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User 'clockfly' has created a pull request for this issue:
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Sean Zhong commented on SPARK-16283:
Created a sub-task to move QuantileSummaries to package
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Apache Spark commented on SPARK-16283:
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User 'lw-lin' has created a pull request for this issue:
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Apache Spark commented on SPARK-16283:
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User 'lw-lin' has created a pull request for this issue:
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Apache Spark commented on SPARK-16283:
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User 'lw-lin' has created a pull request for this issue:
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Apache Spark commented on SPARK-16283:
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User 'lw-lin' has created a pull request for this issue:
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Liwei Lin commented on SPARK-16283:
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Thanks for the clarification. I'm working on this one, thanks!
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Reynold Xin commented on SPARK-16283:
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We just need a function, and doesn't need it to be identical
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Tim Hunter commented on SPARK-16283:
Are we trying to reproduce Hive's results here? In this case,
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Kai Jiang commented on SPARK-16283:
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I also noticed that there is an inconsistency between hive's
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Liwei Lin commented on SPARK-16283:
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Hive's percentile_approx implementation computes approximate
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Tim Hunter commented on SPARK-16283:
We should, the algorithm picked is optimized for this use case.
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Reynold Xin commented on SPARK-16283:
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[~thunterdb] can we use your implementation for
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