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@HyukjinKwon Thank you for following up work on the PR. @cloud-fan @viirya
@maropu Thanks for your reviews.
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[SPARK-25896][CORE][WIP] Accumulator should only be updated once for each
successful task in shuffle map stage
## What changes were proposed in this pull request?
This is a followup of
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retest this please
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I will fix the build error.
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> is there anything blocked by this? I agree this is a good feature, but it
asks the data source to provide a new ability, which may become a problem when
migrating file sources to data source v2.
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Github user srowen commented on the issue:
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I don't think BLAS matters here as these are all vector-vector operations
and f2jblas is used directly (i.e. stays in the JVM).
Are all the vectors dense? I suppose I'm still surprised if
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Github user srowen commented on the issue:
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That sounds like a good idea. I wonder if it's safe to back-port to
2.4/2.3? should be if it's just a maintenance release.
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I don't think this tests something about the correctness of Spark though. I
am not sure this is worth it.
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I also would not expect updating an immutable data structure to be faster.
Building a map once from tuples at the end seems better than rebuilding a map
each time. Under the hood the immutable map
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is there anything blocked by this? I agree this is a good feature, but it
asks the data source to provide a new ability, which may become a problem when
migrating file sources to data source v2.
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that sounds more reasonable and a better implementation, thanks.
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Thanks for the remark above. I have checked scala.mutable.Map
performance, it is essentially better. For some cases, speed up is up to 2
times I will update the benchmark and the PR soon.
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[SPARK-25895][Core]Adding testcase to compare Lz4 and Zstd compression
## What changes were proposed in this pull request?
Added a UT to verify Zstd compression algorithm has better
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@gatorsmile @viirya @cloud-fan @dbtsai your thoughts?
cc @dongjoon-hyun for ORC file format perspective.
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[SPARK-25894][SQL] Add a ColumnarFileFormat type which returns the column
count for a given schema
(link to Jira: https://issues.apache.org/jira/browse/SPARK-25894)
## What changes were
Github user WenqianZhao commented on the issue:
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By the way, @ankurdave , hi, I'm very curious about why you use delta
instead of just newPR as the message. Is that for better performance or just at
chance? Could you please answer this
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LGTM except some minor comments
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Github user SparkQA commented on the issue:
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