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If no other comments, I'll commit this? I'll leave it open for a bit longer
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Github user MaxGekk commented on the issue:
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@HyukjinKwon Thank you for your work on the PR. @cloud-fan @felixcheung
@dongjoon-hyun @gatorsmile Thanks for your reviews.
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Github user MaxGekk commented on the issue:
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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 h
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retest this please
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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 sq
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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 is
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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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Shar
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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?
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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 pr
Github user WenqianZhao commented on the issue:
https://github.com/apache/spark/pull/20899
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 questio
Github user AmplabJenkins commented on the issue:
https://github.com/apache/spark/pull/22901
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Github user SparkQA commented on the issue:
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Github user cloud-fan commented on the issue:
https://github.com/apache/spark/pull/22892
LGTM except some minor comments
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Github user cloud-fan commented on a diff in the pull request:
https://github.com/apache/spark/pull/22892#discussion_r229672667
--- Diff:
sql/hive/src/test/scala/org/apache/spark/sql/hive/HiveShowCreateTableSuite.scala
---
@@ -0,0 +1,198 @@
+/*
+ * Licensed to the Apache S
Github user asfgit closed the pull request at:
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Github user cloud-fan commented on a diff in the pull request:
https://github.com/apache/spark/pull/22892#discussion_r229671459
--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/execution/command/tables.scala ---
@@ -1063,21 +1067,19 @@ case class ShowCreateTableCommand(table:
Github user HyukjinKwon commented on the issue:
https://github.com/apache/spark/pull/22895
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Github user SparkQA commented on the issue:
https://github.com/apache/spark/pull/22898
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