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Github user HyukjinKwon commented on the issue:
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Thanks @yhuai! I just addressed your comments.
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[SPARK-16432] Empty blocks fail to serialize due to assert in
ChunkedByteBuffer
## What changes were proposed in this pull request?
It's possible to also change the callers to not pass in em
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--- Diff:
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@@ -341,63 +327,115 @@ public UnsafeArrayData copy
Github user cloud-fan commented on a diff in the pull request:
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--- Diff:
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@@ -0,0 +1,215 @@
+/*
+ * Licensed t
Github user keypointt commented on a diff in the pull request:
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Github user cloud-fan commented on the issue:
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LGTM except some minor comments, it's pretty close! One easy-to-ignore
comment: https://github.com/apache/spark/pull/13680/files#r69849567
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Github user rxin commented on the issue:
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@jurriaan should this be called quoteAll rather than escapeAll?
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Ping!
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Github user dongjoon-hyun commented on the issue:
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Hi, @shivaram .
Now, it's ready for review again.
Please let me know if there is something to do more.
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GitHub user zsxwing opened a pull request:
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[SPARK-16433][SQL]Improve StreamingQuery.explain when no data arrives
## What changes were proposed in this pull request?
Display `No physical plan. Waiting for data.` instead of `N/A` for
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LGTM. Thanks @dongjoon-hyun -- Merging this to master, branch-2.0
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For this one I think we should consider supporting only foldable literals
for the path component.
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--- Diff:
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@@ -403,17 +400,18 @@ object CreateDataSourceTab
GitHub user husseinhazimeh opened a pull request:
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[SPARK-16431] [ML] Add a unified method that accepts single instances to
feature transformers and predictors
## What changes were proposed in this pull request?
Current feature transform
Github user jerryshao commented on the issue:
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Thanks a lot @tgravescs and @vanzin for your suggestions, I will change the
codes accordingly, greatly appreciate your comments.
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Can one of the admins verify this patch?
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[SPARK-16434][SQL][WIP] Avoid record-per type dispatch in JSON when reading
## What changes were proposed in this pull request?
(Please fill in changes proposed in this fix)
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@mengxr @sethah can you review this patch?
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Also - rather than having concrete implementations for all of these, why
don't we use RuntimeReplaceable?
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Github user janplus commented on a diff in the pull request:
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Github user viirya commented on the issue:
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@gatorsmile This is the benchmark results. No significant difference.
Before this patch:
Java HotSpot(TM) 64-Bit Server VM 1.8.0_71-b15 on Linux
3.19.0-25-generic
Intel(R
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--- Diff: yarn/src/main/scala/org/apache/spark/deploy/yarn/Client.scala ---
@@ -390,8 +390,9 @@ private[spark] class Client(
// Upload Spark and th
Github user janplus commented on the issue:
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cc @cloud-fan @rxin @liancheng
I did optimization for Literal `part`, so we don't need to check for every
row. But since we may not assume in all circumstances the `part` is Literal, I
keep the
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cc @tdas
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*/
Github user viirya commented on the issue:
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Python UDT in python side only serializes the python data to sql type
defined in the Python UDT. The problem now is happened at the serialization to
row in java side on the serialized python data. I
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I pushed a new change to this. We now have better error messages and test
coverage for those. These expressions also now require foldable paths.
I also changed the test values to make su
Github user gatorsmile commented on the issue:
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Great! Around 5% performance penalty looks OK to me. Maybe we can send the
code changes to the performance team for seeing TPC-DS improvement. CC @jfchen
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[SPARK-16436][SQL] checkEvaluation support NaN and RuntimeReplaceable
## What changes were proposed in this pull request?
This small patch modifies ExpressionEvalHelper. checkEvaluation to s
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Github user SparkQA commented on the issue:
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Github user viirya commented on the issue:
https://github.com/apache/spark/pull/13701
@gatorsmile You know that the benchmark results will not the same every
time even you run it with the same codes. If the difference is under a small
range, we can assume they have no significant diff
Github user viirya commented on the issue:
https://github.com/apache/spark/pull/13701
@gatorsmile BTW, if the TPC-DS performance is measured with 2.0 codebase,
this should benefit the performance.
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Github user rxin commented on the issue:
https://github.com/apache/spark/pull/14095
Can you fix Python?
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Github user gatorsmile commented on the issue:
https://github.com/apache/spark/pull/13701
@viirya If you run multiple times and still see 5% performance difference,
you can confirm the penalty is around 5%. However, this might also depend on
the other factors, e.g., the total time. Th
Github user SparkQA commented on the issue:
https://github.com/apache/spark/pull/14102
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Github user viirya commented on the issue:
https://github.com/apache/spark/pull/13701
@gatorsmile I think the times I run the benchmark is not enough to confirm
there is 5% performance difference. But I think it is not important here
because we don't want to measure the exact performa
Github user cloud-fan commented on a diff in the pull request:
https://github.com/apache/spark/pull/13890#discussion_r70024013
--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/execution/ExistingRDD.scala ---
@@ -74,13 +74,71 @@ object RDDConversions {
}
}
Github user cloud-fan commented on the issue:
https://github.com/apache/spark/pull/13890
LGTM, cc @liancheng to take another look
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Github user cloud-fan commented on a diff in the pull request:
https://github.com/apache/spark/pull/14103#discussion_r70024354
--- Diff:
sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/expressions/ExpressionEvalHelper.scala
---
@@ -41,7 +41,12 @@ trait ExpressionEvalHelp
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