Github user gatorsmile commented on the issue:
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LGTM except above comments. This PR does not change anything else but just
clean the implementation of existing Data Source V2 API
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--- Diff:
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@@ -56,6 +56,12 @@ class ChunkedByteBufferSuite extends SparkFunSuite {
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Github user dongjoon-hyun commented on the issue:
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Thank you for review, @HyukjinKwon , @holdenk , @bersprockets .
I didn't notice SPARK-23776 when I chose SPARK-23853 . I think we can merge
those PRs now.
@bersprockets . Coul
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--- Diff: docs/sql-programming-guide.md ---
@@ -1805,12 +1805,13 @@ working with timestamps in `pandas_udf`s to get the
best performance, see
Github user rxin commented on a diff in the pull request:
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--- Diff: docs/sql-programming-guide.md ---
@@ -1805,12 +1805,13 @@ working with timestamps in `pandas_udf`s to get the
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- Si
Github user dilipbiswal commented on the issue:
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@maropu So with the fix, if the query predicate contains an scalar subquery
expression, then that expression is not considered for partition pruning. For
example, if the predicate was , part_ke
Github user advancedxy commented on the issue:
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> We should not do these 2 things together, and to me the second one is way
simpler to get in and we should do it first.
Agreed. For the scope of this pr, let's get killed tasks's accumul
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@maropu Ok. It sounds reasonable to me
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> For example user may want to record CPU time for every task and get the
total CPU time for the application.
The problem is, shall we allow end users to collect metrics via
accumulators?
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One question; we have no risk to miss any partition pruning by this fix?
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Plz add `[CORE]` in the title.
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Have you checked the @srowen 's comment?
https://github.com/apache/spark/pull/18949#issuecomment-323354674
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LGTM, and nice UT.
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@manbuyun you need to add the unit test into `ChunkedByteBufferSuite.scala`
and push a new commit.
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[SPARK-24109] Remove class SnappyOutputStreamWrapper
JIRA:
https://issues.apache.org/jira/browse/SPARK-24109?jql=text%20~%20%22SnappyOutputStreamWrapper%22
Wrapper over `SnappyOutputStrea
Github user advancedxy commented on the issue:
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> However, I don't agree user side accumulators should get updates from
killed tasks, that changes the semantic of accumulators. And I don't think
end-users need to care about killed tasks. Simil
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Thank you for review and merge, @cloud-fan !
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test("writeFully() does not affect original buffer's position") {
val chunkedByteBuffer = new
ChunkedByteBuffer(Array(ByteBuffer.allocate(80*1024*1024)))
chunkedByteBuffer.writeFul
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Would it be possible to add a unit test?
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overall good, @jkbradley Would you mind take a look ?
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I do agree task killed event should carry metrics update, as it's
reasonable to count killed tasks for something like how many bytes were read
from files.
However, I don't agree user side
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[SPARK-24107] ChunkedByteBuffer.writeFully method has not reset the limit
value
JIRA Issue:
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Chunk
Github user advancedxy commented on the issue:
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I add a note for accumulator update. Please comment if more document is
needed.
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LGTM, merging to master!
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plz add `[SQL]` in the title.
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Ah, ok. Thanks!
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Also this is a yarn, not core, change.
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The change is fail to build, please fix it.
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sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/TypeCoercion.scala
---
@@ -782,6 +782,22 @@ object TypeCoercion {
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Github user HyukjinKwon commented on the issue:
https://github.com/apache/spark/pull/21157
Please go ahead if there's another approach to avoid to remove but fix it.
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Github user HyukjinKwon commented on the issue:
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ok to test
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Github user HyukjinKwon commented on the issue:
https://github.com/apache/spark/pull/21107
Thank you for reviewing this @bersprockets, @viirya, @BryanCutler,
@icexelloss and @felixcheung.
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Github user bersprockets commented on a diff in the pull request:
https://github.com/apache/spark/pull/21169#discussion_r184565093
--- Diff: sql/core/src/test/resources/sql-tests/inputs/datetime.sql ---
@@ -27,3 +27,8 @@ select current_date = current_date(), current_timestamp =
cur
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