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--- Diff: sql/core/src/test/scala/org/apache/spark/sql/DatasetSuite.scala
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--- Diff: core/src/main/scala/org/apache/spark/deploy/SparkSubmit.scala ---
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[MINOR][BUILD] Remove *.crc from .gitignore
## What changes were proposed in this pull request?
Remove *.crc from .gitignore as there are actual .crc files in the test
source dirs and IJ
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*:*_2.11
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Github user LiehuoChen commented on the issue:
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Hi HyukjinKwon,
Thanks for all the works to try to make the Jenkin test pass.
I patched this PR to spark 2.4, and anything works fine but failed in
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Github user cloud-fan commented on the issue:
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since this PR only touches mima, and the jenkins already passed the mima
check, I'm going to merge it to master, thanks!
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LGTM. Thanks!
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BTW can you include a simple benchmark to show this problem? e.g. just run
a query in spark-shell, and post the result before and after this PR.
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I'd like to merge this simple PR first, to address the performance problem
(unnecessary subquery execution).
Let's create a new ticket for subquery filter pushing to data source, and
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thanks, merging to master!
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cc @jiangxb1987 Could you take a look at this?
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--- Diff: R/pkg/R/SQLContext.R ---
@@ -172,36 +257,72 @@ getDefaultSqlSource <- function() {
createDataFrame <- function(data, schema = NULL,
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@srowen Great thanks for your guidance, address all your suggestion in
ff234d3 and update the record table in
https://github.com/apache/spark/pull/22989#issuecomment-437939830.
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Yes. The `filePartitions` are the same as the bucket number when
`BucketedRead`:
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> The reason is that each bucket file is too big
Can you elaborate please? Is it because we don't chunk each file into
multiple splits when we read bucketed table?
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--- Diff: project/MimaExcludes.scala ---
@@ -164,7 +212,50 @@ object MimaExcludes {
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merged to master/2.4
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thx, but DO NOT MERGE - there's some nasty bug I'm still investigating..
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Looks fine to me. adding @cloud-fan and @hvanhovell
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--- Diff:
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@@ -469,7 +471,21 @@ abstract class TreeNode[BaseType <:
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--- Diff: R/pkg/R/sparkR.R ---
@@ -283,6 +283,10 @@ sparkR.session <- function(
enableHiveSupport = TRUE,
...) {
+ if
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--- Diff: docs/index.md ---
@@ -31,7 +31,8 @@ Spark runs on both Windows and UNIX-like systems (e.g.
Linux, Mac OS). It's easy
locally on one
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--- Diff: docs/index.md ---
@@ -31,7 +31,8 @@ Spark runs on both Windows and UNIX-like systems (e.g.
Linux, Mac OS). It's easy
locally on one
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--- Diff: R/WINDOWS.md ---
@@ -3,7 +3,7 @@
To build SparkR on Windows, the following steps are required
1. Install R (>= 3.1) and
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In this way, we could postpone R upgrade after Spark 3.0.0 release in
Jenkins, and could still test the deprecated R version 3.1.
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