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Github user zsxwing commented on the issue:
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Thanks! Merging to master and 2.1.
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Github user viirya commented on a diff in the pull request:
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--- Diff:
core/src/main/scala/org/apache/spark/storage/memory/MemoryStore.scala ---
@@ -331,7 +332,7 @@ private[spark] class MemoryStore(
var
Github user viirya commented on a diff in the pull request:
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--- Diff:
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@@ -78,6 +80,7 @@ private[spark] class TorrentBroadcast[T: ClassTag](obj:
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Github user felixcheung commented on a diff in the pull request:
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--- Diff: R/pkg/R/utils.R ---
@@ -851,3 +851,12 @@ rbindRaws <- function(inputData){
out[!rawcolumns] <- lapply(out[!rawcolumns], unlist)
Github user cloud-fan commented on the issue:
https://github.com/apache/spark/pull/16030
the new behavior LGTM, but I'm not sure if we still need to keep the old
behavior
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LGTM
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Github user uncleGen commented on a diff in the pull request:
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--- Diff:
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@@ -90,6 +91,10 @@ private[spark] class EventLoggingListener(
Github user dongjoon-hyun commented on the issue:
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Do you mean to replace the current whole `TableReader.scala` which was
introduced in SPARK-1251 ? I guessed Spark chose this direct access approach
for the performance issue at that time.
Github user uncleGen commented on a diff in the pull request:
https://github.com/apache/spark/pull/15915#discussion_r9169
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Yes, I'll do that but the test failures here are different. I'm still to
figure out the root cause.
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Github user cloud-fan commented on the issue:
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hi @kapilsingh5050 can you also include
https://github.com/apache/spark/pull/16244? It does fix the maven tests.
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Github user gatorsmile commented on the issue:
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LGTM
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Github user gatorsmile commented on a diff in the pull request:
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--- Diff:
sql/hive/src/main/scala/org/apache/spark/sql/hive/execution/InsertIntoHiveTable.scala
---
@@ -121,21 +121,61 @@ case class
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--- Diff:
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@@ -121,21 +121,61 @@ case class InsertIntoHiveTable(
Github user JoshRosen commented on a diff in the pull request:
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--- Diff: core/src/main/scala/org/apache/spark/executor/Executor.scala ---
@@ -432,6 +458,78 @@ private[spark] class Executor(
}
/**
Github user JoshRosen commented on the issue:
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@lins05, I'll see if there's a way to get a nicer executor exit status to
be reported back to the driver.
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Github user JoshRosen commented on a diff in the pull request:
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--- Diff: core/src/main/scala/org/apache/spark/executor/Executor.scala ---
@@ -432,6 +458,78 @@ private[spark] class Executor(
}
/**
Github user cloud-fan commented on the issue:
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Is there any high-level API that we can use to read hive tables? The
current hive table reader is so low-level that we have to support features like
`skip.header.line.count`, and I think it
Github user viirya commented on a diff in the pull request:
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--- Diff:
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---
@@ -514,6 +514,25 @@ case class OptimizeCodegen(conf:
GitHub user wangyum opened a pull request:
https://github.com/apache/spark/pull/16252
[SPARK-18827][Core] Fix cannot read broadcast on disk
## What changes were proposed in this pull request?
Fix cannot read broadcast on disk
## How was this patch tested?
Add
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retest this please
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[SPARK-18826][SS]Add 'newestFirst' option to FileStreamSource
## What changes were proposed in this pull request?
When starting a stream with a lot of backfill and maxFilesPerTrigger, the
Github user shivaram commented on a diff in the pull request:
https://github.com/apache/spark/pull/16248#discussion_r91883327
--- Diff: R/pkg/R/utils.R ---
@@ -851,3 +851,12 @@ rbindRaws <- function(inputData){
out[!rawcolumns] <- lapply(out[!rawcolumns], unlist)
out
Github user shivaram commented on a diff in the pull request:
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--- Diff: R/pkg/R/install.R ---
@@ -104,7 +113,12 @@ install.spark <- function(hadoopVersion = "2.7",
mirrorUrl = NULL,
if (tarExists && !overwrite)
Github user shivaram commented on the issue:
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Can we open a JIRA for this ? Its good to track this change
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--- Diff: examples/src/main/r/native-r-package.R ---
@@ -0,0 +1,68 @@
+#
+# Licensed to the Apache Software Foundation (ASF) under one or more
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Github user rxin commented on a diff in the pull request:
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--- Diff:
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---
@@ -514,6 +514,25 @@ case class OptimizeCodegen(conf:
Github user viirya commented on a diff in the pull request:
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--- Diff:
sql/catalyst/src/main/java/org/apache/spark/sql/catalyst/expressions/codegen/BufferHolder.java
---
@@ -57,6 +60,12 @@ public
Github user viirya commented on a diff in the pull request:
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--- Diff:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/complexTypeCreator.scala
---
@@ -56,33 +58,93 @@ case class
Github user daisukebe commented on the issue:
https://github.com/apache/spark/pull/16195
@vanzin , 2.0 already has this capability per
https://issues.apache.org/jira/browse/SPARK-529, thus my patch targets on 1.6.
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Github user yanboliang commented on a diff in the pull request:
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--- Diff: docs/sparkr.md ---
@@ -472,21 +472,17 @@ should fit in a single machine. If that is not the
case they can do something li
`dapply`
Github user viirya commented on a diff in the pull request:
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--- Diff:
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---
@@ -18,8 +18,11 @@
package
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@@ -18,8 +18,11 @@
package
Github user uncleGen commented on a diff in the pull request:
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--- Diff: core/src/main/scala/org/apache/spark/memory/MemoryManager.scala
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@@ -223,8 +222,10 @@ private[spark] abstract class MemoryManager(
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Github user xuanyuanking commented on a diff in the pull request:
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--- Diff:
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@@ -105,6 +111,7 @@ object HiveCatalogMetrics extends Source {
Github user dongjoon-hyun commented on the issue:
https://github.com/apache/spark/pull/14638
Thank you so much, @jamartinh , @srowen , @HyukjinKwon , and @gatorsmile .
We can distinguish the two existing problems separately here.
First, **a)** Spark returns incorrect
Github user kiszk commented on the issue:
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I am thinking about an simpler approach. However, it is fine to close for
now.
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Github user YuhuWang2002 commented on the issue:
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retest this please
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Github user cloud-fan commented on the issue:
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the test is good now
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Github user winningsix commented on the issue:
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@yaooqinn yes, the validation is working on server side.
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Github user uncleGen commented on the issue:
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@srowen Sorry for the delay, I will update it as soon as possible on the
basis of comments.
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Github user uncleGen commented on the issue:
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@vanzin Sorry for the delay, I will update as soon as possible on the basis
of your comments.
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Github user michalsenkyr commented on the issue:
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Possible optimization: Instead of conversions using `to`, we can use
`Builder`s. This way we could get rid of the conversion overhead. This would
require adding a new codegen method that would
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@srowen completed.
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https://github.com/apache/spark/pull/16180#discussion_r91865764
--- Diff: docs/programming-guide.md ---
@@ -1345,14 +1345,17 @@ therefore be efficiently supported in parallel.
They can be used to implement co
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