[GitHub] spark pull request: SPARK-2532: Minimal shuffle consolidation fixe...
Github user mateiz commented on the pull request: https://github.com/apache/spark/pull/1678#issuecomment-50930691 @aarondav can you update the name of this PR to reference this sub-task JIRA instead: https://issues.apache.org/jira/browse/SPARK-2791? --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. ---
[GitHub] spark pull request: SPARK-2532: Minimal shuffle consolidation fixe...
Github user SparkQA commented on the pull request: https://github.com/apache/spark/pull/1678#issuecomment-50927468 QA results for PR 1678:- This patch PASSES unit tests.- This patch merges cleanly- This patch adds no public classesFor more information see test ouptut:https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/17689/consoleFull --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. ---
[GitHub] spark pull request: SPARK-2532: Minimal shuffle consolidation fixe...
Github user SparkQA commented on the pull request: https://github.com/apache/spark/pull/1678#issuecomment-50921522 QA tests have started for PR 1678. This patch merges cleanly. View progress: https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/17689/consoleFull --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. ---
[GitHub] spark pull request: SPARK-2532: Minimal shuffle consolidation fixe...
Github user mateiz commented on the pull request: https://github.com/apache/spark/pull/1678#issuecomment-50921018 Jenkins, test this please --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. ---
[GitHub] spark pull request: SPARK-2532: Minimal shuffle consolidation fixe...
Github user mridulm commented on a diff in the pull request:
https://github.com/apache/spark/pull/1678#discussion_r15701250
--- Diff:
core/src/main/scala/org/apache/spark/storage/BlockObjectWriter.scala ---
@@ -147,28 +147,36 @@ private[spark] class DiskBlockObjectWriter(
override def isOpen: Boolean = objOut != null
- override def commit(): Long = {
+ override def commitAndClose(): Unit = {
if (initialized) {
// NOTE: Because Kryo doesn't flush the underlying stream we
explicitly flush both the
// serializer stream and the lower level stream.
objOut.flush()
bs.flush()
- val prevPos = lastValidPosition
- lastValidPosition = channel.position()
- lastValidPosition - prevPos
-} else {
- // lastValidPosition is zero if stream is uninitialized
- lastValidPosition
+ close()
}
+finalPosition = file.length()
}
- override def revertPartialWrites() {
-if (initialized) {
- // Discard current writes. We do this by flushing the outstanding
writes and
- // truncate the file to the last valid position.
- objOut.flush()
- bs.flush()
- channel.truncate(lastValidPosition)
+ // Discard current writes. We do this by flushing the outstanding writes
and then
+ // truncating the file to its initial position.
+ override def revertPartialWritesAndClose() {
+try {
+ if (initialized) {
+objOut.flush()
+bs.flush()
+close()
+ }
+
+ val truncateStream = new FileOutputStream(file, true)
+ try {
+truncateStream.getChannel.truncate(initialPosition)
+ } finally {
+truncateStream.close()
+ }
+} catch {
+ case e: Exception =>
+logError("Uncaught exception while reverting partial writes to
file " + file, e)
--- End diff --
Ah, did not notice that the "if (initialized)" did not include the truncate
call !
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[GitHub] spark pull request: SPARK-2532: Minimal shuffle consolidation fixe...
Github user aarondav commented on a diff in the pull request:
https://github.com/apache/spark/pull/1678#discussion_r15684100
--- Diff:
core/src/main/scala/org/apache/spark/storage/BlockObjectWriter.scala ---
@@ -147,28 +147,36 @@ private[spark] class DiskBlockObjectWriter(
override def isOpen: Boolean = objOut != null
- override def commit(): Long = {
+ override def commitAndClose(): Unit = {
--- End diff --
Removing close() actually now requires a very minor refactor of
ExternalSorter for the `objectsWritten == 0` case -- I'd actually rather not
risk it in this PR.
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[GitHub] spark pull request: SPARK-2532: Minimal shuffle consolidation fixe...
Github user aarondav commented on a diff in the pull request:
https://github.com/apache/spark/pull/1678#discussion_r15683958
--- Diff:
core/src/main/scala/org/apache/spark/storage/BlockObjectWriter.scala ---
@@ -147,28 +147,36 @@ private[spark] class DiskBlockObjectWriter(
override def isOpen: Boolean = objOut != null
- override def commit(): Long = {
+ override def commitAndClose(): Unit = {
if (initialized) {
// NOTE: Because Kryo doesn't flush the underlying stream we
explicitly flush both the
// serializer stream and the lower level stream.
objOut.flush()
bs.flush()
- val prevPos = lastValidPosition
- lastValidPosition = channel.position()
- lastValidPosition - prevPos
-} else {
- // lastValidPosition is zero if stream is uninitialized
- lastValidPosition
+ close()
}
+finalPosition = file.length()
}
- override def revertPartialWrites() {
-if (initialized) {
- // Discard current writes. We do this by flushing the outstanding
writes and
- // truncate the file to the last valid position.
- objOut.flush()
- bs.flush()
- channel.truncate(lastValidPosition)
+ // Discard current writes. We do this by flushing the outstanding writes
and then
+ // truncating the file to its initial position.
+ override def revertPartialWritesAndClose() {
+try {
+ if (initialized) {
+objOut.flush()
+bs.flush()
+close()
+ }
+
+ val truncateStream = new FileOutputStream(file, true)
+ try {
+truncateStream.getChannel.truncate(initialPosition)
+ } finally {
+truncateStream.close()
+ }
+} catch {
+ case e: Exception =>
+logError("Uncaught exception while reverting partial writes to
file " + file, e)
--- End diff --
I'm not certain I understand. The situation I am imagining is that we
commit to the first Writer, then the second one fails. In HashShuffleWriter, we
will then call revertPartialWritesAndClose() on all Writers, causing us to
revert all the changes back to "initialPosition", which should revert even the
committed data.
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[GitHub] spark pull request: SPARK-2532: Minimal shuffle consolidation fixe...
Github user mridulm commented on a diff in the pull request:
https://github.com/apache/spark/pull/1678#discussion_r15683224
--- Diff:
core/src/main/scala/org/apache/spark/storage/BlockObjectWriter.scala ---
@@ -147,28 +147,36 @@ private[spark] class DiskBlockObjectWriter(
override def isOpen: Boolean = objOut != null
- override def commit(): Long = {
+ override def commitAndClose(): Unit = {
--- End diff --
When I merged the sort patch, and modified EAOM, it was simply replace
close with commitAndClose.
commitAndClose should be semantically equivalent to close actually.
It is not equivalent to commit() - but we want to remove that :-)
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[GitHub] spark pull request: SPARK-2532: Minimal shuffle consolidation fixe...
Github user mridulm commented on a diff in the pull request:
https://github.com/apache/spark/pull/1678#discussion_r15683205
--- Diff:
core/src/main/scala/org/apache/spark/storage/BlockObjectWriter.scala ---
@@ -147,28 +147,36 @@ private[spark] class DiskBlockObjectWriter(
override def isOpen: Boolean = objOut != null
- override def commit(): Long = {
+ override def commitAndClose(): Unit = {
if (initialized) {
// NOTE: Because Kryo doesn't flush the underlying stream we
explicitly flush both the
// serializer stream and the lower level stream.
objOut.flush()
bs.flush()
- val prevPos = lastValidPosition
- lastValidPosition = channel.position()
- lastValidPosition - prevPos
-} else {
- // lastValidPosition is zero if stream is uninitialized
- lastValidPosition
+ close()
}
+finalPosition = file.length()
}
- override def revertPartialWrites() {
-if (initialized) {
- // Discard current writes. We do this by flushing the outstanding
writes and
- // truncate the file to the last valid position.
- objOut.flush()
- bs.flush()
- channel.truncate(lastValidPosition)
+ // Discard current writes. We do this by flushing the outstanding writes
and then
+ // truncating the file to its initial position.
+ override def revertPartialWritesAndClose() {
+try {
+ if (initialized) {
+objOut.flush()
+bs.flush()
+close()
+ }
+
+ val truncateStream = new FileOutputStream(file, true)
+ try {
+truncateStream.getChannel.truncate(initialPosition)
+ } finally {
+truncateStream.close()
+ }
+} catch {
+ case e: Exception =>
+logError("Uncaught exception while reverting partial writes to
file " + file, e)
--- End diff --
I meant the former case : close on a writer fails with an exception; while
earlier streams succeeded.
So now we have some writers which have committed data (which is not removed
by subsequent revert) while others are reverted.
On the face of it, I agree, it should not cause issues : but then since the
expectation from this class is never enforced; and so can silently fail.
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[GitHub] spark pull request: SPARK-2532: Minimal shuffle consolidation fixe...
Github user aarondav commented on a diff in the pull request:
https://github.com/apache/spark/pull/1678#discussion_r15682607
--- Diff:
core/src/main/scala/org/apache/spark/shuffle/hash/HashShuffleWriter.scala ---
@@ -120,8 +121,7 @@ private[spark] class HashShuffleWriter[K, V](
private def revertWrites(): Unit = {
if (shuffle != null && shuffle.writers != null) {
for (writer <- shuffle.writers) {
-writer.revertPartialWrites()
-writer.close()
+writer.revertPartialWritesAndClose()
--- End diff --
Revert actually doesn't throw, per its (updated) comment.
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[GitHub] spark pull request: SPARK-2532: Minimal shuffle consolidation fixe...
Github user aarondav commented on a diff in the pull request:
https://github.com/apache/spark/pull/1678#discussion_r15682605
--- Diff:
core/src/main/scala/org/apache/spark/storage/BlockObjectWriter.scala ---
@@ -147,28 +147,36 @@ private[spark] class DiskBlockObjectWriter(
override def isOpen: Boolean = objOut != null
- override def commit(): Long = {
+ override def commitAndClose(): Unit = {
--- End diff --
Absolutely -- I did not do that in this patch because ExternalAppendOnlyMap
did a close without a commit, which is a fix outside of the scope of this PR,
but definitely one that should be made.
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[GitHub] spark pull request: SPARK-2532: Minimal shuffle consolidation fixe...
Github user aarondav commented on a diff in the pull request:
https://github.com/apache/spark/pull/1678#discussion_r15682590
--- Diff:
core/src/main/scala/org/apache/spark/storage/BlockObjectWriter.scala ---
@@ -147,28 +147,36 @@ private[spark] class DiskBlockObjectWriter(
override def isOpen: Boolean = objOut != null
- override def commit(): Long = {
+ override def commitAndClose(): Unit = {
if (initialized) {
// NOTE: Because Kryo doesn't flush the underlying stream we
explicitly flush both the
// serializer stream and the lower level stream.
objOut.flush()
bs.flush()
- val prevPos = lastValidPosition
- lastValidPosition = channel.position()
- lastValidPosition - prevPos
-} else {
- // lastValidPosition is zero if stream is uninitialized
- lastValidPosition
+ close()
}
+finalPosition = file.length()
}
- override def revertPartialWrites() {
-if (initialized) {
- // Discard current writes. We do this by flushing the outstanding
writes and
- // truncate the file to the last valid position.
- objOut.flush()
- bs.flush()
- channel.truncate(lastValidPosition)
+ // Discard current writes. We do this by flushing the outstanding writes
and then
+ // truncating the file to its initial position.
+ override def revertPartialWritesAndClose() {
+try {
+ if (initialized) {
+objOut.flush()
+bs.flush()
+close()
+ }
+
+ val truncateStream = new FileOutputStream(file, true)
+ try {
+truncateStream.getChannel.truncate(initialPosition)
+ } finally {
+truncateStream.close()
+ }
+} catch {
+ case e: Exception =>
+logError("Uncaught exception while reverting partial writes to
file " + file, e)
--- End diff --
Closed streams should not inherently throw (since we check `initialized`
before flushing and closing). However, we may be left with leftover data, as
you said. I don't see a way to prevent the possibility of that occurring, but
it should be possible to recover if users only rely on the returned
fileSegment().
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[GitHub] spark pull request: SPARK-2532: Minimal shuffle consolidation fixe...
Github user mridulm commented on a diff in the pull request:
https://github.com/apache/spark/pull/1678#discussion_r15682457
--- Diff:
core/src/main/scala/org/apache/spark/storage/BlockObjectWriter.scala ---
@@ -147,28 +147,36 @@ private[spark] class DiskBlockObjectWriter(
override def isOpen: Boolean = objOut != null
- override def commit(): Long = {
+ override def commitAndClose(): Unit = {
--- End diff --
We should remove close from the interface, and make it private to this
class btw.
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[GitHub] spark pull request: SPARK-2532: Minimal shuffle consolidation fixe...
Github user mridulm commented on a diff in the pull request:
https://github.com/apache/spark/pull/1678#discussion_r15682412
--- Diff:
core/src/main/scala/org/apache/spark/storage/BlockObjectWriter.scala ---
@@ -147,28 +147,36 @@ private[spark] class DiskBlockObjectWriter(
override def isOpen: Boolean = objOut != null
- override def commit(): Long = {
+ override def commitAndClose(): Unit = {
if (initialized) {
// NOTE: Because Kryo doesn't flush the underlying stream we
explicitly flush both the
// serializer stream and the lower level stream.
objOut.flush()
bs.flush()
- val prevPos = lastValidPosition
- lastValidPosition = channel.position()
- lastValidPosition - prevPos
-} else {
- // lastValidPosition is zero if stream is uninitialized
- lastValidPosition
+ close()
}
+finalPosition = file.length()
}
- override def revertPartialWrites() {
-if (initialized) {
- // Discard current writes. We do this by flushing the outstanding
writes and
- // truncate the file to the last valid position.
- objOut.flush()
- bs.flush()
- channel.truncate(lastValidPosition)
+ // Discard current writes. We do this by flushing the outstanding writes
and then
+ // truncating the file to its initial position.
+ override def revertPartialWritesAndClose() {
+try {
+ if (initialized) {
+objOut.flush()
+bs.flush()
+close()
+ }
+
+ val truncateStream = new FileOutputStream(file, true)
+ try {
+truncateStream.getChannel.truncate(initialPosition)
+ } finally {
+truncateStream.close()
+ }
+} catch {
+ case e: Exception =>
+logError("Uncaught exception while reverting partial writes to
file " + file, e)
--- End diff --
In the use of writers in HashShuffleWriter, it is possible for a closed
stream to be reverted (if some other stream's close failed for example).
In the above, that will leave this file with leftover data - I am not sure
what the impact of this would be.
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[GitHub] spark pull request: SPARK-2532: Minimal shuffle consolidation fixe...
Github user mridulm commented on a diff in the pull request:
https://github.com/apache/spark/pull/1678#discussion_r15682389
--- Diff:
core/src/main/scala/org/apache/spark/shuffle/hash/HashShuffleWriter.scala ---
@@ -120,8 +121,7 @@ private[spark] class HashShuffleWriter[K, V](
private def revertWrites(): Unit = {
if (shuffle != null && shuffle.writers != null) {
for (writer <- shuffle.writers) {
-writer.revertPartialWrites()
-writer.close()
+writer.revertPartialWritesAndClose()
--- End diff --
revert can throw exception : which will cause other writers to not revert.
We need to wrap it in try/catch, log and continue
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[GitHub] spark pull request: SPARK-2532: Minimal shuffle consolidation fixe...
Github user SparkQA commented on the pull request: https://github.com/apache/spark/pull/1678#issuecomment-50793796 QA results for PR 1678:- This patch PASSES unit tests.- This patch merges cleanly- This patch adds no public classesFor more information see test ouptut:https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/17585/consoleFull --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. ---
[GitHub] spark pull request: SPARK-2532: Minimal shuffle consolidation fixe...
Github user SparkQA commented on the pull request: https://github.com/apache/spark/pull/1678#issuecomment-50786593 QA tests have started for PR 1678. This patch merges cleanly. View progress: https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/17585/consoleFull --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. ---
[GitHub] spark pull request: SPARK-2532: Minimal shuffle consolidation fixe...
Github user aarondav commented on the pull request: https://github.com/apache/spark/pull/1678#issuecomment-50785949 Both prior failures are due to being unable to bind to ports, which sounds like leftover state from other jenkins runs (especially since they were two entirely disjoint sets of failed tests related to port binding). --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. ---
[GitHub] spark pull request: SPARK-2532: Minimal shuffle consolidation fixe...
Github user aarondav commented on the pull request: https://github.com/apache/spark/pull/1678#issuecomment-50785966 Jenkins, retest this please. --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. ---
[GitHub] spark pull request: SPARK-2532: Minimal shuffle consolidation fixe...
Github user SparkQA commented on the pull request: https://github.com/apache/spark/pull/1678#issuecomment-50724029 QA results for PR 1678:- This patch FAILED unit tests.- This patch merges cleanly- This patch adds no public classesFor more information see test ouptut:https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/17565/consoleFull --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. ---
[GitHub] spark pull request: SPARK-2532: Minimal shuffle consolidation fixe...
Github user SparkQA commented on the pull request: https://github.com/apache/spark/pull/1678#issuecomment-50718818 QA tests have started for PR 1678. This patch merges cleanly. View progress: https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/17565/consoleFull --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. ---
[GitHub] spark pull request: SPARK-2532: Minimal shuffle consolidation fixe...
Github user aarondav commented on the pull request: https://github.com/apache/spark/pull/1678#issuecomment-50718425 Jenkins, retest this please. --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. ---
[GitHub] spark pull request: SPARK-2532: Minimal shuffle consolidation fixe...
Github user SparkQA commented on the pull request: https://github.com/apache/spark/pull/1678#issuecomment-50718100 QA results for PR 1678:- This patch FAILED unit tests.- This patch merges cleanly- This patch adds no public classesFor more information see test ouptut:https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/17553/consoleFull --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. ---
[GitHub] spark pull request: SPARK-2532: Minimal shuffle consolidation fixe...
Github user SparkQA commented on the pull request: https://github.com/apache/spark/pull/1678#issuecomment-50714957 QA tests have started for PR 1678. This patch merges cleanly. View progress: https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/17553/consoleFull --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. ---
[GitHub] spark pull request: SPARK-2532: Minimal shuffle consolidation fixe...
Github user SparkQA commented on the pull request: https://github.com/apache/spark/pull/1678#issuecomment-50710747 QA results for PR 1678:- This patch FAILED unit tests.- This patch merges cleanly- This patch adds no public classesFor more information see test ouptut:https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/17537/consoleFull --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. ---
[GitHub] spark pull request: SPARK-2532: Minimal shuffle consolidation fixe...
Github user mateiz commented on the pull request: https://github.com/apache/spark/pull/1678#issuecomment-50706164 That's true, this is small enough to add back into branch-1.0 too. We should see if we can do the same for the rest of #1609 too (ideally I would like to merge that whole PR into branch-1.0, but I'm not sure how easy that is). --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. ---
[GitHub] spark pull request: SPARK-2532: Minimal shuffle consolidation fixe...
Github user witgo commented on the pull request: https://github.com/apache/spark/pull/1678#issuecomment-50706018 We can also merge it to 1.0 branch. --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. ---
[GitHub] spark pull request: SPARK-2532: Minimal shuffle consolidation fixe...
Github user aarondav commented on the pull request: https://github.com/apache/spark/pull/1678#issuecomment-50705532 @mridulm Please take a look if possible. @mateiz This now interacts with the ExternalSorter stuff, and it's possible it partially helps fix a serialization bug (since some serializers apparently write things during a close() after a flush()). --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. ---
[GitHub] spark pull request: SPARK-2532: Minimal shuffle consolidation fixe...
Github user SparkQA commented on the pull request: https://github.com/apache/spark/pull/1678#issuecomment-50705494 QA tests have started for PR 1678. This patch merges cleanly. View progress: https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/17537/consoleFull --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. ---
[GitHub] spark pull request: SPARK-2532: Minimal shuffle consolidation fixe...
Github user SparkQA commented on the pull request: https://github.com/apache/spark/pull/1678#issuecomment-50704906 QA results for PR 1678:- This patch FAILED unit tests.- This patch merges cleanly- This patch adds no public classesFor more information see test ouptut:https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/17535/consoleFull --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. ---
[GitHub] spark pull request: SPARK-2532: Minimal shuffle consolidation fixe...
Github user SparkQA commented on the pull request: https://github.com/apache/spark/pull/1678#issuecomment-50704721 QA tests have started for PR 1678. This patch merges cleanly. View progress: https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/17535/consoleFull --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. ---
[GitHub] spark pull request: SPARK-2532: Minimal shuffle consolidation fixe...
GitHub user aarondav opened a pull request: https://github.com/apache/spark/pull/1678 SPARK-2532: Minimal shuffle consolidation fixes All changes from this PR are by @mridulm and are drawn from his work in #1609. This patch is intended to fix all major issues related to shuffle file consolidation that @mridulm found, while minimizing changes to the code, with the hope that it may be more easily merged into 1.1. This patch is **not** intended as a replacement for #1609, which provides many additional benefits, including fixes to ExternalAppendOnlyMap, improvements to DiskBlockObjectWriter's API, and several new unit tests. If it is feasible to merge #1609 for the 1.1 deadline, that is a preferable option. You can merge this pull request into a Git repository by running: $ git pull https://github.com/aarondav/spark consol Alternatively you can review and apply these changes as the patch at: https://github.com/apache/spark/pull/1678.patch To close this pull request, make a commit to your master/trunk branch with (at least) the following in the commit message: This closes #1678 commit f298ac92f7df30f53636fca874c8bc6ed764af19 Author: Aaron Davidson Date: 2014-07-28T19:02:24Z SPARK-2532: Minimal shuffle consolidation fixes All changes from this PR are by @mridulm and are drawn from his work in #1609. This patch is intended to fix all major issues related to shuffle file consolidation that @mridulm found, while minimizing changes to the code, with the hope that it may be more easily merged into 1.1. This patch is **not** intended as a replacement for #1609, which provides many additional benefits, including fixes to ExternalAppendOnlyMap, improvements to DiskBlockObjectWriter's API, and several new unit tests. If it is feasible to merge #1609 for the 1.1 deadline, that is a preferable option. --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. ---
