Github user vanzin commented on the issue:
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I think I'm starting to understand what you're getting at, but I still
don't see why this has anything to do with the CGSB. What I understand from
your comment is that the EAM may reduce its target
Github user tgravescs commented on the issue:
https://github.com/apache/spark/pull/19047
test this please
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GitHub user dongjoon-hyun opened a pull request:
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[SPARK-21839][SQL] Support SQL config for ORC compression
## What changes were proposed in this pull request?
This PR aims to support `spark.sql.orc.compression.codec` like Parquet's
Github user sitalkedia commented on the issue:
https://github.com/apache/spark/pull/19048
That's not really true.
The EAM uses the `requestTotalExecutors` api to set the target for the
scheduler.
- 10 executors are running, each executor can run 4 tasks at max.
- 20
Github user gatorsmile commented on a diff in the pull request:
https://github.com/apache/spark/pull/18966#discussion_r135332868
--- Diff:
sql/catalyst/src/main/scala/org/apache/spark/sql/internal/SQLConf.scala ---
@@ -582,6 +582,15 @@ object SQLConf {
.intConf
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Github user vanzin commented on the issue:
https://github.com/apache/spark/pull/19048
> This is when things get out of sync because now the scheduler will set
the number of total executors needed from 4 to 1.
Have you actually observed that behavior?
The way I
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Github user gatorsmile commented on a diff in the pull request:
https://github.com/apache/spark/pull/18966#discussion_r135327262
--- Diff:
sql/catalyst/src/main/scala/org/apache/spark/sql/internal/SQLConf.scala ---
@@ -582,6 +582,15 @@ object SQLConf {
.intConf
Github user sitalkedia commented on the issue:
https://github.com/apache/spark/pull/19048
Looking at the scheduler and the dynamic executor allocator code, this is
what my understanding, correct me if I am wrong.
Let's say the dynamic executor allocator is ramping down the
Github user gatorsmile commented on a diff in the pull request:
https://github.com/apache/spark/pull/18966#discussion_r135326229
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@@ -582,6 +582,15 @@ object SQLConf {
.intConf
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Github user gatorsmile commented on a diff in the pull request:
https://github.com/apache/spark/pull/18966#discussion_r135324695
--- Diff:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/codegen/CodeGenerator.scala
---
@@ -769,16 +769,21 @@ class
Github user vanzin commented on the issue:
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I'm not sure I understand why is this a problem. What is the undesired
behavior that happens because of this? That's not explained either in the PR
nor in the bug.
The way I understand the
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Github user tejasapatil commented on the issue:
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cc @hvanhovell @cloud-fan for review
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Github user HyukjinKwon commented on a diff in the pull request:
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--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/HadoopFileLinesReader.scala
---
@@ -32,7 +32,9 @@ import
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Github user vanzin commented on the issue:
https://github.com/apache/spark/pull/18941
The PR title does not match what the PR summary says. The title is about
one change, the summary is about a different change, and the code seems to
handle both. It's all pretty confusing.
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Github user gatorsmile commented on the issue:
https://github.com/apache/spark/pull/19053
LGTM except one comment.
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Github user gatorsmile commented on a diff in the pull request:
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--- Diff:
sql/core/src/test/scala/org/apache/spark/sql/UserDefinedTypeSuite.scala ---
@@ -203,12 +203,14 @@ class UserDefinedTypeSuite extends QueryTest
Github user ajbozarth commented on a diff in the pull request:
https://github.com/apache/spark/pull/19049#discussion_r135313226
--- Diff: core/src/main/resources/org/apache/spark/ui/static/historypage.js
---
@@ -136,6 +136,16 @@ $(document).ready(function() {
Github user ajbozarth commented on the issue:
https://github.com/apache/spark/pull/19049
I'll try to clarify @srowen issue for you @guoxiaolongzte
For most use-cases each Spark cluster has it's own history server and also
uses one type of resource manager. Therefore for most
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Github user asfgit closed the pull request at:
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Github user gatorsmile commented on the issue:
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Thanks! Merging to master.
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Github user gatorsmile commented on the issue:
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LGTM
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Github user BryanCutler commented on a diff in the pull request:
https://github.com/apache/spark/pull/19024#discussion_r135307673
--- Diff: docs/ml-features.md ---
@@ -211,6 +211,89 @@ for more details on the API.
+## FeatureHasher
+
+Feature hashing
Github user BryanCutler commented on a diff in the pull request:
https://github.com/apache/spark/pull/19024#discussion_r135307551
--- Diff: docs/ml-features.md ---
@@ -53,9 +53,9 @@ are calculated based on the mapped indices. This approach
avoids the need to com
term-to-index
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Github user dilipbiswal commented on a diff in the pull request:
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--- Diff:
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---
@@ -98,6 +99,11 @@ object RewritePredicateSubquery
Github user vanzin commented on the issue:
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Merging to master.
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Github user asfgit closed the pull request at:
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Github user vanzin commented on the issue:
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@jerryshao there are conflicts in 2.2, will need a separate PR.
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Github user gatorsmile commented on a diff in the pull request:
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--- Diff:
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---
@@ -32,7 +32,9 @@ import
Github user vanzin commented on the issue:
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Merging to master, will also try 2.2.
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Github user ericvandenbergfb commented on the issue:
https://github.com/apache/spark/pull/18791
The default is off, so people can opt-in to more aggressive clean up.
Is this okay to be merged?
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Github user lianhuiwang commented on the issue:
https://github.com/apache/spark/pull/18193
@cloud-fan I have address your comments. Thanks.
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Github user shivaram commented on the issue:
https://github.com/apache/spark/pull/19016
Thats great ! I will also run this by winbuilder later today.
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Github user dongjoon-hyun commented on the issue:
https://github.com/apache/spark/pull/18991
+1, I cannot agree anymore.
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Github user gatorsmile commented on the issue:
https://github.com/apache/spark/pull/18991
Yes. The commercial DBMS products have a very good/comprehensive test
coverage. So far, it is missing in Apache Spark. Basically, we simply trust the
underlying data sources, which are
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Github user dongjoon-hyun commented on the issue:
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Wow. It's real commercial spec. Thank you! I understand.
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Github user gatorsmile commented on the issue:
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Since I saw you are also working on the enhancement of ORC reader/writer,
we need to check all the limits (value ranges). I am not sure how good Apache
ORC/Parquet did in their test case design.
Github user tgravescs commented on the issue:
https://github.com/apache/spark/pull/19047
ok to test
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Github user srowen commented on the issue:
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Oops, I meant UDT. Just referring to the tests name in the code.
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Github user pgandhi999 commented on a diff in the pull request:
https://github.com/apache/spark/pull/19047#discussion_r135297693
--- Diff:
launcher/src/main/java/org/apache/spark/launcher/AbstractCommandBuilder.java ---
@@ -136,7 +136,8 @@ void addOptionString(List cmd, String
Github user dongjoon-hyun commented on the issue:
https://github.com/apache/spark/pull/18991
Thank you for the comments and directions. Definitely, I'll try!
Since we depends on Apache Spark 1.4.0, I think I can add raw level test
case somewhere for evaluation purpose only.
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Github user gatorsmile commented on the issue:
https://github.com/apache/spark/pull/18991
If ORC incorrectly filters out the extra rows, we might get incorrect
results. In addition, we do not know whether the push down could get the
performance gain. We saw the performance regression
Github user dongjoon-hyun commented on the issue:
https://github.com/apache/spark/pull/18991
Hi, @gatorsmile .
Could you review this ORC PPD default configuration? Our data source
doesn't trust any data sources including Parquet/ORC. I think ORC PPD do no
harm on Spark.
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Github user asfgit closed the pull request at:
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Github user dongjoon-hyun commented on the issue:
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Thank you for review and merging, @gatorsmile .
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Github user gatorsmile commented on the issue:
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Thanks! Merging to master.
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UDF?
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Github user sitalkedia commented on the issue:
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Jenkins retest this please.
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Github user hhbyyh commented on the issue:
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Got it. Will make a pass today.
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Github user tejasapatil commented on the issue:
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This is superseded by https://github.com/apache/spark/pull/19054 Closing
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GitHub user tejasapatil opened a pull request:
https://github.com/apache/spark/pull/19054
[SPARK-18067] Avoid shuffling child if join keys are superset of child's
partitioning keys
Jira : https://issues.apache.org/jira/browse/SPARK-18067
## What problem is being addressed
Github user viirya commented on a diff in the pull request:
https://github.com/apache/spark/pull/19050#discussion_r135283339
--- Diff:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/optimizer/subquery.scala
---
@@ -98,6 +99,11 @@ object RewritePredicateSubquery extends
Github user srowen closed the pull request at:
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Merged to master
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Github user cloud-fan commented on the issue:
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thanks, merging to master!
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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/analysis/Analyzer.scala
---
@@ -2502,3 +2373,140 @@ object UpdateOuterReferences
Github user hvanhovell commented on a diff in the pull request:
https://github.com/apache/spark/pull/19050#discussion_r135271400
--- Diff:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/optimizer/subquery.scala
---
@@ -98,6 +99,11 @@ object RewritePredicateSubquery
Github user hvanhovell commented on a diff in the pull request:
https://github.com/apache/spark/pull/19050#discussion_r135270779
--- Diff:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/Analyzer.scala
---
@@ -2502,3 +2373,140 @@ object UpdateOuterReferences
Github user ArtRand commented on the issue:
https://github.com/apache/spark/pull/18837
Hello @srowen, thanks for taking a look at this. You're correct in that
this change does not require users to have a Mesos 1.3+ cluster, we do not
change or omit any required records in the proto
Github user MLnick commented on a diff in the pull request:
https://github.com/apache/spark/pull/19024#discussion_r135261324
--- Diff: docs/ml-features.md ---
@@ -211,6 +211,89 @@ for more details on the API.
+## FeatureHasher
+
+Feature hashing
Github user MLnick commented on a diff in the pull request:
https://github.com/apache/spark/pull/19024#discussion_r135261228
--- Diff: docs/ml-features.md ---
@@ -53,9 +53,9 @@ are calculated based on the mapped indices. This approach
avoids the need to com
term-to-index map,
Github user caneGuy commented on the issue:
https://github.com/apache/spark/pull/18730
@cloud-fan Jekins done!
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Github user jerryshao commented on the issue:
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LGTM, I tried locally. Looks like now the NPE is gone in yarn UT, thanks
for the fix.
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