[GitHub] spark issue #23039: [SPARK-26066][SQL] Using new SQL config spark.sql.debug....

2018-11-14 Thread MaxGekk
Github user MaxGekk commented on the issue:

https://github.com/apache/spark/pull/23039
  
> let's fix PR description and title for that.
> One PR should have one theme with a proper title. 

@HyukjinKwon @dongjoon-hyun I have renamed this PR. Is new title fine for 
you?

> We frequently search by commit title. Please don't split this PR into two 
sub PRs.

Sure, I will not.


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[GitHub] spark issue #23030: [MINOR][YARN] Make memLimitExceededLogMessage more clean

2018-11-14 Thread AmplabJenkins
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[GitHub] spark issue #23030: [MINOR][YARN] Make memLimitExceededLogMessage more clean

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[GitHub] spark issue #23030: [MINOR][YARN] Make memLimitExceededLogMessage more clean

2018-11-14 Thread SparkQA
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[GitHub] spark issue #23041: [SPARK-26069][TESTS]Fix flaky test: RpcIntegrationSuite....

2018-11-14 Thread SparkQA
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[GitHub] spark issue #23041: [SPARK-26069][TESTS]Fix flaky test: RpcIntegrationSuite....

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[GitHub] spark issue #23041: [SPARK-26069][TESTS]Fix flaky test: RpcIntegrationSuite....

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[GitHub] spark pull request #23041: [SPARK-26069][TESTS]Fix flaky test: RpcIntegratio...

2018-11-14 Thread zsxwing
Github user zsxwing commented on a diff in the pull request:

https://github.com/apache/spark/pull/23041#discussion_r233734198
  
--- Diff: 
common/network-common/src/test/java/org/apache/spark/network/RpcIntegrationSuite.java
 ---
@@ -371,23 +371,29 @@ private void assertErrorsContain(Set errors, 
Set contains) {
 
   private void assertErrorAndClosed(RpcResult result, String 
expectedError) {
 assertTrue("unexpected success: " + result.successMessages, 
result.successMessages.isEmpty());
-// we expect 1 additional error, which contains *either* "closed" or 
"Connection reset"
+// we expect 1 additional error, which should contain one of the 
follow messages:
+// - "closed"
+// - "Connection reset"
+// - "java.nio.channels.ClosedChannelException"
 Set errors = result.errorMessages;
 assertEquals("Expected 2 errors, got " + errors.size() + "errors: " +
 errors, 2, errors.size());
 
 Set containsAndClosed = Sets.newHashSet(expectedError);
 containsAndClosed.add("closed");
 containsAndClosed.add("Connection reset");
+containsAndClosed.add("java.nio.channels.ClosedChannelException");
 
 Pair, Set> r = checkErrorsContain(errors, 
containsAndClosed);
 
-Set errorsNotFound = r.getRight();
-assertEquals(1, errorsNotFound.size());
-String err = errorsNotFound.iterator().next();
-assertTrue(err.equals("closed") || err.equals("Connection reset"));
+assertTrue("Got a non-empty set " + r.getLeft(), 
r.getLeft().isEmpty());
--- End diff --

Moved this check here so that we can see what's the error that causes the 
test failure.


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[GitHub] spark issue #23041: [SPARK-26069][TESTS]Fix flaky test: RpcIntegrationSuite....

2018-11-14 Thread zsxwing
Github user zsxwing commented on the issue:

https://github.com/apache/spark/pull/23041
  
cc @squito


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[GitHub] spark pull request #23041: [SPARK-26069][TESTS]Fix flaky test: RpcIntegratio...

2018-11-14 Thread zsxwing
GitHub user zsxwing opened a pull request:

https://github.com/apache/spark/pull/23041

[SPARK-26069][TESTS]Fix flaky test: 
RpcIntegrationSuite.sendRpcWithStreamFailures

## What changes were proposed in this pull request?

The test failure is because `assertErrorAndClosed` misses one possible 
error message: `java.nio.channels.ClosedChannelException`. This happens when 
the second `uploadStream` is called after the channel has been closed. This can 
be reproduced by adding `Thread.sleep(1000)` below this line: 
https://github.com/apache/spark/blob/03306a6df39c9fd6cb581401c13c4dfc6bbd632e/common/network-common/src/test/java/org/apache/spark/network/RpcIntegrationSuite.java#L217

This PR fixes the above issue and also improves the test failure messages 
of `assertErrorAndClosed`.

## How was this patch tested?

Jenkins

You can merge this pull request into a Git repository by running:

$ git pull https://github.com/zsxwing/spark SPARK-26069

Alternatively you can review and apply these changes as the patch at:

https://github.com/apache/spark/pull/23041.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 #23041


commit 6bebcb5e004ed4b434c550d26ed1a922d13e0446
Author: Shixiong Zhu 
Date:   2018-11-15T07:16:00Z

fix test




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[GitHub] spark issue #23030: [MINOR][YARN] Make memLimitExceededLogMessage more clean

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[GitHub] spark issue #23030: [MINOR][YARN] Make memLimitExceededLogMessage more clean

2018-11-14 Thread SparkQA
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[GitHub] spark issue #23030: [MINOR][YARN] Make memLimitExceededLogMessage more clean

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[GitHub] spark issue #16732: [SPARK-19368][MLlib] BlockMatrix.toIndexedRowMatrix() op...

2018-11-14 Thread uzadude
Github user uzadude commented on the issue:

https://github.com/apache/spark/pull/16732
  
After running some more experiments I was able to reduce the runtime by 
another 1.5x factor. So currently the 
"toCoordinateMatrix().toIndexedRowMatrix()" is better by a bit only in the 
extreme cases when the block matrix size was somewhat incorrectly configured 
(as above - 1000x1000 and density 1/1000) - meaning it will contain many rows 
with only one value, then the gain comes only from the overhead of shuffling 
primitive instead of a Vector. So I generally think this approach is better.


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[GitHub] spark issue #23029: [SPARK-26055][CORE] InterfaceStability annotations shoul...

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[GitHub] spark issue #23029: [SPARK-26055][CORE] InterfaceStability annotations shoul...

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[GitHub] spark issue #23029: [SPARK-26055][CORE] InterfaceStability annotations shoul...

2018-11-14 Thread SparkQA
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[GitHub] spark pull request #21526: [SPARK-24515][CORE] No need to warning when outpu...

2018-11-14 Thread caneGuy
Github user caneGuy closed the pull request at:

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[GitHub] spark issue #22893: [SPARK-25868][MLlib] One part of Spark MLlib Kmean Logic...

2018-11-14 Thread KyleLi1985
Github user KyleLi1985 commented on the issue:

https://github.com/apache/spark/pull/22893
  
> Thanks @KyleLi1985 this looks like a nice win in the end. Thanks for your 
investigation.

@srowen @HyukjinKwon @mgaido91 Thanks for review. It is my pleasure.


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[GitHub] spark issue #23038: [SPARK-25451][CORE][WEBUI]Aggregated metrics table doesn...

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[GitHub] spark issue #23031: [SPARK-26060][CORE][SQL] Track SparkConf entries and mak...

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[GitHub] spark issue #23031: [SPARK-26060][CORE][SQL] Track SparkConf entries and mak...

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[GitHub] spark issue #23038: [SPARK-25451][CORE][WEBUI]Aggregated metrics table doesn...

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[GitHub] spark issue #23040: [SPARK-26068][Core]ChunkedByteBufferInputStream should h...

2018-11-14 Thread advancedxy
Github user advancedxy commented on the issue:

https://github.com/apache/spark/pull/23040
  
cc @ericl and @JoshRosen, this bug was introduced by 
https://github.com/apache/spark/pull/14099/files 

After loosing empty chunk check, the ChunkedByteBufferInputStream doesn't 
handle empty chunks correctly


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[GitHub] spark issue #23038: [SPARK-25451][CORE][WEBUI]Aggregated metrics table doesn...

2018-11-14 Thread SparkQA
Github user SparkQA commented on the issue:

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[GitHub] spark issue #23040: [SPARK-26068][Core]ChunkedByteBufferInputStream should h...

2018-11-14 Thread linhong-intel
Github user linhong-intel commented on the issue:

https://github.com/apache/spark/pull/23040
  
cc @xuanyuanking 


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[GitHub] spark issue #23031: [SPARK-26060][CORE][SQL] Track SparkConf entries and mak...

2018-11-14 Thread SparkQA
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[GitHub] spark issue #23031: [SPARK-26060][CORE][SQL] Track SparkConf entries and mak...

2018-11-14 Thread ueshin
Github user ueshin commented on the issue:

https://github.com/apache/spark/pull/23031
  
@vanzin Thanks for letting me know it and that's really good to know.
I'll update this to use it.


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[GitHub] spark issue #23040: [SPARK-26068][Core]ChunkedByteBufferInputStream should h...

2018-11-14 Thread AmplabJenkins
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https://github.com/apache/spark/pull/23040
  
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[GitHub] spark issue #23040: [SPARK-26068][Core]ChunkedByteBufferInputStream should h...

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[GitHub] spark issue #23040: [SPARK-26068][Core]ChunkedByteBufferInputStream should h...

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[GitHub] spark pull request #23040: [SPARK-26068][Core]ChunkedByteBufferInputStream s...

2018-11-14 Thread linhong-intel
GitHub user linhong-intel opened a pull request:

https://github.com/apache/spark/pull/23040

[SPARK-26068][Core]ChunkedByteBufferInputStream should handle empty chunks 
correctly

## What changes were proposed in this pull request?

Empty chunk in ChunkedByteBuffer will truncate the 
ChunkedByteBufferInputStream.
The detail reason is described in 

## How was this patch tested?
Modified current UT to cover this case.

You can merge this pull request into a Git repository by running:

$ git pull https://github.com/linhong-intel/spark 
fix-empty-chunked-byte-buffer

Alternatively you can review and apply these changes as the patch at:

https://github.com/apache/spark/pull/23040.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 #23040


commit ab81c1e8eefabc9249e7643dffb8d7c0eef3c7dc
Author: Liu,Linhong 
Date:   2018-11-15T03:37:39Z

ChunkedByteBufferInputStream should handle empty chunks correctly




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[GitHub] spark issue #23034: [WIP][SPARK-26035][PYTHON] Break large streaming/tests.p...

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[GitHub] spark issue #23034: [WIP][SPARK-26035][PYTHON] Break large streaming/tests.p...

2018-11-14 Thread SparkQA
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[GitHub] spark issue #22911: [SPARK-25815][k8s] Support kerberos in client mode, keyt...

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[GitHub] spark issue #23034: [WIP][SPARK-26035][PYTHON] Break large streaming/tests.p...

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[GitHub] spark issue #22911: [SPARK-25815][k8s] Support kerberos in client mode, keyt...

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[GitHub] spark pull request #22989: [SPARK-25986][Build] Add rules to ban throw Error...

2018-11-14 Thread srowen
Github user srowen commented on a diff in the pull request:

https://github.com/apache/spark/pull/22989#discussion_r233713175
  
--- Diff: 
common/unsafe/src/main/java/org/apache/spark/unsafe/UnsafeAlignedOffset.java ---
@@ -39,7 +39,9 @@ public static int getSize(Object object, long offset) {
   case 8:
 return (int)Platform.getLong(object, offset);
   default:
+// checkstyle.off: RegexpSinglelineJava
 throw new AssertionError("Illegal UAO_SIZE");
--- End diff --

I think these are ok as AssertionError because they shouldn't be able to 
happen in any JVM state


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[GitHub] spark pull request #23033: [SPARK-26036][PYTHON] Break large tests.py files ...

2018-11-14 Thread asfgit
Github user asfgit closed the pull request at:

https://github.com/apache/spark/pull/23033


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[GitHub] spark issue #23033: [SPARK-26036][PYTHON] Break large tests.py files into sm...

2018-11-14 Thread HyukjinKwon
Github user HyukjinKwon commented on the issue:

https://github.com/apache/spark/pull/23033
  
Merged to master.


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[GitHub] spark issue #23033: [SPARK-26036][PYTHON] Break large tests.py files into sm...

2018-11-14 Thread HyukjinKwon
Github user HyukjinKwon commented on the issue:

https://github.com/apache/spark/pull/23033
  
I am merging this for the same reason with #23021. Let me know if there's 
any concern even after this got merged.


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[GitHub] spark issue #23033: [SPARK-26036][PYTHON] Break large tests.py files into sm...

2018-11-14 Thread HyukjinKwon
Github user HyukjinKwon commented on the issue:

https://github.com/apache/spark/pull/23033
  
@BryanCutler, looks we should add `pyspark.ml.tests` at 
https://github.com/apache/spark/blob/master/python/run-tests.py#L252-L253 so 
that we can run unittests first over doc tests (because arguably unittests take 
longer then doctests).

I think it's missed when `ml/tests.py` was added. For instance, the latest 
above took it took few minutes longer then usual because the ml tests ran at 
the last.


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[GitHub] spark issue #23038: [SPARK-25451][CORE][WEBUI]Aggregated metrics table doesn...

2018-11-14 Thread shahidki31
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Retest this please


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[GitHub] spark pull request #22989: [SPARK-25986][Build] Add rules to ban throw Error...

2018-11-14 Thread cloud-fan
Github user cloud-fan commented on a diff in the pull request:

https://github.com/apache/spark/pull/22989#discussion_r233706605
  
--- Diff: 
common/unsafe/src/main/java/org/apache/spark/unsafe/UnsafeAlignedOffset.java ---
@@ -52,7 +54,9 @@ public static void putSize(Object object, long offset, 
int value) {
 Platform.putLong(object, offset, value);
 break;
   default:
+// checkstyle.off: RegexpSinglelineJava
 throw new AssertionError("Illegal UAO_SIZE");
--- End diff --

ditto


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[GitHub] spark pull request #22989: [SPARK-25986][Build] Add rules to ban throw Error...

2018-11-14 Thread cloud-fan
Github user cloud-fan commented on a diff in the pull request:

https://github.com/apache/spark/pull/22989#discussion_r233706517
  
--- Diff: 
common/unsafe/src/main/java/org/apache/spark/unsafe/UnsafeAlignedOffset.java ---
@@ -39,7 +39,9 @@ public static int getSize(Object object, long offset) {
   case 8:
 return (int)Platform.getLong(object, offset);
   default:
+// checkstyle.off: RegexpSinglelineJava
 throw new AssertionError("Illegal UAO_SIZE");
--- End diff --

shall we throw `IllegalStateException` here?


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[GitHub] spark issue #22911: [SPARK-25815][k8s] Support kerberos in client mode, keyt...

2018-11-14 Thread suxingfate
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--keytab is a simpler way IMO to enable long running spark on k8s than DT 
renew approach


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[GitHub] spark issue #23037: [MINOR][k8s] Add Copy pyspark into corresponding dir cmd...

2018-11-14 Thread AzureQ
Github user AzureQ commented on the issue:

https://github.com/apache/spark/pull/23037
  
> I see this customization to be specific towards how you build your custom 
Docker image. Unless it is relevant towards testing, we are trying to keep the 
default Docker image as lightweight as possible (as long as it passes our test 
cases). Unless one of the committers sees this as an important thing to include 
in the default image, I believe it to be a customization.

This is to make the default Docker image work properly, not customization 
at all. Without this change, the docker image of pyspark does not work properly 
in "client mode" while spark image and rspark image are working properly.


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[GitHub] spark pull request #23035: [SPARK-26057][SQL] Transform also analyzed plans ...

2018-11-14 Thread cloud-fan
Github user cloud-fan commented on a diff in the pull request:

https://github.com/apache/spark/pull/23035#discussion_r233696401
  
--- Diff: sql/core/src/test/scala/org/apache/spark/sql/DataFrameSuite.scala 
---
@@ -2554,4 +2554,34 @@ class DataFrameSuite extends QueryTest with 
SharedSQLContext {
 
 checkAnswer(swappedDf.filter($"key"($"map") > "a"), Row(2, Map(2 -> 
"b")))
   }
+
+  test("SPARK-26057: attribute deduplication on already analyzed plans") {
+withTempView("cc", "p", "c") {
+  val df1 = Seq(("1-1", "sp", 6)).toDF("id", "layout", "n")
+  df1.createOrReplaceTempView("cc")
+  val df2 = Seq(("sp", 1)).toDF("layout", "ts")
+  df2.createOrReplaceTempView("p")
+  val df3 = Seq(("1-1", "sp", 3)).toDF("id", "layout", "ts")
+  df3.createOrReplaceTempView("c")
+  spark.sql(
+"""
+  |SELECT cc.id, cc.layout, count(*) as m
+  |FROM cc
+  |JOIN p USING(layout)
+  |WHERE EXISTS(
+  |  SELECT 1
+  |  FROM c
+  |  WHERE c.id = cc.id AND c.layout = cc.layout AND c.ts > p.ts)
+  |GROUP BY cc.id, cc.layout
+""".stripMargin).createOrReplaceTempView("pcc")
+  val res = spark.sql(
--- End diff --

good catch on the problem! Do you think it's possible to simplify the test? 
I think we just need a temp view with subquery, and use it in a join.


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[GitHub] spark pull request #23035: [SPARK-26057][SQL] Transform also analyzed plans ...

2018-11-14 Thread cloud-fan
Github user cloud-fan commented on a diff in the pull request:

https://github.com/apache/spark/pull/23035#discussion_r233695765
  
--- Diff: sql/core/src/test/scala/org/apache/spark/sql/DataFrameSuite.scala 
---
@@ -2554,4 +2554,34 @@ class DataFrameSuite extends QueryTest with 
SharedSQLContext {
 
 checkAnswer(swappedDf.filter($"key"($"map") > "a"), Row(2, Map(2 -> 
"b")))
   }
+
+  test("SPARK-26057: attribute deduplication on already analyzed plans") {
+withTempView("cc", "p", "c") {
--- End diff --

if we don't care about naming, how about `a, b, c` instead of `cc, p, c`?


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[GitHub] spark issue #23016: [SPARK-26006][mllib] unpersist 'dataInternalRepr' in the...

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[GitHub] spark issue #23016: [SPARK-26006][mllib] unpersist 'dataInternalRepr' in the...

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[GitHub] spark issue #23016: [SPARK-26006][mllib] unpersist 'dataInternalRepr' in the...

2018-11-14 Thread SparkQA
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**[Test build #98853 has 
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[`5c4949d`](https://github.com/apache/spark/commit/5c4949d675bb06689dae8a4748b83f271f176745).
 * This patch passes all tests.
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 * This patch adds no public classes.


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[GitHub] spark issue #23039: [SPARK-26066][SQL] Moving truncatedString to sql/catalys...

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[GitHub] spark issue #23039: [SPARK-26066][SQL] Moving truncatedString to sql/catalys...

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[GitHub] spark issue #23039: [SPARK-26066][SQL] Moving truncatedString to sql/catalys...

2018-11-14 Thread SparkQA
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[GitHub] spark pull request #23027: [SPARK-26049][SQL][TEST] FilterPushdownBenchmark ...

2018-11-14 Thread wangyum
Github user wangyum commented on a diff in the pull request:

https://github.com/apache/spark/pull/23027#discussion_r233689556
  
--- Diff: sql/core/benchmarks/FilterPushdownBenchmark-results.txt ---
@@ -2,669 +2,809 @@
 Pushdown for many distinct value case
 

 
-OpenJDK 64-Bit Server VM 1.8.0_181-b13 on Linux 3.10.0-862.3.2.el7.x86_64
-Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
+Java HotSpot(TM) 64-Bit Server VM 1.8.0_191-b12 on Mac OS X 10.12.6
+Intel(R) Core(TM) i7-7820HQ CPU @ 2.90GHz
 Select 0 string row (value IS NULL): Best/Avg Time(ms)Rate(M/s)   
Per Row(ns)   Relative
 

-Parquet Vectorized  11405 / 11485  1.4 
725.1   1.0X
-Parquet Vectorized (Pushdown)  675 /  690 23.3 
 42.9  16.9X
-Native ORC Vectorized 7127 / 7170  2.2 
453.1   1.6X
-Native ORC Vectorized (Pushdown)   519 /  541 30.3 
 33.0  22.0X
+Parquet Vectorized7823 / 7996  2.0 
497.4   1.0X
+Parquet Vectorized (Pushdown)  460 /  468 34.2 
 29.2  17.0X
+Native ORC Vectorized 5412 / 5550  2.9 
344.1   1.4X
+Native ORC Vectorized (Pushdown)   551 /  563 28.6 
 35.0  14.2X
+InMemoryTable Vectorized 6 /6   2859.1 
  0.31422.0X
+InMemoryTable Vectorized (Pushdown)  5 /6   3023.0 
  0.31503.6X
 
-OpenJDK 64-Bit Server VM 1.8.0_181-b13 on Linux 3.10.0-862.3.2.el7.x86_64
-Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
+Java HotSpot(TM) 64-Bit Server VM 1.8.0_191-b12 on Mac OS X 10.12.6
+Intel(R) Core(TM) i7-7820HQ CPU @ 2.90GHz
 Select 0 string row ('7864320' < value < '7864320'): Best/Avg Time(ms)
Rate(M/s)   Per Row(ns)   Relative
 

-Parquet Vectorized  11457 / 11473  1.4 
728.4   1.0X
-Parquet Vectorized (Pushdown)  656 /  686 24.0 
 41.7  17.5X
-Native ORC Vectorized 7328 / 7342  2.1 
465.9   1.6X
-Native ORC Vectorized (Pushdown)   539 /  565 29.2 
 34.2  21.3X
+Parquet Vectorized   8322 / 11160  1.9 
529.1   1.0X
+Parquet Vectorized (Pushdown)  463 /  472 34.0 
 29.4  18.0X
+Native ORC Vectorized 5622 / 5635  2.8 
357.4   1.5X
+Native ORC Vectorized (Pushdown)   563 /  595 27.9 
 35.8  14.8X
+InMemoryTable Vectorized  4831 / 4881  3.3 
307.2   1.7X
+InMemoryTable Vectorized (Pushdown)   1980 / 2027  7.9 
125.9   4.2X
 
-OpenJDK 64-Bit Server VM 1.8.0_181-b13 on Linux 3.10.0-862.3.2.el7.x86_64
-Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
+Java HotSpot(TM) 64-Bit Server VM 1.8.0_191-b12 on Mac OS X 10.12.6
+Intel(R) Core(TM) i7-7820HQ CPU @ 2.90GHz
 Select 1 string row (value = '7864320'): Best/Avg Time(ms)Rate(M/s)   
Per Row(ns)   Relative
 

-Parquet Vectorized  11878 / 11888  1.3 
755.2   1.0X
-Parquet Vectorized (Pushdown)  630 /  654 25.0 
 40.1  18.9X
-Native ORC Vectorized 7342 / 7362  2.1 
466.8   1.6X
-Native ORC Vectorized (Pushdown)   519 /  537 30.3 
 33.0  22.9X
+Parquet Vectorized8322 / 8386  1.9 
529.1   1.0X
+Parquet Vectorized (Pushdown)  434 /  441 36.2 
 27.6  19.2X
+Native ORC Vectorized 5659 / 5944  2.8 
359.8   1.5X
+Native ORC Vectorized (Pushdown)   535 /  567 29.4 
 34.0  15.6X
+InMemoryTable Vectorized  4784 / 4879  3.3 
304.1   1.7X
+InMemoryTable Vectorized (Pushdown)   1950 / 1985  8.1 
124.0   4.3X
 
-OpenJDK 64-Bit Server VM 1.8.0_181-b13 on Linux 3.10.0-862.3.2.el7.x86_64
-Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
+Java HotSpot(TM) 64-Bit Server VM 

[GitHub] spark issue #22911: [SPARK-25815][k8s] Support kerberos in client mode, keyt...

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[GitHub] spark issue #22911: [SPARK-25815][k8s] Support kerberos in client mode, keyt...

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[GitHub] spark issue #22989: [SPARK-25986][Build] Add rules to ban throw Errors in ap...

2018-11-14 Thread xuanyuanking
Github user xuanyuanking commented on the issue:

https://github.com/apache/spark/pull/22989
  
Thanks @HyukjinKwon @viirya @felixcheung @srowen for your review and advise!


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[GitHub] spark pull request #23027: [SPARK-26049][SQL][TEST] FilterPushdownBenchmark ...

2018-11-14 Thread wangyum
Github user wangyum commented on a diff in the pull request:

https://github.com/apache/spark/pull/23027#discussion_r233687968
  
--- Diff: sql/core/benchmarks/FilterPushdownBenchmark-results.txt ---
@@ -2,669 +2,809 @@
 Pushdown for many distinct value case
 

 
-OpenJDK 64-Bit Server VM 1.8.0_181-b13 on Linux 3.10.0-862.3.2.el7.x86_64
-Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
+Java HotSpot(TM) 64-Bit Server VM 1.8.0_191-b12 on Mac OS X 10.12.6
+Intel(R) Core(TM) i7-7820HQ CPU @ 2.90GHz
 Select 0 string row (value IS NULL): Best/Avg Time(ms)Rate(M/s)   
Per Row(ns)   Relative
 

-Parquet Vectorized  11405 / 11485  1.4 
725.1   1.0X
-Parquet Vectorized (Pushdown)  675 /  690 23.3 
 42.9  16.9X
-Native ORC Vectorized 7127 / 7170  2.2 
453.1   1.6X
-Native ORC Vectorized (Pushdown)   519 /  541 30.3 
 33.0  22.0X
+Parquet Vectorized7823 / 7996  2.0 
497.4   1.0X
+Parquet Vectorized (Pushdown)  460 /  468 34.2 
 29.2  17.0X
+Native ORC Vectorized 5412 / 5550  2.9 
344.1   1.4X
+Native ORC Vectorized (Pushdown)   551 /  563 28.6 
 35.0  14.2X
+InMemoryTable Vectorized 6 /6   2859.1 
  0.31422.0X
+InMemoryTable Vectorized (Pushdown)  5 /6   3023.0 
  0.31503.6X
 
-OpenJDK 64-Bit Server VM 1.8.0_181-b13 on Linux 3.10.0-862.3.2.el7.x86_64
-Intel(R) Xeon(R) CPU E5-2670 v2 @ 2.50GHz
+Java HotSpot(TM) 64-Bit Server VM 1.8.0_191-b12 on Mac OS X 10.12.6
+Intel(R) Core(TM) i7-7820HQ CPU @ 2.90GHz
 Select 0 string row ('7864320' < value < '7864320'): Best/Avg Time(ms)
Rate(M/s)   Per Row(ns)   Relative
 

-Parquet Vectorized  11457 / 11473  1.4 
728.4   1.0X
-Parquet Vectorized (Pushdown)  656 /  686 24.0 
 41.7  17.5X
-Native ORC Vectorized 7328 / 7342  2.1 
465.9   1.6X
-Native ORC Vectorized (Pushdown)   539 /  565 29.2 
 34.2  21.3X
+Parquet Vectorized   8322 / 11160  1.9 
529.1   1.0X
+Parquet Vectorized (Pushdown)  463 /  472 34.0 
 29.4  18.0X
+Native ORC Vectorized 5622 / 5635  2.8 
357.4   1.5X
+Native ORC Vectorized (Pushdown)   563 /  595 27.9 
 35.8  14.8X
+InMemoryTable Vectorized  4831 / 4881  3.3 
307.2   1.7X
+InMemoryTable Vectorized (Pushdown)   1980 / 2027  7.9 
125.9   4.2X
--- End diff --

Yes. This is the current benchmark result. I plan to improve it step by 
step. Example: [SPARK-26004](https://issues.apache.org/jira/browse/SPARK-26004)


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[GitHub] spark pull request #23027: [SPARK-26049][SQL][TEST] FilterPushdownBenchmark ...

2018-11-14 Thread wangyum
Github user wangyum commented on a diff in the pull request:

https://github.com/apache/spark/pull/23027#discussion_r233686986
  
--- Diff: 
sql/core/src/test/scala/org/apache/spark/sql/execution/benchmark/FilterPushdownBenchmark.scala
 ---
@@ -131,6 +134,15 @@ object FilterPushdownBenchmark extends BenchmarkBase 
with SQLHelper {
   }
 }
 
+Seq(false, true).foreach { pushDownEnabled =>
+  val name = s"InMemoryTable Vectorized ${if (pushDownEnabled) 
s"(Pushdown)" else ""}"
+  benchmark.addCase(name) { _ =>
+withSQLConf(SQLConf.IN_MEMORY_PARTITION_PRUNING.key -> 
s"$pushDownEnabled") {
--- End diff --

I think the InMemoryTable's partition same to Parquet RowGroup(@kiszk 
please correct if I'm wrong). We put them together and it's easy to compare 
performance.


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[GitHub] spark issue #23039: [SPARK-26066][SQL] Moving truncatedString to sql/catalys...

2018-11-14 Thread dongjoon-hyun
Github user dongjoon-hyun commented on the issue:

https://github.com/apache/spark/pull/23039
  
@MaxGekk . One PR should have one theme with a proper title. We frequently 
search by commit title. Please don't split this PR into two sub PRs.


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[GitHub] spark issue #22967: [SPARK-25956] Make Scala 2.12 as default Scala version i...

2018-11-14 Thread xerial
Github user xerial commented on the issue:

https://github.com/apache/spark/pull/22967
  
Thank you for all the efforts to make this happen! 

Spark has been the last resort before deprecating Scala 2.11. 

After Spark 3.0, as an OSS contributor, we can stop maintaining cross 
builds for Scala 2.11 and can completely migrate to Scala 2.12 or later after 
Spark 3.0. 


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[GitHub] spark issue #21688: [SPARK-21809] : Change Stage Page to use datatables to s...

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[GitHub] spark issue #21688: [SPARK-21809] : Change Stage Page to use datatables to s...

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[GitHub] spark issue #23012: [SPARK-26014][R] Deprecate R prior to version 3.4 in Spa...

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