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Github user vanzin commented on the issue:
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retest this please
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Github user BryanCutler commented on a diff in the pull request:
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--- Diff: python/pyspark/ml/evaluation.py ---
@@ -311,19 +330,25 @@ def setParams(self, predictionCol="prediction",
labelCol="label",
if
Github user jodersky commented on a diff in the pull request:
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--- Diff: sbin/spark-daemon.sh ---
@@ -122,6 +123,35 @@ if [ "$SPARK_NICENESS" = "" ]; then
export SPARK_NICENESS=0
fi
Github user jodersky commented on a diff in the pull request:
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--- Diff: sbin/spark-daemon.sh ---
@@ -146,13 +176,11 @@ run_command() {
case "$mode" in
(class)
- nohup nice -n
Github user jodersky commented on a diff in the pull request:
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--- Diff: sbin/spark-daemon.sh ---
@@ -146,13 +176,11 @@ run_command() {
case "$mode" in
(class)
- nohup nice -n
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--- Diff: sbin/spark-daemon.sh ---
@@ -122,6 +123,35 @@ if [ "$SPARK_NICENESS" = "" ]; then
export SPARK_NICENESS=0
fi
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--- Diff: sbin/spark-daemon.sh ---
@@ -122,6 +123,35 @@ if [ "$SPARK_NICENESS" = "" ]; then
export SPARK_NICENESS=0
fi
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Github user ajbozarth commented on the issue:
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Just to raise an idea that would possibly mean less code change, would
simply having a flag that causing a "currently processing applications" type
message to display without an actual count with
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--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/UDFRegistration.scala ---
@@ -412,6 +419,63 @@ class UDFRegistration private[sql] (functionRegistry:
Github user marmbrus commented on a diff in the pull request:
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--- Diff: python/pyspark/sql/context.py ---
@@ -202,6 +202,26 @@ def registerFunction(self, name, f,
returnType=StringType()):
"""
Github user marmbrus commented on a diff in the pull request:
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--- Diff:
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@@ -17,9 +17,15 @@
package org.apache.spark.sql
+
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--- Diff:
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@@ -225,13 +225,16 @@ case class FileSourceScanExec(
}
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Github user zsxwing commented on the issue:
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LGTM. Merging to 2.0. Thanks!
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Github user jkbradley commented on the issue:
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I'll go ahead and merge with master. Thanks!
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--- Diff:
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@@ -176,7 +184,9 @@ class StreamExecution(
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Github user Yunni commented on a diff in the pull request:
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--- Diff:
mllib/src/main/scala/org/apache/spark/ml/feature/RandomProjection.scala ---
@@ -0,0 +1,146 @@
+/*
+ * Licensed to the Apache Software
Github user markhamstra commented on a diff in the pull request:
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--- Diff: core/src/main/scala/org/apache/spark/scheduler/DAGScheduler.scala
---
@@ -1255,27 +1255,46 @@ class DAGScheduler(
s"longer
Github user avulanov commented on a diff in the pull request:
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--- Diff:
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@@ -757,7 +758,10 @@ private[sql] class SQLConf extends Serializable with
Github user wangmiao1981 commented on the issue:
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It might not be a R specific issue. I am trying to create a test case on
Scala side in SQLUtilsSuite.scala.
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Github user wangmiao1981 commented on the issue:
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I think we should find out the root cause of the negative length of "NA"
field. Yesterday, I debugged R side and I have not found out the reason yet.
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Github user wangmiao1981 commented on the issue:
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New test on Mac:
> df <- data.frame(Date = as.Date(c(rep("2016-01-10", 10), "NA", "NA")), id
= 1:12)
>
> dim(createDataFrame(df))
16/10/11 12:10:30 ERROR Executor:
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Github user tgravescs commented on the issue:
https://github.com/apache/spark/pull/15410
ah, yeah startup would definitely be a good case for this and like I
mentioned its better then nothing so I'm ok with concept.
I wonder for the other use case where it hasn't looked in ~
Github user wangmiao1981 commented on a diff in the pull request:
https://github.com/apache/spark/pull/15421#discussion_r82865118
--- Diff: core/src/main/scala/org/apache/spark/api/r/SerDe.scala ---
@@ -125,15 +125,24 @@ private[spark] object SerDe {
}
def
Github user wangmiao1981 commented on the issue:
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MacBook Pro (Retina, 15-inch, Mid 2015)
This is the machine that I test the patch on.
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Github user wangmiao1981 commented on the issue:
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@falaki I saw the exception on Mac too. But I don't find the root cause of
negative length in the input stream. Catching the exception will solve the
problem. Do you want to explore the reason
Github user falaki commented on the issue:
https://github.com/apache/spark/pull/15421
@wangmiao1981 thanks for testing on Windows. I added a check for this.
Would you please try again and let me know? Unfortunately, I don't have access
to a windows box for testing.
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--- Diff: core/src/main/scala/org/apache/spark/api/r/SerDe.scala ---
@@ -125,15 +125,24 @@ private[spark] object SerDe {
}
def
Github user markhamstra commented on a diff in the pull request:
https://github.com/apache/spark/pull/15335#discussion_r82864060
--- Diff: core/src/main/scala/org/apache/spark/scheduler/DAGScheduler.scala
---
@@ -1255,27 +1255,46 @@ class DAGScheduler(
s"longer
Github user wangmiao1981 commented on a diff in the pull request:
https://github.com/apache/spark/pull/15421#discussion_r82863921
--- Diff: core/src/main/scala/org/apache/spark/api/r/SerDe.scala ---
@@ -125,15 +125,24 @@ private[spark] object SerDe {
}
def
Github user mallman commented on the issue:
https://github.com/apache/spark/pull/14690
>> Finally, this would require us to read the schema files. That's
something I'm trying to avoid in this patch.
> Not sure what you mean here, but the parquet change should be execution
Github user jkbradley commented on the issue:
https://github.com/apache/spark/pull/15431
LGTM2
Thanks!
Is it fine with you if this just gets fixed in master, not branch-2.0
(since the other PR is not in branch-2.0 since it adds a new public API)?
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Github user wangmiao1981 commented on the issue:
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@falaki I patched your fix to a clean build. I still see the following
error:
> df <- data.frame(Date = as.Date(c(rep("2016-01-10", 10), "NA", "NA")), id
= 1:12)
>
>
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Github user felixcheung commented on the issue:
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hmm, still the same error in the new test case in appveyor
```
Failed
-
1. Error: SPARK-17811: can create
Github user ericl commented on the issue:
https://github.com/apache/spark/pull/14690
> For one thing, a ListingFileCatalog performs a file tree traversal right
off the bat. However, the external catalog returns the locations of partitions
as part of the listPartitionsByFilter call. I
Github user felixcheung commented on the issue:
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LGTM
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Github user rxin commented on the issue:
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LGTM except that one comment on naming.
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--- Diff: sql/core/src/main/scala/org/apache/spark/sql/RuntimeConfig.scala
---
@@ -132,4 +136,9 @@ class RuntimeConfig private[sql](sqlConf: SQLConf = new
Github user rxin commented on a diff in the pull request:
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--- Diff: sql/core/src/main/scala/org/apache/spark/sql/RuntimeConfig.scala
---
@@ -36,6 +37,7 @@ class RuntimeConfig private[sql](sqlConf: SQLConf = new
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Github user rxin commented on the issue:
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hm - maybe we should just cast any NullType input into some concrete type
defined by an ExpectsInputTypes expression?
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--- Diff: python/pyspark/sql/streaming.py ---
@@ -189,6 +189,282 @@ def resetTerminated(self):
self._jsqm.resetTerminated()
+class
GitHub user brkyvz opened a pull request:
https://github.com/apache/spark/pull/15437
[SPARK-17876] Write StructuredStreaming WAL to a stream instead of
materializing all at once
## What changes were proposed in this pull request?
The CompactibleFileStreamLog materializes
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--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/StreamMetrics.scala
---
@@ -0,0 +1,244 @@
+/*
+ * Licensed to the
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--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/StreamExecution.scala
---
@@ -530,7 +692,7 @@ class StreamExecution(
case
Github user tdas commented on a diff in the pull request:
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--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/StreamExecution.scala
---
@@ -516,12 +563,127 @@ class StreamExecution(
Github user tdas commented on a diff in the pull request:
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--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/StreamExecution.scala
---
@@ -221,8 +247,15 @@ class StreamExecution(
Github user tdas commented on a diff in the pull request:
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--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/StreamExecution.scala
---
@@ -105,11 +105,21 @@ class StreamExecution(
var
Github user tdas commented on a diff in the pull request:
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--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/StreamMetrics.scala
---
@@ -0,0 +1,244 @@
+/*
+ * Licensed to the Apache
Github user mallman commented on the issue:
https://github.com/apache/spark/pull/14690
I believe that using a method like `TableFileCatalog.filterPartitions` to
build a new file catalog restricted to some pruned partitions is a sound
approach, however I'm starting to reconsider the
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--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/StreamExecution.scala
---
@@ -516,12 +563,127 @@ class StreamExecution(
Github user tdas commented on a diff in the pull request:
https://github.com/apache/spark/pull/15307#discussion_r82855520
--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/StreamExecution.scala
---
@@ -176,7 +184,9 @@ class StreamExecution(
//
Github user srowen commented on a diff in the pull request:
https://github.com/apache/spark/pull/15436#discussion_r82854783
--- Diff: NOTICE ---
@@ -162,7 +162,7 @@ Please visit the Netty web site for more information:
* http://netty.io/
-Copyright 2011 The
Github user srowen commented on a diff in the pull request:
https://github.com/apache/spark/pull/15436#discussion_r82854900
--- Diff: dev/deps/spark-deps-hadoop-2.3 ---
@@ -130,7 +130,6 @@ metrics-json-3.1.2.jar
metrics-jvm-3.1.2.jar
minlog-1.3.0.jar
mx4j-3.0.2.jar
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[SPARK-17875] [BUILD] Remove unneeded direct dependence on Netty 3.x
## What changes were proposed in this pull request?
Remove unneeded direct dependency on Netty 3.x. I left the
Github user dilipbiswal commented on the issue:
https://github.com/apache/spark/pull/15190
@yhuai We will use Parquet format in your example. We look at ```SQL
spark.sql.sources.default ``` configuration to decide on the format to use ?
Here is the output for your perusal.
Github user vijoshi commented on the issue:
https://github.com/apache/spark/pull/15410
@tgravescs - you're right - for newer logs that are generated, there could
be a window of time (10 secs or whatever the user configures) where the new
logs are not picked up for replay and the UI
Github user zsxwing commented on the issue:
https://github.com/apache/spark/pull/15422
> For example, in MR you have the ability to even set the percentage of bad
records you want to tolerate (we dont have that in spark).
I may be wrong. But in MR, I think bad records just
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Github user mallman commented on the issue:
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Ah cripes. I committed something I didn't want to. I'm rebasing again in a
few...
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Github user sethah commented on the issue:
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I'll try to take a look before too long. For now, I see there are no tests,
could you please add tests, using the summary tests for binary classification
as a guide? Thanks!
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Github user tdas commented on the issue:
https://github.com/apache/spark/pull/15384
Merging it to master, and branch 2.0
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Github user mallman commented on a diff in the pull request:
https://github.com/apache/spark/pull/14690#discussion_r82850487
--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/execution/DataSourceScanExec.scala
---
@@ -225,13 +225,16 @@ case class FileSourceScanExec(
}
Github user srowen commented on the issue:
https://github.com/apache/spark/pull/15422
@mridulm for the scenario you're imagining, maybe the data is OK, sure.
That doesn't mean it's true in all cases. Yeah, this is really to work around
bad input, which you can to some degree do at
Github user BryanCutler commented on the issue:
https://github.com/apache/spark/pull/13194
Just one question, otherwise LGTM
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Github user BryanCutler commented on a diff in the pull request:
https://github.com/apache/spark/pull/13194#discussion_r82849461
--- Diff: python/pyspark/ml/evaluation.py ---
@@ -21,7 +21,8 @@
from pyspark.ml.wrapper import JavaParams
from pyspark.ml.param import Param,
Github user jodersky commented on a diff in the pull request:
https://github.com/apache/spark/pull/15398#discussion_r82849408
--- Diff:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/util/StringUtils.scala
---
@@ -25,26 +25,25 @@ object StringUtils {
//
Github user mridulm commented on the issue:
https://github.com/apache/spark/pull/15422
@marmbrus +1 on logging, that is definitely something which was probably
missed here.
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