Github user srowen commented on the issue:
https://github.com/apache/spark/pull/13762
I think we should close this PR.
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Github user srowen commented on the issue:
https://github.com/apache/spark/pull/15052
I get that, but if it's always true, then there was no problem to begin
with. That's what the code seems to think right now. I haven't looked at the
code much but that's the question -- are you sure
Github user SparkQA commented on the issue:
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Github user SparkQA commented on the issue:
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Github user a-roberts commented on the issue:
https://github.com/apache/spark/pull/14961
Sean, yep, I've had trouble reproducing it too, kicked off a bunch of
builds over the weekend including one using Hadoop-2.3 which was my initial
theory (only difference between our testing
Github user SparkQA commented on the issue:
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Github user cloud-fan commented on the issue:
https://github.com/apache/spark/pull/15046
ah good catch! But adding a new flag looks a little tricky, let me think if
there is better way to fix it
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Github user djvulee commented on the issue:
https://github.com/apache/spark/pull/15052
@srowen No. It does not matter whether the file is empty or not, if the
file is empty, the `getsize()` just return 0, and this should be OK.
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Github user AnthonyTruchet commented on the issue:
https://github.com/apache/spark/pull/15023
I'm aware that features are not generally back-ported. The point is, for us
this is a bug, preventing a deployment in production. We thus back-ported the
fix internally and now propose to
Github user clockfly commented on the issue:
https://github.com/apache/spark/pull/15056
@yhuai
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Github user cloud-fan commented on the issue:
https://github.com/apache/spark/pull/15040
`BucketingInfoExtractor` maybe a too flexible concept, we only need a
boolean flag to indicate it's a spark native bucketing or hive bucketing, and
I'm sure how soon we need to support bucketed
Github user SparkQA commented on the issue:
https://github.com/apache/spark/pull/14995
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Github user srowen commented on the issue:
https://github.com/apache/spark/pull/15052
Is the idea that the file may be non empty when written ?
There is at least one more instance of this call but maybe the file is
known to be empty before.
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Github user cloud-fan commented on a diff in the pull request:
https://github.com/apache/spark/pull/15047#discussion_r78331887
--- Diff: sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveHash.scala
---
@@ -0,0 +1,145 @@
+/*
+ * Licensed to the Apache Software
Github user cloud-fan commented on a diff in the pull request:
https://github.com/apache/spark/pull/15048#discussion_r78331097
--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/rules.scala
---
@@ -68,7 +68,7 @@ class ResolveDataSource(sparkSession:
Github user djvulee commented on the issue:
https://github.com/apache/spark/pull/15052
@srowen I update PR using an increment way to update the DiskBytesSpilled
metrics.
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Github user cloud-fan commented on a diff in the pull request:
https://github.com/apache/spark/pull/14988#discussion_r78330099
--- Diff:
sql/hive/src/main/scala/org/apache/spark/sql/hive/execution/HiveTableScanExec.scala
---
@@ -164,4 +164,28 @@ case class HiveTableScanExec(
Github user djvulee commented on the issue:
https://github.com/apache/spark/pull/15052
@srowen you are right, I will correct it soon.
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Github user SparkQA commented on the issue:
https://github.com/apache/spark/pull/13513
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Github user AmplabJenkins commented on the issue:
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Github user jerryshao commented on the issue:
https://github.com/apache/spark/pull/13513
@zsxwing , thanks a lot for your comments, I did several refactorings:
1. Abstract and consolidate `FileStreamSinkLog` and `FileStreamSourceLog`,
now they share same code path to do
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Github user yanboliang commented on the issue:
https://github.com/apache/spark/pull/12819
@zhengruifeng I saw your implementation switch the training process from
RDD operation to Dataset operation with UDAF. I think we should do some
performance test to verify there is no
GitHub user clockfly opened a pull request:
https://github.com/apache/spark/pull/15056
[SPARK-17503][Core] Fix memory leak in Memory store when unable to cache
the whole RDD
## What changes were proposed in this pull request?
Memory store may throws OutOfMemoryError
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Github user yanboliang commented on a diff in the pull request:
https://github.com/apache/spark/pull/12819#discussion_r78325688
--- Diff:
mllib/src/main/scala/org/apache/spark/ml/classification/NaiveBayes.scala ---
@@ -109,10 +120,51 @@ class NaiveBayes @Since("1.5.0") (
Github user yanboliang commented on a diff in the pull request:
https://github.com/apache/spark/pull/12819#discussion_r78325579
--- Diff:
mllib/src/main/scala/org/apache/spark/ml/classification/NaiveBayes.scala ---
@@ -98,7 +99,17 @@ class NaiveBayes @Since("1.5.0") (
*/
Github user srowen commented on the issue:
https://github.com/apache/spark/pull/15000
My only hesitation about this is that this property really only exists to
print it in the shell. Is there a good use case for it otherwise? I know it's
minor but want to make sure we're not just
Github user SparkQA commented on the issue:
https://github.com/apache/spark/pull/15053
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Github user srowen commented on the issue:
https://github.com/apache/spark/pull/15053
Jenkins test this please
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Github user srowen commented on the issue:
https://github.com/apache/spark/pull/15052
Given how DiskBytesSpilled is used, and still used in other parts of the
code, this doesn't look correct. It seems to be a global that is always
incremented. Here you reset the value in certain
Github user adrian-wang commented on the issue:
https://github.com/apache/spark/pull/15011
@hvanhovell I have checked with Hive and MySQL, they all support dropping
current database. By asking user to switch to another database before drop the
current one is not enough though, if
Github user SparkQA commented on the issue:
https://github.com/apache/spark/pull/15055
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GitHub user VinceShieh opened a pull request:
https://github.com/apache/spark/pull/15055
[SPARK-17462][MLLIB]use VersionUtils to parse Spark version strings
## What changes were proposed in this pull request?
Several places in MLlib use custom regexes or other approaches to
Github user dbtsai commented on a diff in the pull request:
https://github.com/apache/spark/pull/14834#discussion_r78321887
--- Diff:
mllib/src/main/scala/org/apache/spark/ml/classification/LogisticRegression.scala
---
@@ -460,33 +577,74 @@ class LogisticRegression
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https://github.com/apache/spark/pull/14834#discussion_r78321247
--- Diff:
mllib/src/main/scala/org/apache/spark/ml/classification/LogisticRegression.scala
---
@@ -323,32 +382,33 @@ class LogisticRegression
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Github user dbtsai commented on a diff in the pull request:
https://github.com/apache/spark/pull/14834#discussion_r78321146
--- Diff:
mllib/src/main/scala/org/apache/spark/ml/classification/LogisticRegression.scala
---
@@ -311,8 +350,28 @@ class LogisticRegression @Since("1.2.0")
Github user HyukjinKwon commented on the issue:
https://github.com/apache/spark/pull/11729
gentle ping @mbaddar1
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Github user HyukjinKwon commented on the issue:
https://github.com/apache/spark/pull/11079
+1 for not a problem.
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Github user SparkQA commented on the issue:
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GitHub user gatorsmile opened a pull request:
https://github.com/apache/spark/pull/15054
[SPARK-17502] [SQL] Fix Multiple Bugs in DDL Statements on Temporary Views
[WIP]
### What changes were proposed in this pull request?
- When the permanent tables/views do not exist but the
Github user HyukjinKwon commented on the issue:
https://github.com/apache/spark/pull/15020
ping @bigdatatraining
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