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[SPARK-23386][DEPLOY] enable direct application links in SHS before replay
## What changes were proposed in this pull request?
Enable direct job links already in the scan thread before
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cc @jiangxb1987
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@jerryshao Could you have a time to help to review?
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[SPARK-23385][CORE] Allow SparkUITab to be customized adding in Sparkâ¦
â¦Conf and loaded when creating SparkUI
## What changes were proposed in this pull request?
It would be
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--- Diff: python/pyspark/sql/dataframe.py ---
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[SPARK-23384][WEB-UI]When it has no incomplete(completed) applications
found, the last updated time is not formatted and client local time zone is not
show in history server web ui.
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Github user dongjoon-hyun commented on the issue:
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First of all, ORC 1.4.2 was very safe because it has only ORC-235 removing
redundant dependencies.
For ORC 1.4.3, the following five patches are included.
1. ORC-298 Move
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@dongjoon-hyun Could you go over the list of the resolved JIRAs in ORC
1.4.2 and 1.4.3 that could cause the regressions?
We need to know the impact and the risk. If possible, also added
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Sure. No problem. BTW, is it applicable for Apache Spark 2.3?
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+1 for 1.4.3
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--- Diff:
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@@ -98,10 +99,22 @@ public UnsafeKVExternalSorter(
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[SPARK-17147][STREAMING][KAFKA] Allow non-consecutive offsets
## What changes were proposed in this pull request?
Add a configuration spark.streaming.kafka.allowNonConsecutiveOffsets to
Github user gatorsmile commented on the issue:
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@omalley Thanks for your quick reply!
@dongjoon-hyun Maybe we should directly bump to 1.4.3?
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[SPARK-23383][Build][Minor]Make a distribution should exit with usage while
detecting wrong options
## What changes were proposed in this pull request?
```shell
./dev/make-distribution.sh
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Github user omalley commented on the issue:
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Sorry, I forgot to transition the jira issues for the ORC 1.4.3, so they
didn't show up in the search from the notes.
The list of jiras closed by the 1.4.3 release is:
Github user gatorsmile commented on the issue:
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I am wondering what is the difference between ORC 1.4.3 and ORC 1.4.2?
Their release notes are the SAME.
https://orc.apache.org/news/2018/02/09/ORC-1.4.3/ and
Github user zhengruifeng commented on a diff in the pull request:
https://github.com/apache/spark/pull/20518#discussion_r167417459
--- Diff:
mllib/src/main/scala/org/apache/spark/mllib/clustering/KMeans.scala ---
@@ -745,4 +763,27 @@ private[spark] class CosineDistanceMeasure
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[spark-23382][WEB-UI]Spark Streaming ui about the contents of the for need
to have hidden and show features, when the table records very much.
## What changes were proposed in this
Github user viirya commented on the issue:
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Not only `threshold`, the default params of `NaiveBayes`,
`LogisticRegression` (maybe more, I'm looking up now) are all set in the
estimator, not in their model. The models are received the default
Github user heary-cao commented on the issue:
https://github.com/apache/spark/pull/20516
@srowen, I think this is a function provided by spark for port use,
One is that the spark user only needs to specify start port and the offset
of ports (spark.port.maxRetries settings), the
Github user LantaoJin commented on the issue:
https://github.com/apache/spark/pull/20532
Thanks everyone. So just close it? Or easily leave an enabled switch like
blockUpdated dose? I am all OK.
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--- Diff: python/pyspark/sql/dataframe.py ---
@@ -1941,12 +1941,24 @@ def toPandas(self):
timezone = None
if
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Thank you, @kiszk .
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retest this please
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Github user MrBago commented on the issue:
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I believe this will break persistence for LogisticRegression. I believe the
issue is that the `threshold` param on LogisticRegressionModel doesn't get a
default directly, but only gets it during the
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Retest this please.
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Retest this please.
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--- Diff:
sql/hive/src/main/scala/org/apache/spark/sql/hive/client/HiveClientImpl.scala
---
@@ -292,10 +292,12 @@ private[hive] class
Github user bersprockets commented on the issue:
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>yea but we can't simply flush and ignore the stdout specifically from
sitecustomize unless we define a kind of an additional protocol like this
because we can't simply distinguish if the
Github user mgaido91 commented on the issue:
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thank you @gatorsmile for taking a look at this. Let me know if there is
something I can/should improve. Thanks.
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@mgaido91 Yeah, we definitely should include this rule. We just need more
careful review and comprehensive test cases. Thanks for your work!
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