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tested on windows, r-hub/r-devel
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@akopich If you want to cache the input dataset, create JIAR to discuss it
first. It's another issue I think. This JIAR also related to input caching
issues:
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LGTM pending Jenkins
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package org.apache.spark.sql.test
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Github user WeichenXu123 commented on the issue:
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> We'll actually only have to run an O(n log n) sort on continuous feature
values once (i.e. in the FeatureVector constructor), since once the continuous
features are sorted we can update them
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closing in favor of https://github.com/apache/spark/pull/19579
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[SPARK-22356][SQL] data source table should support overlapped columns
between data and partition schema
## What changes were proposed in this pull request?
This is a regression
Github user viirya commented on a diff in the pull request:
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--- Diff: sql/core/src/main/scala/org/apache/spark/sql/Dataset.scala ---
@@ -3102,7 +3103,12 @@ class Dataset[T] private[sql](
* Collect all elements
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+/*
+ * Licensed to the Apache
Github user stanzhai commented on the issue:
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Hi @gatorsmile , I've added some test cases, and passed on my machine.
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* Collect all
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Github user viirya commented on the issue:
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Nice catch! LGTM with two minor comments.
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Github user rezasafi commented on the issue:
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Sorry for the delay. It seems that to be able to commit the same rdd in
different stages we need to use stageId. So the jobId and other configurations
in the write method of SparkHadoopWriter
Github user dongjoon-hyun commented on the issue:
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Thank you for review, @gatorsmile and @cloud-fan . Especially, @cloud-fan
's opinion is my original approach in #17980 and #18953 (before Aug 16). I
cannot agree any more.
>
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*/
def
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Github user jerryshao commented on the issue:
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@sitalkedia would you please reopen this PR, I think the second issue I
fixed before is not valid anymore, for the first issue the fix is no difference
compared to here.
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Verified again, looks like the 2nd bullet is not valid anymore, I cannot
reproduce it in latest master branch, this might have already been fixed in
SPARK-13054.
So only first issue
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@cloud-fan Two remaining do while loop are updated.
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@huaxingao Good catch! Thanks.
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Github user jerryshao commented on the issue:
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@vanzin , in the current code `stageIdToTaskIndices` cannot be used to
track number of running tasks, because this structure doesn't remove task index
from itself when task is finished
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@@ -1619,11 +1619,38 @@ def to_arrow_type(dt):
arrow_type = pa.decimal(dt.precision, dt.scale)
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# If a nullable integer series has been promoted to
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I wonder if we should add cache() for lda training data, even not for this
feature.
@srowen Not sure where we're on caching the training data or not for
different algorithms. Appreciate
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Github user mccheah commented on a diff in the pull request:
https://github.com/apache/spark/pull/19468#discussion_r147017517
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resource-managers/kubernetes/core/src/main/scala/org/apache/spark/scheduler/cluster/k8s/ExecutorPodFactory.scala
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Github user mccheah commented on a diff in the pull request:
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--- Diff:
resource-managers/kubernetes/core/src/main/scala/org/apache/spark/scheduler/cluster/k8s/KubernetesClusterSchedulerBackend.scala
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