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Github user LucaCanali commented on the issue:
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I have implemented the changes as from the latest comments, namely inlined
the method.
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Github user tgravescs commented on the issue:
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yeah that doesn't reproduce it, you really need a fetch failure in there
and would think some kind of randomness or order in the map output, I've
started to try to write something to reproduce
Github user NiharS commented on the issue:
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Can't be a coincidence...it's failing two pyspark streaming tests,
test_binary_records_stream and test_text_file_stream (same two earlier, I
misanalyzed it when I said it was ML stuff). I'm running
Github user mccheah commented on the issue:
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@cloud-fan @tgravescs was wondering if we could get an ETA on this landing?
Also, I tried running something analogous to the example script from the
description of
Github user srowen commented on the issue:
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The .ml implementation wraps the .mllib implementation. The .mllib package
isn't really being developed anymore, even though parts of it are still
'active' insofar as they underpin the .ml
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@gatorsmile I am closing this since the changes in UnionRDD have been
already merged to the master:
https://github.com/apache/spark/commit/32da87dfa451fff677ed9316f740be2abdbff6a4
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retest this please
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Hi guys, I know I'm arriving a little bit late to the party. I just had a
quick question: does this PR include the "renew service pod" that is described
in the spec? I went through that doc and
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--- Diff: pom.xml ---
@@ -1770,6 +1770,10 @@
org.apache.hive
hive-storage-api
+
+
Github user ifilonenko commented on the issue:
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@vanzin This PR does not include the renew service pod as that will live as
a separate micro-service. But the current design has the `KubernetesClient`
creating the delegation tokens and storing
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LGTM, then let me ask @gatorsmile
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test this please
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Why is the unit test added for the ml package and not the mllib package?
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--- Diff: R/pkg/R/generics.R ---
@@ -799,10 +807,18 @@ setGeneric("array_sort", function(x) {
standardGeneric("array_sort") })
#' @name NULL
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yes, thanks, forgot to update in the Scala API, so I updated all them
accordingly. Thanks.
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@kiszk Could you help move the related test cases in StreamSuite.scala to
here?
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@ifilonenko I don't think we need to extend this to other resource
managers, since users of Kubernetes/Mesos RMs probably don't want to use use
multiple Hadoop clusters at the same time that
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Ok, closing
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@@ -33,6 +32,7 @@ RUN apk add --no-cache python
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--- Diff: core/src/main/java/org/apache/spark/ExecutorPlugin.java ---
@@ -0,0 +1,38 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under
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org.apache.hive
hive-storage-api
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--- Diff: core/src/main/scala/org/apache/spark/executor/Executor.scala ---
@@ -136,6 +136,15 @@ private[spark] class Executor(
// for fetching remote
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Github user srowen commented on the issue:
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More info ... the test failure symptom is that this test never completes,
just repeating a `RejectedExecutionException`:
```
- FileBasedWriteAheadLog - handling file errors while reading
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}
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also, I don't recall anywhere in spark that depends/sets MDC...
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@holdenk and @mccheah any other comments before merge?
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GitHub user vinodkc opened a pull request:
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[SPARK-25301][SQL] When a view uses an UDF from a non default database,
Spark analyser throws AnalysisException
## What changes were proposed in this pull request?
When a hive view uses an UDF
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@@ -604,4 +604,14 @@ package object config {
.intConf
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@@ -136,6 +136,15 @@ private[spark] class Executor(
// for fetching remote
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+/*
+ * Licensed to the Apache Software Foundation (ASF)
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retest this please
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The one concern is whether this behavior change impacts anything else. Now
some exceptions will cause an actual exception in a caller to methods like
Await, rather than just logging and continuing.
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ok to test
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@@ -48,6 +48,8 @@ class
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