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> @darabos . Thank you for trying to make a contribution. However, we had
better discuss on that JIRA first before making a PR. Especially, for
SPARK-20144 which is discussed already, it does.
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@pgandhi999 thanks for the changes. I will review them tomorrow.
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@mgaido91 . The failure is relevant to this PR. Could you take a look?
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As @tejasapatil suggested above, this fallback is not suggested to be on in
a prod setting. It could also impact the system health (e.g., the other
concurrent queries that are querying the same H
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This sets the major Python version of the docker
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Also, https://github.com/apache/spark/pull/22614#discussion_r223172392
proposes a better and safer solution by introducing `exponential backoff with
retries`. @kmanamcheri Could you update your P
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> a better and safer solution by introducing exponential backoff with
retries
I'm confused about that suggestion. What is being retried? The user query?
The HMS call? What is changing in bet
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Github user BryanCutler commented on the issue:
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I think there is a typo in your example in the description
```
@pandas_udf('double', PandasUDFType.GROUPED_AGG)
def avg(v):
return v.mean()
return avg
```
I think y
Github user icexelloss commented on the issue:
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@BryanCutler Yes that was a typo :) Thanks!
I am also +1 to support numpy data structure in addition to Pandas. So
happy to discuss here or separately.
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@gatorsmile, @tejasapatil was reviewing the code before I added the new
config option. I have asked him to review the new code. Lets see what his
thoughts are on that. I have also asked him clar
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How about pandas UDF? How about using RDD APIs? Do we face the same issues?
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@gatorsmile did you get a chance to think about this?
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Github user MaxGekk commented on the issue:
https://github.com/apache/spark/pull/22654
@gatorsmile Please, take a look at this.
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Github user MaxGekk commented on the issue:
https://github.com/apache/spark/pull/22429
@zsxwing Please, have a look at the PR one more time.
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Github user MaxGekk commented on the issue:
https://github.com/apache/spark/pull/22656
@HyukjinKwon Could you look at the PR, please.
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Github user vanzin commented on a diff in the pull request:
https://github.com/apache/spark/pull/22615#discussion_r223509836
--- Diff: dev/create-release/release-build.sh ---
@@ -191,9 +191,17 @@ if [[ "$1" == "package" ]]; then
make_binary_release() {
NAME=$1
Github user SparkQA commented on the issue:
https://github.com/apache/spark/pull/22623
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Github user zsxwing commented on the issue:
https://github.com/apache/spark/pull/22628
Is it supposed to the flaky ChunkFetchIntegrationSuite?
http://spark-tests.appspot.com/test-details?suite_name=org.apache.spark.network.ChunkFetchIntegrationSuite&test_name=fetchFileChunk
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Github user NiharS commented on a diff in the pull request:
https://github.com/apache/spark/pull/22504#discussion_r223512824
--- Diff: core/src/main/scala/org/apache/spark/internal/Logging.scala ---
@@ -192,7 +211,15 @@ private[spark] object Logging {
defaultSparkLog4jC
Github user SparkQA commented on the issue:
https://github.com/apache/spark/pull/22482
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Github user zsxwing commented on a diff in the pull request:
https://github.com/apache/spark/pull/22173#discussion_r223513440
--- Diff:
common/network-common/src/main/java/org/apache/spark/network/TransportContext.java
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@@ -77,17 +82,54 @@
private static final MessageEnc
Github user srowen commented on the issue:
https://github.com/apache/spark/pull/22615
I guess we've just pinged @shaneknapp ! But I figured the jobs would simply
fail and could be removed at leisure.
Yes, this mechanism is a little weird but may be the simplest thing here. I
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