Github user viirya commented on a diff in the pull request:
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--- Diff: python/pyspark/sql/functions.py ---
@@ -2142,18 +2159,26 @@ def udf(f=None, returnType=StringType()):
| 8| JOHN DOE|
Github user jerryshao commented on the issue:
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Hi @klion26 , sorry for the late response. Can we please understand the
problem first, would you please describe your problem in detail and how to
reproduce your issue?
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--- Diff:
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@@ -169,6 +267,125 @@
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Github user ConeyLiu commented on the issue:
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Hi @cloud-fan, thanks for reviewing. The code has updated, pls take a look.
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Github user michaelmior commented on the issue:
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Whoops. Sorry about that. I opened the PR via the CLI so I didn't see the
pointer on the web interface. I should have known better though. Updated!
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GitHub user cloud-fan opened a pull request:
https://github.com/apache/spark/pull/19265
[SPARK-22047][flaky test] HiveExternalCatalogVersionsSuite
## What changes were proposed in this pull request?
This PR tries to download Spark for each test run, to make sure each test
Github user viirya commented on a diff in the pull request:
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--- Diff: python/pyspark/sql/functions.py ---
@@ -2142,18 +2159,26 @@ def udf(f=None, returnType=StringType()):
| 8| JOHN DOE|
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Github user jerryshao commented on the issue:
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LGTM, let me retest this again.
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@marktab You should close merged PR. Thanks!
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Github user maver1ck commented on the issue:
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I check with some samples and code with float can trigger errors.
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retest this please
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Github user klion26 commented on the issue:
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Hi @jerryshao, thank you for your reply.
# Problem
the problem is for long running jobs which run on **yarn with HA** will
request more executors than it requests.
# How to
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Github user jerryshao commented on the issue:
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@michaelmior would you please follow the instruction
(https://spark.apache.org/contributing.html) to update PR title and create a
corresponding JIRA, thanks!
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Github user jerryshao commented on the issue:
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@zsxwing @jiangxb1987 would you please help to review this PR when you have
time, thanks a lot.
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Jenkins, retest this please.
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@srowen rebased against `master` to get the test ignore
https://github.com/apache/spark/commit/894a7561de2c2ff01fe7fcc5268378161e9e5643
, should be good to retest now :)
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retest this please.
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retest this please
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ok to test
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Github user fjh100456 commented on the issue:
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Encounter two problems:
1. I tried to fix it in the order of 'compression' > 'parquet.compression'
> 'spark.sql.parquet.compression. codec', but found 'parquet.compression' may
come from a
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Github user maropu commented on the issue:
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I though, if this limit highly depends on JVM implementations, better to
put the limit as a global variable somewhere (e.g., `ARRAY_INT_MAX` in
`spark.util.Utils` or other places)? As another
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--- Diff:
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@@ -352,11 +374,16 @@ object TypeCoercion {
Github user gatorsmile commented on the issue:
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It looks good, but the actual code should be very simple if you are writing
using the Scala way
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Thanks! Merged to master.
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@@ -624,7 +639,9 @@ class FsHistoryProviderSuite extends
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ok to test.
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Did you enable RM or NM recovery, can you please clarify it?
Normally, if we assume there's are 2 containers running on this NM, after
10 minutes, RM will detect the failure of NM and
Github user HyukjinKwon commented on the issue:
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Seems fine to me too as is. @maver1ck, I think you could take out `[WIP]`
and let it be merged.
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Github user a10y commented on a diff in the pull request:
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--- Diff: python/pyspark/sql/dataframe.py ---
@@ -1810,17 +1810,20 @@ def _to_scala_map(sc, jm):
return sc._jvm.PythonUtils.toScalaMap(jm)
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Github user WeichenXu123 commented on the issue:
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Looks not the reason. maybe issues somewhere else. Let me run test later.
Thanks!
But there is some small issues in test:
Don't include gen data time:
```
val start =
Github user vanzin commented on a diff in the pull request:
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--- Diff:
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@@ -65,53 +60,76 @@ private[spark] class LiveListenerBus(conf: SparkConf)
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Github user gatorsmile commented on a diff in the pull request:
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--- Diff:
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@@ -925,6 +925,12 @@ object SQLConf {
.intConf
Github user srowen commented on the issue:
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Yeah, agree, it could be some global constant. I don't think it should be
configurable. Ideally it's determined from the JVM, but don't know a way to do
that.
In many cases, assuming
Github user vanzin commented on a diff in the pull request:
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@@ -720,19 +633,67 @@ private[history] class
Github user gatorsmile commented on the issue:
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I can see the value, but it does not perform well in most cases if we using
JDBC connection. Instead of adding the extra dialect to upstream, could you
please add Hive as a separate data source?
GitHub user Taaffy opened a pull request:
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Incorrect Metric reported in MetricsReporter.scala
Current implementation for processingRate-total uses wrong metric:
mistakenly uses inputRowsPerSecond instead of processedRowsPerSecond
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Github user maver1ck commented on the issue:
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OK. It passed all tests, so let merge it
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Github user akopich commented on the issue:
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Ping @jkbradley .
Thank you @WeichenXu123 one again for the comment! Please, have a look.
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[WIP][SPARK-20628][CORE] Blacklist nodes when they transition to
DECOMMISSIONING state in YARN
## What changes were proposed in this pull request?
Dynamic cluster configurations where cluster
Github user gatorsmile commented on the issue:
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I think we should not do it, because no DB vendor does it.
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can we retest this ? The unknown return code is not related to the code.
Thanks.
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retest this please
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Github user WeichenXu123 commented on the issue:
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@viirya I run the code, you're right, most of time cost on the executedPlan
generation (The old version code). thanks!
But can you append benchmark comparison with `RDD.aggregate` version?
Github user rxin commented on the issue:
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What does this even mean?
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retest this please
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--- Diff:
sql/catalyst/src/main/scala/org/apache/spark/sql/internal/SQLConf.scala ---
@@ -925,6 +925,12 @@ object SQLConf {
.intConf
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@@ -925,6 +925,12 @@ object SQLConf {
.intConf
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--- Diff:
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@@ -462,31 +462,44 @@ final class OnlineLDAOptimizer extends
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@@ -462,31 +462,44 @@ final class OnlineLDAOptimizer extends
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Can one of the admins verify this patch?
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Please make a JIRA @Taaffy
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@WeichenXu123 Do you mean we keep both inputCol and inputCols in
`Bucketizer`?
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