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--- Diff: dev/deps/spark-deps-hadoop-2.6 ---
@@ -182,7 +182,7 @@ slf4j-api-1.7.16.jar
slf4j-log4j12-1.7.16.jar
snakeyaml-1.15.jar
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--- Diff:
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@@ -179,7 +179,7 @@ private[ui] abstract class
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--- Diff: sql/core/src/main/scala/org/apache/spark/sql/SQLImplicits.scala
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GitHub user ueshin opened a pull request:
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[SPARK-23290][SQL][PYTHON] Use datetime.date for date type when converting
Spark DataFrame to Pandas DataFrame.
## What changes were proposed in this pull request?
In #18664, there was a
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cc @BryanCutler @icexelloss @HyukjinKwon @cloud-fan @gatorsmile
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--- Diff: pom.xml ---
@@ -185,6 +185,10 @@
2.8
1.8
1.0.0
+
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this is targeting master, right?
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Just FYI, this will not be merged to 2.3
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Any updates? this PR seems to address critical issue:
https://issues.apache.org/jira/browse/SPARK-3162
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--- Diff: python/pyspark/sql/dataframe.py ---
@@ -667,6 +667,51 @@ def repartition(self, numPartitions, *cols):
else:
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--- Diff: python/pyspark/sql/dataframe.py ---
@@ -667,6 +667,51 @@ def repartition(self, numPartitions, *cols):
else:
raise
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Retest this please.
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--- Diff: docs/sql-programming-guide.md ---
@@ -1776,6 +1776,42 @@ working with timestamps in `pandas_udf`s to get the
best performance, see
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@@ -250,11 +257,20 @@ class SQLQueryTestSuite extends QueryTest with
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Can one of the admins verify this patch?
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LGTM since 1.4.2 does not seem to include major changes based on [the
release summary](https://orc.apache.org/news/2018/01/23/ORC-1.4.2/).
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LGTM pending tests.
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--- Diff:
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@@ -51,6 +51,52 @@ private[v1] class
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--- Diff:
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@@ -93,6 +93,7 @@ private[spark] trait UIRoot {
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--- Diff: core/src/main/scala/org/apache/spark/util/Utils.scala ---
@@ -2168,7 +2169,23 @@ private[spark] object Utils extends Logging {
// We need
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[SPARK-23182][CORE] Allow enabling TCP keep alive on the master RPC
connections.
## What changes were proposed in this pull request?
Make it possible for the master to enable TCP keep
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--- Diff:
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@@ -0,0 +1,89 @@
+/*
+ * Licensed to the Apache Software
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--- Diff: python/pyspark/sql/dataframe.py ---
@@ -2020,8 +2021,6 @@ def _to_corrected_pandas_type(dt):
return np.int32
elif
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@@ -0,0 +1,40 @@
+/*
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Right, @kiszk !
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merging this to master/2.3
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package
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I've updated this to no longer require #20387. It wasn't relying on those
changes at all. @gatorsmile, @cloud-fan, what do you think about getting this
into 2.3.0?
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--- Diff: python/pyspark/sql/dataframe.py ---
@@ -2020,8 +2021,6 @@ def _to_corrected_pandas_type(dt):
return np.int32
elif type(dt)
Github user wangyum commented on the issue:
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The failure is due to flaky test suite.
```
org.apache.spark.sql.hive.client.HiveClientSuites.(It is not a test it is a
sbt.testing.NestedSuiteSelector)
```
jenkins, retest this
Github user dongjoon-hyun commented on the issue:
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Thank you for review, @gatorsmile and @HyukjinKwon .
Sure, this is for Apache Spark 2.4.
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@@ -0,0 +1,89 @@
+/*
+ * Licensed to the Apache Software
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@@ -17,16 +17,23 @@
package org.apache.spark.status
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@@ -327,6 +327,14 @@ object TypeCoercion {
GitHub user cloud-fan opened a pull request:
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[SPARK-23312][SQL][followup] add a config to turn off vectorized cache
reader
## What changes were proposed in this pull request?
https://github.com/apache/spark/pull/20483 tried to
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@@ -61,6 +61,9 @@ case class
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@sameeragarwal @kiszk @viirya @gatorsmile
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[SPARK-23310][CORE][FOLLOWUP] Fix Java style check issues.
## What changes were proposed in this pull request?
This is a follow-up of #20492 which broke lint-java checks.
This pr fixes
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jenkins, retest this please.
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--- Diff: python/pyspark/serializers.py ---
@@ -230,6 +230,9 @@ def create_array(s, t):
s =
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> Seems like pyarrow ignores `type` parameter for `pa.Array.from_pandas()`
and consider it as binary type when the type is string type and the string
values are `str` instead of `unicode` in Python
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Github user heary-cao commented on a diff in the pull request:
https://github.com/apache/spark/pull/18555#discussion_r166171819
--- Diff:
core/src/main/scala/org/apache/spark/internal/config/package.scala ---
@@ -231,6 +315,9 @@ package object config {
private[spark] val
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