Github user HyukjinKwon commented on the issue:
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Ah, yup. There are few tests for old Pandas which were tested only when
Pandas version was lower, and I rewrote them to be tested when both Pandas
version is lower and missing. Let me clarify
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[SPARK-23290][SQL][PYTHON][BACKPORT-2.3] Use datetime.date for date type
when converting Spark DataFrame to Pandas DataFrame.
## What changes were proposed in this pull request?
This is a
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Seems fine.
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@@ -1655,15 +1655,17 @@ case class Left(str:
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looks like this PR doesn't skip the "old Pandas" tests, but rewrite them?
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Thank you @felixcheung, @yhuai, @ueshin and @BryanCutler for reviewing this.
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Merged to master.
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@ueshin can you send a new PR for 2.3? it conflicts, thanks!
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LGTM, merging to master/2.3!
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@mgaido91 agree that it is better to normalize centers
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thanks, merging to master/2.3!
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retest this please
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After went through the changes here, I think we only need to update 2 nodes
to include table name in `nodeName`: hive table scan and in-memory table scan.
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--- Diff:
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@@ -169,10 +171,12 @@ case class LogicalRDD(
case class
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LGTM pending Jenkins.
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--- Diff: python/pyspark/sql/tests.py ---
@@ -4062,18 +4062,42 @@ def test_vectorized_udf_unsupported_types(self):
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for field in arrow_schema])
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After more thoughts, I feel it's reasonable to include table information in
the node name.
The UI displays `nodeName` in the plan graph, and displays `simpleString`
in a pop-up window
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also cc @cloud-fan @gatorsmile @sameeragarwal
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retest this please
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@HyukjinKwon SGTM!
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LGTM, thanks for fixing this.
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I originally thought similarly but after another look into this again, it
seems it would rather be better to keep it consistent with what Pandas does for
now. FYI, seems `datetime.date` ->
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jenkins, retest this please.
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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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@@ -61,6 +61,9 @@ case class
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@sameeragarwal @kiszk @viirya @gatorsmile
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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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--- Diff:
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@@ -327,6 +327,14 @@ object TypeCoercion {
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@@ -0,0 +1,89 @@
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+ * Licensed to the Apache Software
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---
@@ -17,16 +17,23 @@
package org.apache.spark.status
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Thank you for review, @gatorsmile and @HyukjinKwon .
Sure, this is for Apache Spark 2.4.
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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
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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)
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@mgaido91 what do you think about the right follow-up here? as in your
comment just above?
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for PR 20485 at commit
Github user cloud-fan commented on the issue:
https://github.com/apache/spark/pull/20485
retest this please
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