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lgtm
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@HyukjinKwon no worries. Rebased.
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--- Diff: project/SparkBuild.scala ---
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"JAVA_HOME" ->
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Sorry, @icexelloss. Mind resolving the conflict?
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Hm .. yea but we can't simply flush and ignore the stdout specifically from
sitecustomize unless we define a kind of an additional protocol like this
because we can't simply distinguish if the
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Branch 2.2
## What changes were proposed in this pull request?
(Please fill in changes proposed in this fix)
## How was this patch tested?
(Please explain how this
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Can one of the admins verify this patch?
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[SPARK-23381][CORE] Murmur3 hash generates a different value from other
implementations
## What changes were proposed in this pull request?
Murmur3 hash generates a different value from the
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--- Diff: mllib/src/main/scala/org/apache/spark/ml/param/params.scala ---
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Github user mgaido91 commented on the issue:
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@gatorsmile thanks for your comment. I moved it to a separate rule and
added more tests.
As per the added value of this rule, I see 3 main points:
1. Let's imagine that a user exposes
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retest this please
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--- Diff: python/pyspark/sql/types.py ---
@@ -1766,15 +1781,13 @@ def _check_series_convert_timestamps_localize(s,
from_timezone, to_timezone):
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--- Diff: python/pyspark/sql/tests.py ---
@@ -2867,6 +2867,35 @@ def
test_create_dataframe_required_pandas_not_found(self):
Github user viirya commented on the issue:
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Yeah, IMHO, when the user loads a model from old version into new version
to run, I think it is reasonable to run it with current default value because
the param is not explicitly set and should use
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@viirya that's a good question. Honestly my idea is that if the user
doesn't set a value, he/she doesn't care about it, so it is good to use the new
version default IMHO. But it is also true that
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Seems it happened to fix this case too:
```python
spark.conf.set("spark.sql.execution.arrow.enabled", "false")
df = spark.createDataFrame([[bytearray("a")]])
df.toPandas()
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cc @ueshin, @BryanCutler and @icexelloss, could you take a look please when
you have some time?
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--- Diff: mllib/src/main/scala/org/apache/spark/ml/param/params.scala ---
@@ -864,6 +864,11 @@ trait Params extends Identifiable with Serializable {
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--- Diff: python/pyspark/sql/dataframe.py ---
@@ -1941,12 +1941,24 @@ def toPandas(self):
timezone = None
if
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--- Diff: mllib/src/main/scala/org/apache/spark/ml/param/params.scala ---
@@ -864,6 +864,11 @@ trait Params extends Identifiable with Serializable {
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--- Diff: python/pyspark/sql/dataframe.py ---
@@ -1955,38 +1967,34 @@ def toPandas(self):
return
Github user viirya commented on the issue:
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@mgaido91 I also considered the issue of changed default values across
versions. I'm not sure which is more reasonable, using old version's default
value or using current version's default value.
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[SPARK-23380][PYTHON] Make toPandas fall back to Arrow optimization
disabled when schema is not supported in Arrow optimization
## What changes were proposed in this pull request?
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@@ -864,6 +864,11 @@ trait Params extends Identifiable with Serializable {
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--- Diff:
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@@ -931,7 +925,8 @@ private[spark] object RandomForest extends Logging {
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[SPARK-23377][ML] Fixes Bucketizer with multiple columns persistence bug
## What changes were proposed in this pull request?
Since 2.3, `Bucketizer` supports multiple input/output columns.
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retest this please
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retest this please
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--- Diff:
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---
@@ -139,15 +139,15 @@ class
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I am careful to say this out .. but let me leave my +0 for
https://github.com/apache/spark/pull/20397#issuecomment-361345426. One option
might be a similar name with `DataWriterFactory` but
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https://github.com/apache/spark/pull/20397#discussion_r167392663
--- Diff:
sql/core/src/test/scala/org/apache/spark/sql/execution/streaming/RateSourceV2Suite.scala
---
@@ -78,7 +78,7 @@ class RateSourceV2Suite
Github user gatorsmile commented on a diff in the pull request:
https://github.com/apache/spark/pull/20407#discussion_r167392901
--- Diff:
sql/catalyst/src/main/scala/org/apache/spark/sql/internal/SQLConf.scala ---
@@ -156,6 +156,15 @@ object SQLConf {
.booleanConf
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