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Thanks a lot @zsxwing for your comments. Yes I agree with you that current
approach of replaying event logs suffers a lot for streaming application. The
reason I
Github user dbtsai commented on the pull request:
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@iyounus Maybe in this case, `WeightedLeastSqures ` should drop those
columns so the model can be still trained.
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--- Diff:
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@@ -359,6 +361,18 @@ object StructType extends AbstractDataType {
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--- Diff:
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retest this please
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I'll close this pr and discuss this issue in #10898.
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I'll close this pr and I discuss this in #10928.
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--- Diff:
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@@ -248,9 +248,7 @@ private[history] class FsHistoryProvider(conf:
Github user holdenk commented on a diff in the pull request:
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--- Diff: python/pyspark/sql/functions.py ---
@@ -263,6 +263,38 @@ def corr(col1, col2):
return Column(sc._jvm.functions.corr(_to_java_column(col1),
GitHub user andrewor14 opened a pull request:
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[SPARK-13055] SQLHistoryListener throws ClassCastException
This is an existing issue uncovered recently by #10835. The reason for the
exception was because the `SQLHistoryListener` gets all
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retest this please
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retest this please
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--- Diff: python/pyspark/mllib/clustering.py ---
@@ -783,17 +865,34 @@ def train(cls, rdd, k=10, maxIterations=20,
docConcentration=-1.0,
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--- Diff: python/pyspark/mllib/clustering.py ---
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def
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--- Diff: python/pyspark/mllib/clustering.py ---
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Learning algorithm for Gaussian Mixtures
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--- Diff: python/pyspark/mllib/clustering.py ---
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@since('1.5.0')
def
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retest this please
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@zsxwing
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retest this please
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--- Diff: python/pyspark/mllib/clustering.py ---
@@ -49,6 +49,9 @@ class KMeansModel(Saveable, Loader):
"""A clustering model derived from the
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--- Diff: python/pyspark/mllib/clustering.py ---
@@ -304,9 +345,11 @@ def predictSoft(self, x):
"""
Find the membership of point 'x'
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--- Diff: python/pyspark/mllib/clustering.py ---
@@ -289,8 +328,10 @@ def predict(self, x):
Find the cluster to which the point 'x' or each point
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--- Diff: python/pyspark/mllib/clustering.py ---
@@ -170,7 +173,43 @@ class KMeans(object):
@since('0.9.0')
def train(cls, rdd, k,
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--- Diff: python/pyspark/mllib/clustering.py ---
@@ -170,7 +173,43 @@ class KMeans(object):
@since('0.9.0')
def train(cls, rdd, k,
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--- Diff:
mllib/src/main/scala/org/apache/spark/mllib/clustering/KMeans.scala ---
@@ -482,12 +482,15 @@ object KMeans {
/**
* Trains a k-means
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--- Diff: python/pyspark/mllib/clustering.py ---
@@ -289,8 +328,10 @@ def predict(self, x):
Find the cluster to which the point 'x' or each point
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--- Diff: python/pyspark/mllib/clustering.py ---
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@since('0.9.0')
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--- Diff: python/pyspark/mllib/clustering.py ---
@@ -170,7 +173,43 @@ class KMeans(object):
@since('0.9.0')
def train(cls, rdd, k,
Github user asfgit closed the pull request at:
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--- Diff: python/pyspark/sql/functions.py ---
@@ -263,6 +263,38 @@ def corr(col1, col2):
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@srowen commons-codec is already in the section
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Thanks! I'm going to merging this to master.
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@davies side note: The JIRA number is wrong.
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@shivaram any suggestion on how to proceed?
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I'll close this pr and discuss this in #10928.
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--- Diff:
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@@ -328,6 +328,8 @@ KW_WEEK: 'WEEK'|'WEEKS';
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fragment
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--- Diff:
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@@ -124,6 +124,18 @@ int getVersionNumber() {
*/
Github user levin-royl commented on the pull request:
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Hi, just wanted to know if there are any unhanded items on my end WRT this
change. Thanks.
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Github user SparkQA commented on the pull request:
https://github.com/apache/spark/pull/10968#issuecomment-176046912
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Github user yanboliang commented on the pull request:
https://github.com/apache/spark/pull/10469#issuecomment-176070210
@jkbradley You PR looks good and get merged, thanks!
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Github user adrian-wang commented on a diff in the pull request:
https://github.com/apache/spark/pull/10762#discussion_r51094651
--- Diff:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/CheckAnalysis.scala
---
@@ -104,6 +105,9 @@ trait CheckAnalysis {
Github user AmplabJenkins commented on the pull request:
https://github.com/apache/spark/pull/10960#issuecomment-176068652
Merged build finished. Test FAILed.
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Github user SparkQA commented on the pull request:
https://github.com/apache/spark/pull/10966#issuecomment-176069616
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