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--- Diff:
mllib/src/main/scala/org/apache/spark/ml/regression/GeneralizedLinearRegression.scala
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@@ -944,15 +981,27 @@ class
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@@ -406,6 +435,14 @@ object
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--- Diff:
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---
@@ -168,6 +179,7 @@ private[regression] trait
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--- Diff:
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@@ -798,77 +798,160 @@ class
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Github user sethah commented on a diff in the pull request:
https://github.com/apache/spark/pull/16715#discussion_r100970965
--- Diff: mllib/src/main/scala/org/apache/spark/ml/feature/LSH.scala ---
@@ -222,17 +222,18 @@ private[ml] abstract class LSHModel[T <: LSHModel[T]]
}
Github user sethah commented on a diff in the pull request:
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--- Diff: python/pyspark/ml/feature.py ---
@@ -755,6 +945,103 @@ def maxAbs(self):
@inherit_doc
+class MinHashLSH(JavaEstimator,
Github user sethah commented on a diff in the pull request:
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--- Diff:
examples/src/main/scala/org/apache/spark/examples/ml/MinHashLSHExample.scala ---
@@ -37,38 +43,45 @@ object MinHashLSHExample {
(0,
Github user sethah commented on a diff in the pull request:
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--- Diff:
examples/src/main/scala/org/apache/spark/examples/ml/MinHashLSHExample.scala ---
@@ -21,9 +21,15 @@ package org.apache.spark.examples.ml
//
Github user zhzhan commented on the issue:
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@tejasapatil Do you want to fix the BufferedRowIterator for
WholeStageCodegenExec as well? As for inner join, the LinkedList currentRows
would cause the same issue as it buffer the rows from inner
Github user Pashugan commented on the issue:
https://github.com/apache/spark/pull/16913
There must be some misunderstanding. May I have a chance you have a look at
my micro-patch because it has nothing to do with the driver and its options. In
fact, it fixes the call of the "launcher
Github user jiangxb1987 commented on the issue:
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Thank you for doing this, this looks good to me.
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Github user asfgit closed the pull request at:
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Github user gatorsmile commented on the issue:
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LGTM. Merging to master!
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Github user jinxing64 commented on a diff in the pull request:
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--- Diff:
core/src/test/scala/org/apache/spark/scheduler/DAGSchedulerSuite.scala ---
@@ -2161,6 +2161,48 @@ class DAGSchedulerSuite extends SparkFunSuite
Github user jinxing64 commented on the issue:
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@kayousterhout
I've refined accordingly. Sorry for the stupid mistake I made. Please take
another look at this : )
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@kayousterhout
I've refined accordingly, please take another look : )
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--- Diff: docs/ml-features.md ---
@@ -1558,6 +1558,15 @@ for more details on the API.
{% include_example
Github user Yunni commented on a diff in the pull request:
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--- Diff: python/pyspark/ml/feature.py ---
@@ -120,6 +122,198 @@ def getThreshold(self):
return self.getOrDefault(self.threshold)
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--- Diff:
examples/src/main/scala/org/apache/spark/examples/ml/MinHashLSHExample.scala ---
@@ -37,38 +38,44 @@ object MinHashLSHExample {
(0,
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--- Diff:
examples/src/main/python/ml/bucketed_random_projection_lsh_example.py ---
@@ -0,0 +1,81 @@
+#
+# Licensed to the Apache Software Foundation
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--- Diff:
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@@ -38,40 +39,45 @@ object
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--- Diff:
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---
@@ -35,6 +35,8 @@
import
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--- Diff: python/pyspark/ml/feature.py ---
@@ -120,6 +122,198 @@ def getThreshold(self):
return self.getOrDefault(self.threshold)
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--- Diff: python/pyspark/ml/feature.py ---
@@ -120,6 +122,198 @@ def getThreshold(self):
return self.getOrDefault(self.threshold)
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--- Diff:
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@@ -111,8 +111,8 @@ class BucketedRandomProjectionLSHModel
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--- Diff: python/pyspark/ml/feature.py ---
@@ -120,6 +122,198 @@ def getThreshold(self):
return self.getOrDefault(self.threshold)
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--- Diff: python/pyspark/ml/feature.py ---
@@ -120,6 +122,198 @@ def getThreshold(self):
return self.getOrDefault(self.threshold)
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Github user windpiger commented on the issue:
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@gatorsmile I'd like to take that.
https://issues.apache.org/jira/browse/SPARK-19583 Thanks~
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test this please
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cc @hvanhovell @jiangxb1987
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Github user ooq commented on the issue:
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@yaooqinn Do you have any benchmarks on the performance difference? I think
pointTo() is pretty cheap. And does the patch pass the tests? I think valueRow
is not updated correctly in your patch.
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Github user gatorsmile commented on the issue:
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Let me rewrite the test cases in Scala.
```Scala
val df = spark.range(0, 1, 1, 5)
assert(df.rdd.getNumPartitions == 5)
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cc @srowen
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--- Diff: docs/structured-streaming-kafka-integration.md ---
@@ -119,6 +119,124 @@ ds3.selectExpr("CAST(key AS STRING)", "CAST(value AS
STRING)")
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