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Posted to reviews@spark.apache.org by Ishiihara <gi...@git.apache.org> on 2014/08/14 01:25:41 UTC
[GitHub] spark pull request: [SPARK-2907][MLlib] Word2Vec performance impro...
GitHub user Ishiihara opened a pull request:
https://github.com/apache/spark/pull/1932
[SPARK-2907][MLlib] Word2Vec performance improve
@mengxr Please review the code. Adding weights in reduceByKey soon.
Only output model entry for words appeared in the partition before merging and use reduceByKey to combine model. In general, this implementation is 30s or so faster than implementation using big array.
You can merge this pull request into a Git repository by running:
$ git pull https://github.com/Ishiihara/spark Word2Vec-improve2
Alternatively you can review and apply these changes as the patch at:
https://github.com/apache/spark/pull/1932.patch
To close this pull request, make a commit to your master/trunk branch
with (at least) the following in the commit message:
This closes #1932
----
commit aa2ab36c6a9fa22e759ccb99352394dd6d6317e0
Author: Liquan Pei <li...@gmail.com>
Date: 2014-08-13T12:45:17Z
use reduceByKey to combine models
commit 9075e1cba5ae64add2986514be99dc51083ff177
Author: Liquan Pei <li...@gmail.com>
Date: 2014-08-13T23:17:58Z
combine syn0Global and syn1Global to synGlobal
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[GitHub] spark pull request: [MLlib] Word2Vec performance improvement
Posted by SparkQA <gi...@git.apache.org>.
Github user SparkQA commented on the pull request:
https://github.com/apache/spark/pull/1932#issuecomment-52452252
[QA tests have finished](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/18732/consoleFull) for PR 1932 at commit [`d5377a9`](https://github.com/apache/spark/commit/d5377a9ea607d015fce4a2ac7eebdb467db5f46f).
* This patch **passes** unit tests.
* This patch merges cleanly.
* This patch adds no public classes.
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[GitHub] spark pull request: [SPARK-3097][MLlib] Word2Vec performance impro...
Posted by asfgit <gi...@git.apache.org>.
Github user asfgit closed the pull request at:
https://github.com/apache/spark/pull/1932
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[GitHub] spark pull request: [MLlib] Word2Vec performance improvement
Posted by SparkQA <gi...@git.apache.org>.
Github user SparkQA commented on the pull request:
https://github.com/apache/spark/pull/1932#issuecomment-52220608
QA results for PR 1932:<br>- This patch FAILED unit tests.<br>- This patch merges cleanly<br>- This patch adds no public classes<br><br>For more information see test ouptut:<br>https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/18547/consoleFull
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[GitHub] spark pull request: [MLlib] Word2Vec performance improvement
Posted by mengxr <gi...@git.apache.org>.
Github user mengxr commented on a diff in the pull request:
https://github.com/apache/spark/pull/1932#discussion_r16222200
--- Diff: mllib/src/main/scala/org/apache/spark/mllib/feature/Word2Vec.scala ---
@@ -284,16 +284,15 @@ class Word2Vec extends Serializable with Logging {
val newSentences = sentences.repartition(numPartitions).cache()
val initRandom = new XORShiftRandom(seed)
- var syn0Global =
- Array.fill[Float](vocabSize * vectorSize)((initRandom.nextFloat() - 0.5f) / vectorSize)
- var syn1Global = new Array[Float](vocabSize * vectorSize)
-
+ var synGlobal =
--- End diff --
There is no slicing across both syn0 and syn1, right?
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[GitHub] spark pull request: [MLlib] Word2Vec performance improvement
Posted by mengxr <gi...@git.apache.org>.
Github user mengxr commented on a diff in the pull request:
https://github.com/apache/spark/pull/1932#discussion_r16221788
--- Diff: mllib/src/main/scala/org/apache/spark/mllib/feature/Word2Vec.scala ---
@@ -284,16 +284,15 @@ class Word2Vec extends Serializable with Logging {
val newSentences = sentences.repartition(numPartitions).cache()
val initRandom = new XORShiftRandom(seed)
- var syn0Global =
- Array.fill[Float](vocabSize * vectorSize)((initRandom.nextFloat() - 0.5f) / vectorSize)
- var syn1Global = new Array[Float](vocabSize * vectorSize)
-
+ var synGlobal =
--- End diff --
Do we want to keep `syn0` and `syn1` in order to have an easy mapping from/to the original C implementation? It reduces the code maintenance cost.
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[GitHub] spark pull request: [MLlib] Word2Vec performance improvement
Posted by SparkQA <gi...@git.apache.org>.
Github user SparkQA commented on the pull request:
https://github.com/apache/spark/pull/1932#issuecomment-52408585
[QA tests have started](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/18683/consoleFull) for PR 1932 at commit [`cad2011`](https://github.com/apache/spark/commit/cad201140970df237fc5492691c774e4d2d83763).
* This patch merges cleanly.
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[GitHub] spark pull request: [MLlib] Word2Vec performance improvement
Posted by mengxr <gi...@git.apache.org>.
Github user mengxr commented on the pull request:
https://github.com/apache/spark/pull/1932#issuecomment-52449340
Jenkins, test this please.
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[GitHub] spark pull request: [MLlib] Word2Vec performance improvement
Posted by mengxr <gi...@git.apache.org>.
Github user mengxr commented on a diff in the pull request:
https://github.com/apache/spark/pull/1932#discussion_r16221793
--- Diff: mllib/src/main/scala/org/apache/spark/mllib/feature/Word2Vec.scala ---
@@ -321,42 +320,46 @@ class Word2Vec extends Serializable with Logging {
// Hierarchical softmax
var d = 0
while (d < bcVocab.value(word).codeLen) {
- val l2 = bcVocab.value(word).point(d) * vectorSize
+ val ind = bcVocab.value(word).point(d)
+ val l2 = ind * vectorSize
// Propagate hidden -> output
- var f = blas.sdot(vectorSize, syn0, l1, 1, syn1, l2, 1)
+ synModify(ind) += 1
+ var f = blas.sdot(vectorSize, syn, l1, 1, syn, l2, 1)
if (f > -MAX_EXP && f < MAX_EXP) {
val ind = ((f + MAX_EXP) * (EXP_TABLE_SIZE / MAX_EXP / 2.0)).toInt
f = expTable.value(ind)
val g = ((1 - bcVocab.value(word).code(d) - f) * alpha).toFloat
- blas.saxpy(vectorSize, g, syn1, l2, 1, neu1e, 0, 1)
- blas.saxpy(vectorSize, g, syn0, l1, 1, syn1, l2, 1)
+ blas.saxpy(vectorSize, g, syn, l2, 1, neu1e, 0, 1)
+ blas.saxpy(vectorSize, g, syn, l1, 1, syn, l2, 1)
}
d += 1
}
- blas.saxpy(vectorSize, 1.0f, neu1e, 0, 1, syn0, l1, 1)
+ blas.saxpy(vectorSize, 1.0f, neu1e, 0, 1, syn, l1, 1)
+ synModify(lastWord) += 1
}
}
a += 1
}
pos += 1
}
- (syn0, syn1, lwc, wc)
+ (syn, lwc, wc)
}
- Iterator(model)
- }
- val (aggSyn0, aggSyn1, _, _) =
- partial.treeReduce { case ((syn0_1, syn1_1, lwc_1, wc_1), (syn0_2, syn1_2, lwc_2, wc_2)) =>
- val n = syn0_1.length
- val weight1 = 1.0f * wc_1 / (wc_1 + wc_2)
- val weight2 = 1.0f * wc_2 / (wc_1 + wc_2)
- blas.sscal(n, weight1, syn0_1, 1)
- blas.sscal(n, weight1, syn1_1, 1)
- blas.saxpy(n, weight2, syn0_2, 1, syn0_1, 1)
- blas.saxpy(n, weight2, syn1_2, 1, syn1_1, 1)
- (syn0_1, syn1_1, lwc_1 + lwc_2, wc_1 + wc_2)
+ val synLocal = model._1
+ val synOut = new PrimitiveKeyOpenHashMap[Int, Array[Float]](vocabSize * 2)
+ var index = 0
+ while(index < 2 * vocabSize) {
+ if (synModify(index) != 0) {
+ synOut.update(index, synLocal.slice(index * vectorSize, (index + 1) * vectorSize))
+ }
+ index += 1
}
- syn0Global = aggSyn0
- syn1Global = aggSyn1
+ Iterator(synOut)
+ }
+ synGlobal = partial.flatMap(x => x).reduceByKey {
+ case (v1,v2) =>
+ blas.saxpy(vectorSize, 1.0f, v2, 1, v1, 1)
+ v1
+ }.collect().sortBy(_._1).flatMap(x => x._2)
--- End diff --
updating `synGlobal` in-place is more memory-efficient. We don't need to allocate new storage and sort.
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[GitHub] spark pull request: [MLlib] Word2Vec performance improvement
Posted by SparkQA <gi...@git.apache.org>.
Github user SparkQA commented on the pull request:
https://github.com/apache/spark/pull/1932#issuecomment-52409509
[QA tests have finished](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/18683/consoleFull) for PR 1932 at commit [`cad2011`](https://github.com/apache/spark/commit/cad201140970df237fc5492691c774e4d2d83763).
* This patch **passes** unit tests.
* This patch merges cleanly.
* This patch adds no public classes.
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[GitHub] spark pull request: [MLlib] Word2Vec performance improvement
Posted by Ishiihara <gi...@git.apache.org>.
Github user Ishiihara commented on a diff in the pull request:
https://github.com/apache/spark/pull/1932#discussion_r16222127
--- Diff: mllib/src/main/scala/org/apache/spark/mllib/feature/Word2Vec.scala ---
@@ -284,16 +284,15 @@ class Word2Vec extends Serializable with Logging {
val newSentences = sentences.repartition(numPartitions).cache()
val initRandom = new XORShiftRandom(seed)
- var syn0Global =
- Array.fill[Float](vocabSize * vectorSize)((initRandom.nextFloat() - 0.5f) / vectorSize)
- var syn1Global = new Array[Float](vocabSize * vectorSize)
-
+ var synGlobal =
--- End diff --
We can keep syn0 and syn1, but it adds some unnecessary slicing operations on array.
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[GitHub] spark pull request: [MLlib] Word2Vec performance improvement
Posted by mengxr <gi...@git.apache.org>.
Github user mengxr commented on a diff in the pull request:
https://github.com/apache/spark/pull/1932#discussion_r16223658
--- Diff: mllib/src/main/scala/org/apache/spark/mllib/feature/Word2Vec.scala ---
@@ -284,16 +284,15 @@ class Word2Vec extends Serializable with Logging {
val newSentences = sentences.repartition(numPartitions).cache()
val initRandom = new XORShiftRandom(seed)
- var syn0Global =
- Array.fill[Float](vocabSize * vectorSize)((initRandom.nextFloat() - 0.5f) / vectorSize)
- var syn1Global = new Array[Float](vocabSize * vectorSize)
-
+ var synGlobal =
--- End diff --
Making composite key in the output RDD so reduceByKey can distinguish whether the update is for syn0 or syn1?
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[GitHub] spark pull request: [MLlib] Word2Vec performance improvement
Posted by mengxr <gi...@git.apache.org>.
Github user mengxr commented on a diff in the pull request:
https://github.com/apache/spark/pull/1932#discussion_r16221784
--- Diff: mllib/src/main/scala/org/apache/spark/mllib/feature/Word2Vec.scala ---
@@ -34,7 +34,7 @@ import org.apache.spark.mllib.rdd.RDDFunctions._
import org.apache.spark.rdd._
import org.apache.spark.util.Utils
import org.apache.spark.util.random.XORShiftRandom
-
+import org.apache.spark.util.collection.PrimitiveKeyOpenHashMap
/**
--- End diff --
add an empty line after imports
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[GitHub] spark pull request: [MLlib] Word2Vec performance improvement
Posted by Ishiihara <gi...@git.apache.org>.
Github user Ishiihara commented on a diff in the pull request:
https://github.com/apache/spark/pull/1932#discussion_r16222465
--- Diff: mllib/src/main/scala/org/apache/spark/mllib/feature/Word2Vec.scala ---
@@ -284,16 +284,15 @@ class Word2Vec extends Serializable with Logging {
val newSentences = sentences.repartition(numPartitions).cache()
val initRandom = new XORShiftRandom(seed)
- var syn0Global =
- Array.fill[Float](vocabSize * vectorSize)((initRandom.nextFloat() - 0.5f) / vectorSize)
- var syn1Global = new Array[Float](vocabSize * vectorSize)
-
+ var synGlobal =
--- End diff --
We need to perform reduceByKey on both syn0 and syn1 and we have different updated keys for syn0 and syn1. To perform reduceByKey of syn0 and syn1 together, we need to have a unique key and one way to achieve this is to treat i + vocabSize as the key for syn1(i). Then after we collect, we need to slice to update syn0Global and syn1Global. Any better idea?
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[GitHub] spark pull request: [MLlib] Word2Vec performance improvement
Posted by mengxr <gi...@git.apache.org>.
Github user mengxr commented on the pull request:
https://github.com/apache/spark/pull/1932#issuecomment-52144922
Jenkins, test this please.
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[GitHub] spark pull request: [SPARK-3097][MLlib] Word2Vec performance impro...
Posted by loveconan1988 <gi...@git.apache.org>.
Github user loveconan1988 commented on the pull request:
https://github.com/apache/spark/pull/1932#issuecomment-52456557
------------------ 原始邮件 ------------------
发件人: "asfgit";<no...@github.com>;
发送时间: 2014年8月18日(星期一) 下午2:31
收件人: "apache/spark"<sp...@noreply.github.com>;
主题: Re: [spark] [SPARK-3097][MLlib] Word2Vec performance improvement(#1932)
Closed #1932 via 3c8fa50.
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[GitHub] spark pull request: [MLlib] Word2Vec performance improvement
Posted by mengxr <gi...@git.apache.org>.
Github user mengxr commented on a diff in the pull request:
https://github.com/apache/spark/pull/1932#discussion_r16221791
--- Diff: mllib/src/main/scala/org/apache/spark/mllib/feature/Word2Vec.scala ---
@@ -321,42 +320,46 @@ class Word2Vec extends Serializable with Logging {
// Hierarchical softmax
var d = 0
while (d < bcVocab.value(word).codeLen) {
- val l2 = bcVocab.value(word).point(d) * vectorSize
+ val ind = bcVocab.value(word).point(d)
+ val l2 = ind * vectorSize
// Propagate hidden -> output
- var f = blas.sdot(vectorSize, syn0, l1, 1, syn1, l2, 1)
+ synModify(ind) += 1
+ var f = blas.sdot(vectorSize, syn, l1, 1, syn, l2, 1)
if (f > -MAX_EXP && f < MAX_EXP) {
val ind = ((f + MAX_EXP) * (EXP_TABLE_SIZE / MAX_EXP / 2.0)).toInt
f = expTable.value(ind)
val g = ((1 - bcVocab.value(word).code(d) - f) * alpha).toFloat
- blas.saxpy(vectorSize, g, syn1, l2, 1, neu1e, 0, 1)
- blas.saxpy(vectorSize, g, syn0, l1, 1, syn1, l2, 1)
+ blas.saxpy(vectorSize, g, syn, l2, 1, neu1e, 0, 1)
+ blas.saxpy(vectorSize, g, syn, l1, 1, syn, l2, 1)
}
d += 1
}
- blas.saxpy(vectorSize, 1.0f, neu1e, 0, 1, syn0, l1, 1)
+ blas.saxpy(vectorSize, 1.0f, neu1e, 0, 1, syn, l1, 1)
+ synModify(lastWord) += 1
}
}
a += 1
}
pos += 1
}
- (syn0, syn1, lwc, wc)
+ (syn, lwc, wc)
}
- Iterator(model)
- }
- val (aggSyn0, aggSyn1, _, _) =
- partial.treeReduce { case ((syn0_1, syn1_1, lwc_1, wc_1), (syn0_2, syn1_2, lwc_2, wc_2)) =>
- val n = syn0_1.length
- val weight1 = 1.0f * wc_1 / (wc_1 + wc_2)
- val weight2 = 1.0f * wc_2 / (wc_1 + wc_2)
- blas.sscal(n, weight1, syn0_1, 1)
- blas.sscal(n, weight1, syn1_1, 1)
- blas.saxpy(n, weight2, syn0_2, 1, syn0_1, 1)
- blas.saxpy(n, weight2, syn1_2, 1, syn1_1, 1)
- (syn0_1, syn1_1, lwc_1 + lwc_2, wc_1 + wc_2)
+ val synLocal = model._1
+ val synOut = new PrimitiveKeyOpenHashMap[Int, Array[Float]](vocabSize * 2)
+ var index = 0
+ while(index < 2 * vocabSize) {
+ if (synModify(index) != 0) {
+ synOut.update(index, synLocal.slice(index * vectorSize, (index + 1) * vectorSize))
+ }
+ index += 1
}
- syn0Global = aggSyn0
- syn1Global = aggSyn1
+ Iterator(synOut)
+ }
+ synGlobal = partial.flatMap(x => x).reduceByKey {
+ case (v1,v2) =>
--- End diff --
move `case (v1, v2) =>` to previous line and add a space after `,`
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[GitHub] spark pull request: [MLlib] Word2Vec performance improvement
Posted by SparkQA <gi...@git.apache.org>.
Github user SparkQA commented on the pull request:
https://github.com/apache/spark/pull/1932#issuecomment-52449489
[QA tests have started](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/18732/consoleFull) for PR 1932 at commit [`d5377a9`](https://github.com/apache/spark/commit/d5377a9ea607d015fce4a2ac7eebdb467db5f46f).
* This patch merges cleanly.
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[GitHub] spark pull request: [MLlib] Word2Vec performance improvement
Posted by SparkQA <gi...@git.apache.org>.
Github user SparkQA commented on the pull request:
https://github.com/apache/spark/pull/1932#issuecomment-52214890
QA tests have started for PR 1932. This patch merges cleanly. <br>View progress: https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/18547/consoleFull
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[GitHub] spark pull request: [MLlib] Word2Vec performance improvement
Posted by mengxr <gi...@git.apache.org>.
Github user mengxr commented on the pull request:
https://github.com/apache/spark/pull/1932#issuecomment-52408516
Jenkins, test this please.
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[GitHub] spark pull request: [SPARK-3097][MLlib] Word2Vec performance impro...
Posted by mengxr <gi...@git.apache.org>.
Github user mengxr commented on the pull request:
https://github.com/apache/spark/pull/1932#issuecomment-52456438
LGTM. Merged into master and branch-1.1. Thanks!
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