Github user mengxr commented on the pull request:
https://github.com/apache/spark/pull/1983#issuecomment-56989958
@witgo Since we are converging on a GraphX-based implementation and
distributed representation of the topic model, do you mind closing this PR?
Thanks!
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Github user witgo closed the pull request at:
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Github user allwefantasy commented on the pull request:
https://github.com/apache/spark/pull/1983#issuecomment-55549348
@witgo i have saw you new performance test configurationã I will try your
new code and test in my data today
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Github user allwefantasy commented on the pull request:
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@witgo i have try ur latest code in my corpus ã it will not Stuck in
broadcasting . However ,some exception are throwã
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Github user mengxr commented on the pull request:
https://github.com/apache/spark/pull/1983#issuecomment-55381531
@witgo @allwefantasy
English | èªå¨ç¿»è¯çä¸æ
|
Let's try to keep the comments in English as much as possible. |
Github user mengxr commented on the pull request:
https://github.com/apache/spark/pull/1983#issuecomment-55381621
@witgo @allwefantasy We had an offline discussion about LDA's
implementation. Please check the JIRA page for the notes.
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Github user witgo commented on the pull request:
https://github.com/apache/spark/pull/1983#issuecomment-55391092
@mengxr @allwefantasy
The current broadcast-based implementation, especially in the corpus is
large, the performance loss is more serious. Next week I will
Github user witgo commented on a diff in the pull request:
https://github.com/apache/spark/pull/1983#discussion_r17490277
--- Diff: mllib/src/main/scala/org/apache/spark/mllib/clustering/LDA.scala
---
@@ -0,0 +1,397 @@
+/*
+ * Licensed to the Apache Software Foundation
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Github user witgo commented on the pull request:
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@allwefantasy
I have updated the code, you can try the latest code.
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Github user allwefantasy commented on the pull request:
https://github.com/apache/spark/pull/1983#issuecomment-55343319
@witgo
好çãå¦æææ´æ°å请éç¥æãæè¿éä¹å¯ä»¥ç¬¬ä¸æ¶é´è¿è¡æµè¯ã
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Github user witgo commented on the pull request:
https://github.com/apache/spark/pull/1983#issuecomment-55223673
@allwefantasy Sparkæ¯å¯ä»¥è°æ´executoråæ¶è¿è¡çtaskæ°éç.
å¦æä½ æ³è®©æ¯ä¸ªexecutoråæ¶å¯ä»¥è¿è¡17个task.
Github user allwefantasy commented on the pull request:
https://github.com/apache/spark/pull/1983#issuecomment-55238978
@witgo æè°¢è¿ä¸ªæå·§çå享ã
æç®åè¿éå°ä¸ä¸ªé®é¢ãæ¨å¤©ä½
é®æè¿è¾¹24wææ¡£çè¯æ°æ¯å¤å°ï¼æç»è®¡äºä¸ï¼æ¯ 2400w
Github user witgo commented on the pull request:
https://github.com/apache/spark/pull/1983#issuecomment-55280269
@allwefantasy ç°æç代ç
å¨è¿ä»£è®¡ç®è¿ç¨ä¸å建äºå¤ªå¤çTopicModelå®ä¾,
æç°å¨æ£å¨å°è¯è§£å³è¿ä¸ªé®é¢.
æè°¢ä½ çåé¦.
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Github user allwefantasy commented on the pull request:
https://github.com/apache/spark/pull/1983#issuecomment-55089256
@witgo çäºä½ çæ§è½æµè¯ ä½
éé¢æ²¡ææå°è¿ä»£æ¬¡æ°ãæ¯å¤å°æ¬¡è¿ä»£å¢ï¼ä¸ä¸ªå°æ¶å°±å®æäºã
Github user witgo commented on the pull request:
https://github.com/apache/spark/pull/1983#issuecomment-55094784
@allwefantasy
æçæµè¯è¯æåºå¤§å°æ¯`196558` 个ææ¡£, `7897767` 个è¯.
è¿ä»£æ¬¡æ°æ¯`100`次.
ä½ ç24ä¸ææ¡£æ»å
±æå¤ä¸ªè¯?
ä½
Github user srowen commented on the pull request:
https://github.com/apache/spark/pull/1983#issuecomment-55095034
(Pardon, I think it's important to also summarize in English, as the lingua
franca of the project, for the benefit of other readers.)
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Github user witgo commented on the pull request:
https://github.com/apache/spark/pull/1983#issuecomment-55095890
@allwefantasy
æ认为è¿éç代ç ` Document(parts(0).toInt,(0 until
wordInfo.value.size).map(k= values.getOrElse(k,0)).toArray)`
æ¯æç¹é®é¢ç..
Github user witgo commented on the pull request:
https://github.com/apache/spark/pull/1983#issuecomment-55096559
@srowen I will try to translate the comments into English
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Github user allwefantasy commented on the pull request:
https://github.com/apache/spark/pull/1983#issuecomment-55129263
@witgo é£å°±æ¯æç¯äºé误ï¼å¯¹Document ä¸content
ç解éäºãæ以为content
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@witgo 西é¢è¿ä¸æ®µä»£ç å¯ä»¥å¤çº¿ç¨åä¹ï¼
for (i - 0 until content.length) {
val term = content(i)
val
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Github user witgo commented on the pull request:
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test this please
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Github user witgo commented on the pull request:
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@mengxr This patch removed the `accumulable` operation . repair formula
errors in `dropOneDistSampler ` method and some of the performance
optimization. About how I
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Github user mengxr commented on the pull request:
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@witgo Thanks for working on LDA! Could you briefly describe what you
changed in this PR? The major feedback of #476 is how we store the model, which
may be worth more
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