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https://issues.apache.org/jira/browse/SPARK-13103?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15130187#comment-15130187
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Louis Liu commented on SPARK-13103:
-----------------------------------
I'm sorry, you are right. The negative numbers doesn't matter.
Those code shall explain the problem:
>>> from pyspark.mllib.feature import HashingTF, IDF
>>> hashtf = HashingTF()
>>> hash('的問題哦')
-234244945207099392
>>> hash('豪們都把')
8689153874407194624
>>> hashtf.indexOf('的問題哦')
0
>>> hashtf.indexOf('豪們都把')
0
> HashTF dosn't count TF correctly
> --------------------------------
>
> Key: SPARK-13103
> URL: https://issues.apache.org/jira/browse/SPARK-13103
> Project: Spark
> Issue Type: Bug
> Components: MLlib
> Affects Versions: 1.6.0
> Environment: Ubuntu 14.04
> Python 3.4.3
> Reporter: Louis Liu
>
> I wrote a Python program to calculate frequencies of n-gram sequences with
> HashTF.
> But it generate a strange output. It found more "一一下嗎" than "一一下".
> HashTF gets words' index with hash()
> But hashes of some Chinese words are negative.
> Ex:
> >>> hash('一一下嗎')
> -6433835193350070115
> >>> hash('一一下')
> -5938108283593463272
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