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[SPARK-3838][examples][mllib][python] Word2Vec example in python #2952
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@@ -162,6 +162,38 @@ for((synonym, cosineSimilarity) <- synonyms) { | |
| } | ||
| {% endhighlight %} | ||
| </div> | ||
| <div data-lang="python"> | ||
| {% highlight python %} | ||
| # This example uses text8 file from http://mattmahoney.net/dc/text8.zip | ||
| # The file was unziped and split into multiple lines using | ||
| # grep -o -E '\w+(\W+\w+){0,15}' text8 > text8_lines | ||
| # This was done so that the example can be run in local mode | ||
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| from pyspark import SparkContext | ||
| from pyspark.mllib.feature import Word2Vec | ||
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| USAGE = ("bin/spark-submit --driver-memory 4g " | ||
| "examples/src/main/python/mllib/word2vec.py text8_lines") | ||
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| if __name__ == "__main__": | ||
| if len(sys.argv) < 2: | ||
| print USAGE | ||
| return | ||
| file_path = sys.argv[1] | ||
| sc = SparkContext(appName='Word2Vec') | ||
| inp = sc.textFile("text8_lines").map(lambda row: [row]) | ||
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Contributor
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| word2vec = Word2Vec() | ||
| model = word2vec.fit(inp) | ||
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| synonyms = model.findSynonyms('china', 40) | ||
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| for word, cosine_distance in synonyms: | ||
| print "{}: {}".format(word, cosine_distance) | ||
| sc.stop() | ||
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Contributor
There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. remove the indent or remove this line. |
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| {% endhighlight %} | ||
| </div> | ||
| </div> | ||
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| ## StandardScaler | ||
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| # | ||
| # Licensed to the Apache Software Foundation (ASF) under one or more | ||
| # contributor license agreements. See the NOTICE file distributed with | ||
| # this work for additional information regarding copyright ownership. | ||
| # The ASF licenses this file to You under the Apache License, Version 2.0 | ||
| # (the "License"); you may not use this file except in compliance with | ||
| # the License. You may obtain a copy of the License at | ||
| # | ||
| # http://www.apache.org/licenses/LICENSE-2.0 | ||
| # | ||
| # Unless required by applicable law or agreed to in writing, software | ||
| # distributed under the License is distributed on an "AS IS" BASIS, | ||
| # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | ||
| # See the License for the specific language governing permissions and | ||
| # limitations under the License. | ||
| # | ||
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| # This example uses text8 file from http://mattmahoney.net/dc/text8.zip | ||
| # The file was unziped and split into multiple lines using | ||
| # grep -o -E '\w+(\W+\w+){0,15}' text8 > text8_lines | ||
| # This was done so that the example can be run in local mode | ||
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Contributor
There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. Could you provide runnable bash commands here to generate "text8_lines"
Contributor
Author
There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. @davies I just jued the command listed in the comments.
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There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. It's better to including download and unzip. |
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| import sys | ||
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Contributor
There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. insert an empty line after |
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| from pyspark import SparkContext | ||
| from pyspark.mllib.feature import Word2Vec | ||
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| USAGE = ("bin/spark-submit --driver-memory 4g " | ||
| "examples/src/main/python/mllib/word2vec.py text8_lines") | ||
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| if __name__ == "__main__": | ||
| if len(sys.argv) < 2: | ||
| print USAGE | ||
| return | ||
| file_path = sys.argv[1] | ||
| sc = SparkContext(appName='Word2Vec') | ||
| inp = sc.textFile("text8_lines").map(lambda row: [row]) | ||
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Contributor
There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. ditto: |
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| word2vec = Word2Vec() | ||
| model = word2vec.fit(inp) | ||
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| synonyms = model.findSynonyms('china', 40) | ||
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| for word, cosine_distance in synonyms: | ||
| print "{}: {}".format(word, cosine_distance) | ||
| sc.stop() | ||
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It's better to put a simplified version here, then could have a link to the example
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@davies simplify the docs should i just remove the Usage line and the creation of the context?
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it should look like the scala one, I think the following should be enough: