{"id":36757,"date":"2023-11-29T19:35:57","date_gmt":"2023-12-20T06:56:02","guid":{"rendered":"https:\/\/www.silicloud.com\/zh\/blog\/%e4%bd%bf%e7%94%a8-apache-spark-%e8%bf%9b%e8%a1%8c-word2vec\/"},"modified":"2024-05-04T11:21:21","modified_gmt":"2024-05-04T03:21:21","slug":"%e4%bd%bf%e7%94%a8-apache-spark-%e8%bf%9b%e8%a1%8c-word2vec","status":"publish","type":"post","link":"https:\/\/www.silicloud.com\/zh\/blog\/%e4%bd%bf%e7%94%a8-apache-spark-%e8%bf%9b%e8%a1%8c-word2vec\/","title":{"rendered":"\u4f7f\u7528 Apache Spark \u8fdb\u884c Word2Vec"},"content":{"rendered":"

Word2Vec\uff1a\u8bcd\u5411\u91cf<\/h4>\n

Word2Vec\u662f\u7531\u8c37\u6b4c\u7814\u7a76\u6240\u57282013\u5e74\u63d0\u51fa\u7684\u4e00\u4e2a\u7b97\u6cd5\uff0c\u8be5\u7b97\u6cd5\u57fa\u4e8e\u5047\u8bbe”\u5728\u76f8\u540c\u4e0a\u4e0b\u6587\u4e2d\u4f7f\u7528\u7684\u5355\u8bcd\u5177\u6709\u76f8\u540c\u7684\u542b\u4e49”\uff0c\u4f7f\u7528\u5411\u91cf\u6765\u8868\u793a\u5355\u8bcd\u7684\u7279\u5f81\u3002\u901a\u8fc7\u5c06\u5355\u8bcd\u53ca\u5176\u542b\u4e49\u5411\u91cf\u5316\uff0c\u8bed\u4e49\u4e0a\u76f8\u4f3c\u7684\u5355\u8bcd\u88ab\u8868\u793a\u4e3a\u5728\u7a7a\u95f4\u4e2d\u9760\u8fd1\u7684\u5411\u91cf\uff0c\u56e0\u6b64\u8be5\u7b97\u6cd5\u53ef\u7528\u4e8e\u63d0\u53d6\u8fd1\u4e49\u8bcd\u3002<\/p>\n

\u4e3b\u9898 (Zh\u01d4 t\u00ed)<\/h4>\n

\u8fd9\u6b21\u6211\u4eec\u5c06\u4f7f\u7528Apache Spark\u7684MLlib\uff0c\u5c1d\u8bd5\u4f7f\u7528Word2Vec\u3002\u4f5c\u4e3a\u4e3b\u9898\uff0c\u6211\u4eec\u5c06\u52a0\u8f7d\u7ef4\u57fa\u767e\u79d1\u7684\u201c\u662d\u548c\u201d\u548c\u201c\u5e73\u6210\u201d\u7b49\u6587\u7ae0\uff0c\u7136\u540e\u5c06\u5b83\u4eec\u4f5c\u4e3a\u8f93\u5165\u6765\u751f\u6210\u6a21\u578b\u3002\u6211\u4eec\u60f3\u8981\u770b\u770b\uff0c\u5f53\u6211\u4eec\u8f93\u5165\u5404\u79cd\u672f\u8bed\u65f6\uff0c\u80fd\u5f97\u5230\u54ea\u4e9b\u8fd1\u4e49\u8bcd\u3002<\/p>\n

\u6838\u5fc3\u7a0b\u5e8f (natively in Chinese)<\/h4>\n

\u6267\u884c\u4f7f\u7528\u7684\u662f spark-shell\uff0c\u4f46\u6838\u5fc3\u7a0b\u5e8f\u9700\u8981\u4e8b\u5148\u5199\u5728\u6587\u4ef6\u4e2d\uff0c\u5e76\u52a0\u8f7d\u5e76\u4f7f\u7528\u5b83\u3002\u4ee5\u4e0b\u662f\u8be5\u7a0b\u5e8f\u3002<\/p>\n

import<\/span> java.io.StringReader<\/span>\r\nimport<\/span> org.apache.spark.mllib.feature.<\/span>{<\/span>Word2Vec<\/span>,<\/span> Word2VecModel<\/span>}<\/span>\r\nimport<\/span> org.apache.lucene.analysis.ja.JapaneseTokenizer<\/span>\r\nimport<\/span> org.apache.lucene.analysis.tokenattributes.CharTermAttribute<\/span>\r\nimport<\/span> org.apache.lucene.analysis.ja.tokenattributes.BaseFormAttribute<\/span>\r\nimport<\/span> org.apache.lucene.analysis.ja.tokenattributes.PartOfSpeechAttribute<\/span>\r\nimport<\/span> org.apache.spark.mllib.linalg.Vectors<\/span>\r\n\r\nimport<\/span> scala.collection.mutable.ArrayBuffer<\/span>\r\ndef<\/span> tokenize<\/span>(<\/span>sentence<\/span>:<\/span> String<\/span>)<\/span>:<\/span> Seq<\/span>[<\/span>String<\/span>]<\/span> =<\/span> {<\/span>\r\n  val<\/span> word<\/span>:<\/span> ArrayBuffer<\/span>[<\/span>String<\/span>]<\/span> =<\/span> new<\/span> ArrayBuffer<\/span>[<\/span>String<\/span>]()<\/span>\r\n  lazy<\/span> val<\/span> stream<\/span> =<\/span> new<\/span> JapaneseTokenizer<\/span>(<\/span>\r\n    new<\/span> StringReader<\/span>(<\/span>sentence<\/span>),<\/span>\r\n    null<\/span>,<\/span>\r\n    false<\/span>,<\/span>\r\n    JapaneseTokenizer<\/span>.<\/span>Mode<\/span>.<\/span>NORMAL<\/span>)<\/span>\r\n\r\n  try<\/span> {<\/span>\r\n    while<\/span>(<\/span>stream<\/span>.<\/span>incrementToken<\/span>())<\/span> {<\/span>\r\n      var<\/span> charAtt<\/span> =<\/span> stream<\/span>.<\/span>getAttribute<\/span>(<\/span>\r\n        classOf<\/span>[<\/span>CharTermAttribute<\/span>]<\/span>\r\n      ).<\/span>toString<\/span>\r\n\r\n      var<\/span> bfAtt<\/span> =<\/span> stream<\/span>.<\/span>getAttribute<\/span>(<\/span>\r\n        classOf<\/span>[<\/span>BaseFormAttribute<\/span>]<\/span>\r\n      ).<\/span>getBaseForm<\/span>\r\n\r\n      var<\/span> partOfSpeech<\/span> =<\/span> stream<\/span>.<\/span>getAttribute<\/span>(<\/span>\r\n        classOf<\/span>[<\/span>PartOfSpeechAttribute<\/span>]<\/span>\r\n      ).<\/span>getPartOfSpeech<\/span>().<\/span>split<\/span>(<\/span>\"-\"<\/span>)(<\/span>0<\/span>)<\/span>\r\n\r\n      (<\/span>partOfSpeech<\/span>,<\/span> bfAtt<\/span>)<\/span> match<\/span> {<\/span>\r\n        case<\/span> (<\/span>\"\u540d\u8a5e\"<\/span>,<\/span> _<\/span>)<\/span>  =><\/span> word<\/span> +=<\/span> charAtt<\/span>\r\n        case<\/span> (<\/span>\"\u52d5\u8a5e\"<\/span>,<\/span> null<\/span>)<\/span>  =><\/span> word<\/span> +=<\/span> charAtt<\/span>\r\n        case<\/span> (<\/span>\"\u52d5\u8a5e\"<\/span>,<\/span> baseForm<\/span>)<\/span>  =><\/span> word<\/span> +=<\/span> baseForm<\/span>\r\n        case<\/span> (<\/span>_<\/span>,<\/span> _<\/span>)<\/span>  =><\/span>\r\n      }<\/span>\r\n    }<\/span>\r\n  }<\/span> finally<\/span> {<\/span>\r\n    stream<\/span>.<\/span>close<\/span>\r\n  }<\/span>\r\n  word<\/span>.<\/span>toSeq<\/span>\r\n}<\/span>\r\n<\/code><\/pre>\n
\u4e0b\u8f7d\u6570\u636e\u6e90<\/h4>\n
\u6211\u5011\u4f7f\u7528\u4ee5\u4e0b\u9801\u9762\u7684\u5167\u5bb9\u3002\u6211\u5011\u53ea\u5c07\u5167\u5bb9\u7c98\u8cbc\u5230\u6587\u672c\u4e2d\uff0c\u4e0d\u5305\u62ecHTML\u6a19\u7c64\u3002
\n\u9019\u4e9b\u6587\u672c\u6587\u4ef6\u5c07\u4fdd\u5b58\u5728\/data\/mllib\/word2vec\u4e0b\u3002
\n\u662d\u548c
\n\u5e73\u6210
\n\u4ee4\u548c<\/p>\n
\u542f\u52a8 spark-shell<\/h4>\n
\u8fd9\u6b21\u4f7f\u7528\u7684\u662f Spark(\u7248\u672c2.1.1)\u3002
\n\u4f7f\u7528 -i \u9009\u9879\u6765\u52a0\u8f7d\u4e0a\u8ff0\u7684 word2vec.scala \u5e76\u542f\u52a8 spark-shell\u3002
\n\u8fd9\u6837\u5728 spark-shell \u4e2d\u5c31\u53ef\u4ee5\u4f7f\u7528 tokenize() \u51fd\u6570\u4e86\u3002<\/p>\n
\/usr\/hdp\/2.6.2.0-205\/spark2\/bin\/spark-shell --master<\/span> local<\/span> --deploy-mode<\/span> client --packages<\/span> org.apache.lucene:lucene-kuromoji:3.6.2 --conf<\/span> spark.serializer=<\/span>org.apache.spark.serializer.KryoSerializer -i<\/span> \/spark\/src\/mllib\/word2vec.scala\r\n<\/code><\/pre>\n
\u6267\u884c\u547d\u4ee4<\/h4>\n
\u4ee5\u4e0b\u662f\u5728spark-shell\u4e2d\u7684\u547d\u4ee4\uff1a
\n1. \u8bfb\u53d6\u6587\u672c\u6587\u4ef6
\n\u8bfb\u53d6\u9884\u5148\u51c6\u5907\u597d\u7684\u6587\u672c\u6587\u4ef6\u5e76\u8fdb\u884c\u5206\u8bcd\u3002<\/p>\n
val input =<\/span> sc.textFile(<\/span>\"\/data\/mllib\/word2vec\"<\/span>)<\/span>.map(<\/span>line =><\/span> tokenize(<\/span>line))<\/span>\r\n<\/code><\/pre>\n
\u8bbe\u7f6e\u5355\u8bcd\u51fa\u73b0\u7684\u4e0b\u9650\u6570\u548c\u751f\u6210\u5355\u8bcd\u5411\u91cf\u7684\u7ef4\u5ea6\u6570\u91cf\u3002<\/p>\n
val word2vec =<\/span> new Word2Vec()<\/span>\r\nword2vec.setMinCount(<\/span>3)<\/span>\r\nword2vec.setVectorSize(<\/span>30)<\/span>\r\n<\/code><\/pre>\n
3. \u6a21\u578b\u7684\u751f\u6210
\n\u901a\u8fc7\u4ee5\u4e0a\u6b65\u9aa4\uff0c\u6a21\u578b\u5c06\u4f1a\u5b8c\u6210\u3002<\/p>\n
val model =<\/span> word2vec.fit(<\/span>input)<\/span>\r\n<\/code><\/pre>\n
\u8bd5\u7740\u5bfb\u627e\u540c\u4e49\u8bcd<\/h4>\n
\u6309\u987a\u5e8f\u4ece\u5f97\u5206\u9ad8\u7684\u5f00\u59cb\uff0c\u68c0\u6d4b\u51fa\u4e94\u4e2a\u9879\u76ee\u3002<\/p>\n
model.findSynonyms(<\/span>\"\u5e73\u6210\"<\/span>,5)<\/span>\r\nres2: Array((<\/span>\u662d\u548c,0.8683416787288002)<\/span>, (<\/span>\u5e74,0.7191081645948658)<\/span>, (<\/span>:,0.7109386795501776)<\/span>, (<\/span>1970,0.6096518744108191)<\/span>, (<\/span>\u65e5\u672c,0.5882052253525422))<\/span>\r\n<\/code><\/pre>\n
“\u662d\u548c”\u4f5c\u4e3a\u4e0e”\u5e73\u6210”\u76f8\u4f3c\u7684\u8bcd\u6c47\u88ab\u68c0\u6d4b\u5230\u4f4d\u4e8e\u9876\u90e8\uff08\u5373\u4f7f\u662f\u5076\u7136\uff09\uff0c\u8fd9\u771f\u662f\u592a\u68d2\u4e86\u3002
\n“:”\u8fd9\u79cd\u610f\u4e49\u4e0d\u660e\u7684\u7b26\u53f7\u5e94\u8be5\u88ab\u9884\u5148\u79fb\u9664\uff0c\u4f5c\u4e3a\u6a21\u578b\u751f\u6210\u4e4b\u524d\u9700\u8981\u5904\u7406\u7684\u6587\u672c\u3002<\/p>\n
model.findSynonyms(<\/span>\"\u662d\u548c\"<\/span>,5)<\/span>\r\nres3: Array[(<\/span>String, Double)]<\/span> =<\/span> Array((<\/span>\u5e73\u6210,0.8683416675677946)<\/span>, (<\/span>\u5e74,0.7414342466252306)<\/span>, (<\/span>\u73fe\u4ee3,0.7280670946869915)<\/span>, (<\/span>\u6557\u6226,0.6568551583363003)<\/span>, (<\/span>1970,0.6326117643599328))<\/span>\r\n<\/code><\/pre>\n
\u5982\u679c\u901a\u8fc7\u201c\u662d\u548c\u201d\u8fdb\u884c\u641c\u7d22\uff0c\u4f1a\u53d1\u73b0\u201c\u5e73\u6210\u201d\u4f5c\u4e3a\u9876\u7ea7\u540c\u4e49\u8bcd\u51fa\u73b0\u3002
\n\u53ef\u80fd\u5e94\u8be5\u5728\u6587\u672c\u4e2d\u5254\u9664\u660e\u663e\u8868\u793a\u65f6\u4ee3\u7684\u5173\u952e\u8bcd\uff0c\u4f8b\u5982\u201c1970\u201d\u7b49\u3002<\/p>\n
model.findSynonyms(<\/span>\"\u4ee4\u548c\"<\/span>,5)<\/span>\r\njava.lang.IllegalStateException: \u4ee4\u548c not in <\/span>vocabulary\r\n<\/code><\/pre>\n
\u751f\u6210\u7684\u6a21\u578b\u4e2d\u5e94\u8be5\u9891\u7e41\u51fa\u73b0\u4e86\u201c\u4ee4\u548c\u201d\u8fd9\u4e2a\u8bcd\u8bed\uff0c\u4f46\u662f\u5728\u6240\u4f7f\u7528\u7684lucene-kuromoji\u7248\u672c\u4e2d\u6ca1\u6709\u5c06\u5b83\u6ce8\u518c\u4e3a\u4e00\u4e2a\u5355\u8bcd\u3002\u8fd9\u53ef\u80fd\u662f\u56e0\u4e3a\u6240\u4f7f\u7528\u7684\u7248\u672c\u8f83\u65e7\uff0c\u5bfc\u81f4\u65e0\u6cd5\u5bf9\u201c\u4ee4\u548c\u201d\u8fdb\u884c\u8bcd\u6cd5\u5206\u6790\u3002<\/p>\n
model.findSynonyms(<\/span>\"\u5143\u53f7\"<\/span>,5)<\/span>\r\nres9: Array[(<\/span>String, Double)]<\/span> =<\/span> Array((<\/span>\u4ee4,0.7863372339299479)<\/span>, (<\/span>''',0.7558561207740144), (\u548c,0.7263245520368361), (\u6dd1,0.7139302506327456), (\u66f2,0.7057422726424456))\r\n<\/span><\/code><\/pre>\n
\u9664\u4e86\u201c\u4ee4\u201d\u6392\u540d\u7b2c\u4e00\u548c\u5355\u5f15\u53f7\u6392\u540d\u7b2c\u4e8c\u4e4b\u5916\uff0c\u6211\u4eec\u53d1\u73b0\u201c\u548c\u201d\u6392\u540d\u7b2c\u4e8c\u4f5c\u4e3a\u201c\u5143\u53f7\u201d\u7684\u540c\u4e49\u8bcd\u88ab\u68c0\u6d4b\u51fa\u6765\u3002\u867d\u7136\u6211\u4eec\u4e0d\u77e5\u9053\u8fd9\u662f\u5426\u6e90\u81ea\u4e8e\u539f\u672c\u7684\u8bcd\u6c47\u201c\u4ee4\u548c\u201d\uff0c\u4f46\u7ed3\u679c\u5341\u5206\u6709\u8da3\u3002<\/p>\n
\u53ea\u8f93\u5165\u4e863\u9875\u7ef4\u57fa\u767e\u79d1\u4fe1\u606f\uff0c\u4f46\u6211\u53d1\u73b0\u9690\u7ea6\u627e\u5230\u4e86\u76f8\u5173\u7684\u8bcd\u8bed\u3002
\n\u7136\u800c\uff0c\u589e\u52a0\u4fe1\u606f\u91cf\u5e76\u4e0d\u610f\u5473\u7740\u63d0\u9ad8\u51c6\u786e\u6027\uff0c\u56e0\u4e3a\u989d\u5916\u7684\u7b26\u53f7\u548c\u6570\u5b57\u7b49\u5197\u4f59\u4fe1\u606f\u5b58\u5728\uff0c\u51c6\u786e\u6027\u4f1a\u4e0b\u964d\u3002
\n\u5982\u4f55\u786e\u4fdd\u8f93\u5165\u4fe1\u606f\u7684\u4e00\u81f4\u6027\u548c\u9ad8\u8d28\u91cf\u53ef\u80fd\u6210\u4e3a\u826f\u597d\u6a21\u578b\u751f\u6210\u7684\u4e00\u4e2a\u5173\u952e\u8981\u7d20\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"
Word2Vec\uff1a\u8bcd\u5411\u91cf Word2Vec\u662f\u7531\u8c37\u6b4c\u7814\u7a76\u6240\u57282013\u5e74\u63d0\u51fa\u7684\u4e00\u4e2a\u7b97\u6cd5\uff0c\u8be5\u7b97\u6cd5\u57fa\u4e8e\u5047\u8bbe&#8221 […]<\/p>\n","protected":false},"author":6,"featured_media":0,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1],"tags":[],"class_list":["post-36757","post","type-post","status-publish","format-standard","hentry","category-uncategorized"],"yoast_head":"\n\u4f7f\u7528 Apache Spark \u8fdb\u884c Word2Vec - Blog - Silicon Cloud<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.silicloud.com\/zh\/blog\/\u4f7f\u7528-apache-spark-\u8fdb\u884c-word2vec\/\" \/>\n<meta property=\"og:locale\" content=\"zh_CN\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"\u4f7f\u7528 Apache Spark \u8fdb\u884c Word2Vec\" \/>\n<meta property=\"og:description\" content=\"Word2Vec\uff1a\u8bcd\u5411\u91cf Word2Vec\u662f\u7531\u8c37\u6b4c\u7814\u7a76\u6240\u57282013\u5e74\u63d0\u51fa\u7684\u4e00\u4e2a\u7b97\u6cd5\uff0c\u8be5\u7b97\u6cd5\u57fa\u4e8e\u5047\u8bbe&#8221 […]\" \/>\n<meta property=\"og:url\" content=\"https:\/\/www.silicloud.com\/zh\/blog\/\u4f7f\u7528-apache-spark-\u8fdb\u884c-word2vec\/\" \/>\n<meta property=\"og:site_name\" content=\"Blog - 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