{"id":99934,"date":"2026-09-03T16:17:09","date_gmt":"2026-09-03T08:17:09","guid":{"rendered":"https:\/\/www.wsisp.com\/helps\/99934.html"},"modified":"2026-09-03T16:17:09","modified_gmt":"2026-09-03T08:17:09","slug":"%e8%ae%a1%e7%ae%97%e6%9c%ba%e6%af%95%e8%ae%be%e9%80%89%e9%a2%98%ef%bd%9c%e5%9f%ba%e4%ba%8e%e5%a4%a7%e6%95%b0%e6%8d%ae%e7%9a%84%e5%85%a8%e7%90%83%e6%9e%81%e7%ab%af%e7%83%ad%e5%8a%9b%e4%ba%8b%e4%bb%b6","status":"publish","type":"post","link":"https:\/\/www.wsisp.com\/helps\/99934.html","title":{"rendered":"\u8ba1\u7b97\u673a\u6bd5\u8bbe\u9009\u9898\uff5c\u57fa\u4e8e\u5927\u6570\u636e\u7684\u5168\u7403\u6781\u7aef\u70ed\u529b\u4e8b\u4ef6\u6316\u6398\u4e0e\u52a8\u6001\u53ef\u89c6\u5316\u7814\u7a76\uff1aHadoop+Spark \u5206\u6790+Django+Vue 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src=\"https:\/\/www.wsisp.com\/helps\/wp-content\/uploads\/2026\/09\/20260903081706-6a992d0298ed0.png\" alt=\"\u5728\u8fd9\u91cc\u63d2\u5165\u56fe\u7247\u63cf\u8ff0\" \/> <img decoding=\"async\" src=\"https:\/\/www.wsisp.com\/helps\/wp-content\/uploads\/2026\/09\/20260903081707-6a992d031939c.png\" alt=\"\u5728\u8fd9\u91cc\u63d2\u5165\u56fe\u7247\u63cf\u8ff0\" \/><\/p>\n<h2>\u4e94\u3001\u4ee3\u7801\u5c55\u793a<\/h2>\n<p>from pyspark.sql <span class=\"token function\">import<\/span> SparkSession, Window<br \/>\nfrom pyspark.sql.functions <span class=\"token function\">import<\/span> <span class=\"token punctuation\">(<\/span><br \/>\n    avg as spark_avg, col, count as spark_count, desc,<br \/>\n    lit, max as spark_max, row_number, round as spark_round,<br \/>\n    stddev as spark_stddev, <span class=\"token function\">sum<\/span> as spark_sum, when,<br \/>\n<span class=\"token punctuation\">)<\/span><br \/>\nfrom pyspark.sql.types <span class=\"token function\">import<\/span> DoubleType, IntegerType<br \/>\nfrom sklearn.cluster <span class=\"token function\">import<\/span> KMeans<br \/>\nfrom sklearn.ensemble <span class=\"token function\">import<\/span> IsolationForest<br \/>\nfrom sklearn.preprocessing <span class=\"token function\">import<\/span> StandardScaler<\/p>\n<p>HDFS_PREPROCESSED <span class=\"token operator\">&#061;<\/span> <span class=\"token punctuation\">(<\/span><br \/>\n    <span class=\"token string\">&#039;hdfs:\/\/127.0.0.1:9000\/GlobalHeatEventSystem\/output\/global_gridded_thermal_preprocessed_data.csv&#039;<\/span><br \/>\n<span class=\"token punctuation\">)<\/span><\/p>\n<p>def create_spark<span class=\"token punctuation\">(<\/span><span class=\"token punctuation\">)<\/span>:<br \/>\n    <span class=\"token builtin class-name\">return<\/span> SparkSession.builder.appName<span class=\"token punctuation\">(<\/span><span class=\"token string\">&#039;GlobalHeatEventSystem_analysis&#039;<\/span><span class=\"token punctuation\">)<\/span>.getOrCreate<span class=\"token punctuation\">(<\/span><span class=\"token punctuation\">)<\/span><\/p>\n<p>def load_preprocessed<span class=\"token punctuation\">(<\/span>spark<span class=\"token punctuation\">)<\/span>:<br \/>\n    <span class=\"token function\">df<\/span> <span class=\"token operator\">&#061;<\/span> spark.read.csv<span class=\"token punctuation\">(<\/span>HDFS_PREPROCESSED, <span class=\"token assign-left variable\">header<\/span><span class=\"token operator\">&#061;<\/span>True, <span class=\"token assign-left variable\">inferSchema<\/span><span class=\"token operator\">&#061;<\/span>False<span class=\"token punctuation\">)<\/span><br \/>\n    <span class=\"token keyword\">for<\/span> <span class=\"token for-or-select variable\">column<\/span> <span class=\"token keyword\">in<\/span> NUMERIC_COLS &#043; <span class=\"token punctuation\">[<\/span><span class=\"token string\">&#039;year&#039;<\/span>, <span class=\"token string\">&#039;month&#039;<\/span>, <span class=\"token string\">&#039;decade&#039;<\/span><span class=\"token punctuation\">]<\/span>:<br \/>\n        <span class=\"token keyword\">if<\/span> <span class=\"token function\">column<\/span> <span class=\"token keyword\">in<\/span> df.columns:<br \/>\n            <span class=\"token function\">df<\/span> <span class=\"token operator\">&#061;<\/span> df.withColumn<span class=\"token punctuation\">(<\/span>column, col<span class=\"token punctuation\">(<\/span>column<span class=\"token punctuation\">)<\/span>.cast<span class=\"token punctuation\">(<\/span>DoubleType<span class=\"token punctuation\">(<\/span><span class=\"token punctuation\">))<\/span><span class=\"token punctuation\">)<\/span><br \/>\n    <span class=\"token builtin class-name\">return<\/span> df.withColumn<span class=\"token punctuation\">(<\/span><span class=\"token string\">&#039;year&#039;<\/span>, col<span class=\"token punctuation\">(<\/span><span class=\"token string\">&#039;year&#039;<\/span><span class=\"token punctuation\">)<\/span>.cast<span class=\"token punctuation\">(<\/span>IntegerType<span class=\"token punctuation\">(<\/span><span class=\"token punctuation\">))<\/span><span class=\"token punctuation\">)<\/span> <span class=\"token punctuation\">\\\\<\/span><br \/>\n             .withColumn<span class=\"token punctuation\">(<\/span><span class=\"token string\">&#039;month&#039;<\/span>, col<span class=\"token punctuation\">(<\/span><span class=\"token string\">&#039;month&#039;<\/span><span class=\"token punctuation\">)<\/span>.cast<span class=\"token punctuation\">(<\/span>IntegerType<span class=\"token punctuation\">(<\/span><span class=\"token punctuation\">))<\/span><span class=\"token punctuation\">)<\/span> <span class=\"token punctuation\">\\\\<\/span><br \/>\n             .withColumn<span class=\"token punctuation\">(<\/span><span class=\"token string\">&#039;decade&#039;<\/span>, col<span class=\"token punctuation\">(<\/span><span class=\"token string\">&#039;decade&#039;<\/span><span class=\"token punctuation\">)<\/span>.cast<span class=\"token punctuation\">(<\/span>IntegerType<span class=\"token punctuation\">(<\/span><span class=\"token punctuation\">))<\/span><span class=\"token punctuation\">)<\/span><\/p>\n<p>def annual_trend_analysis<span class=\"token punctuation\">(<\/span>spark, df, logger_obj, output_dir<span class=\"token punctuation\">)<\/span>:<br \/>\n    <span class=\"token string\">&#034;&#034;<\/span>&#034;A01 \u5e74\u5ea6\u8d8b\u52bf&#xff1a;\u6309 year \u805a\u5408 Mean\/Max\/Min\/Std<span class=\"token string\">&#034;&#034;<\/span>&#034;<br \/>\n    result <span class=\"token operator\">&#061;<\/span> df.groupBy<span class=\"token punctuation\">(<\/span><span class=\"token string\">&#039;year&#039;<\/span><span class=\"token punctuation\">)<\/span>.agg<span class=\"token punctuation\">(<\/span><br \/>\n        spark_round<span class=\"token punctuation\">(<\/span>spark_avg<span class=\"token punctuation\">(<\/span><span class=\"token string\">&#039;Mean&#039;<\/span><span class=\"token punctuation\">)<\/span>, <span class=\"token number\">2<\/span><span class=\"token punctuation\">)<\/span>.alias<span class=\"token punctuation\">(<\/span><span class=\"token string\">&#039;avg_mean&#039;<\/span><span class=\"token punctuation\">)<\/span>,<br \/>\n        spark_round<span class=\"token punctuation\">(<\/span>spark_avg<span class=\"token punctuation\">(<\/span><span class=\"token string\">&#039;Max&#039;<\/span><span class=\"token punctuation\">)<\/span>, <span class=\"token number\">2<\/span><span class=\"token punctuation\">)<\/span>.alias<span class=\"token punctuation\">(<\/span><span class=\"token string\">&#039;avg_max&#039;<\/span><span class=\"token punctuation\">)<\/span>,<br \/>\n        spark_round<span class=\"token punctuation\">(<\/span>spark_avg<span class=\"token punctuation\">(<\/span><span class=\"token string\">&#039;Min&#039;<\/span><span class=\"token punctuation\">)<\/span>, <span class=\"token number\">2<\/span><span class=\"token punctuation\">)<\/span>.alias<span class=\"token punctuation\">(<\/span><span class=\"token string\">&#039;avg_min&#039;<\/span><span class=\"token punctuation\">)<\/span>,<br \/>\n        spark_round<span class=\"token punctuation\">(<\/span>spark_avg<span class=\"token punctuation\">(<\/span><span class=\"token string\">&#039;Std&#039;<\/span><span class=\"token punctuation\">)<\/span>, <span class=\"token number\">2<\/span><span class=\"token punctuation\">)<\/span>.alias<span class=\"token punctuation\">(<\/span><span class=\"token string\">&#039;avg_std&#039;<\/span><span class=\"token punctuation\">)<\/span>,<br \/>\n        spark_count<span class=\"token punctuation\">(<\/span>lit<span class=\"token punctuation\">(<\/span><span class=\"token number\">1<\/span><span class=\"token punctuation\">))<\/span>.alias<span class=\"token punctuation\">(<\/span><span class=\"token string\">&#039;record_count&#039;<\/span><span class=\"token punctuation\">)<\/span>,<br \/>\n    <span class=\"token punctuation\">)<\/span>.orderBy<span class=\"token punctuation\">(<\/span><span class=\"token string\">&#039;year&#039;<\/span><span class=\"token punctuation\">)<\/span><br \/>\n    write_csv<span class=\"token punctuation\">(<\/span>result, os.path.join<span class=\"token punctuation\">(<\/span>output_dir, <span class=\"token string\">&#039;annual_trend.csv&#039;<\/span><span class=\"token punctuation\">))<\/span><\/p>\n<p>def warming_rate_analysis<span class=\"token punctuation\">(<\/span>spark, df, logger_obj, output_dir<span class=\"token punctuation\">)<\/span>:<br \/>\n    <span class=\"token string\">&#034;&#034;<\/span>&#034;A05 \u5347\u6e29\u901f\u7387&#xff1a;\u5e74\u5ea6\u5747\u503c \u2192 \u7ebf\u6027\u56de\u5f52\u659c\u7387<span class=\"token string\">&#034;&#034;<\/span>&#034;<br \/>\n    pdf <span class=\"token operator\">&#061;<\/span> df.groupBy<span class=\"token punctuation\">(<\/span><span class=\"token string\">&#039;year&#039;<\/span><span class=\"token punctuation\">)<\/span>.agg<span class=\"token punctuation\">(<\/span><br \/>\n        spark_round<span class=\"token punctuation\">(<\/span>spark_avg<span class=\"token punctuation\">(<\/span><span class=\"token string\">&#039;Mean&#039;<\/span><span class=\"token punctuation\">)<\/span>, <span class=\"token number\">2<\/span><span class=\"token punctuation\">)<\/span>.alias<span class=\"token punctuation\">(<\/span><span class=\"token string\">&#039;avg_mean&#039;<\/span><span class=\"token punctuation\">)<\/span><br \/>\n    <span class=\"token punctuation\">)<\/span>.orderBy<span class=\"token punctuation\">(<\/span><span class=\"token string\">&#039;year&#039;<\/span><span class=\"token punctuation\">)<\/span>.toPandas<span class=\"token punctuation\">(<\/span><span class=\"token punctuation\">)<\/span><br \/>\n    years <span class=\"token operator\">&#061;<\/span> pdf<span class=\"token punctuation\">[<\/span><span class=\"token string\">&#039;year&#039;<\/span><span class=\"token punctuation\">]<\/span>.astype<span class=\"token punctuation\">(<\/span>float<span class=\"token punctuation\">)<\/span>.values<br \/>\n    means <span class=\"token operator\">&#061;<\/span> pdf<span class=\"token punctuation\">[<\/span><span class=\"token string\">&#039;avg_mean&#039;<\/span><span class=\"token punctuation\">]<\/span>.astype<span class=\"token punctuation\">(<\/span>float<span class=\"token punctuation\">)<\/span>.values<br \/>\n    slope, intercept <span class=\"token operator\">&#061;<\/span> np.polyfit<span class=\"token punctuation\">(<\/span>years, means, <span class=\"token number\">1<\/span><span class=\"token punctuation\">)<\/span><br \/>\n    trend <span class=\"token operator\">&#061;<\/span> slope * years &#043; intercept<br \/>\n    pd.DataFrame<span class=\"token punctuation\">(<\/span><span class=\"token punctuation\">{<\/span><br \/>\n        <span class=\"token string\">&#039;year&#039;<\/span><span class=\"token builtin class-name\">:<\/span> pdf<span class=\"token punctuation\">[<\/span><span class=\"token string\">&#039;year&#039;<\/span><span class=\"token punctuation\">]<\/span>,<br \/>\n        <span class=\"token string\">&#039;avg_mean&#039;<\/span><span class=\"token builtin class-name\">:<\/span> pdf<span class=\"token punctuation\">[<\/span><span class=\"token string\">&#039;avg_mean&#039;<\/span><span class=\"token punctuation\">]<\/span>,<br \/>\n        <span class=\"token string\">&#039;trend_line&#039;<\/span><span class=\"token builtin class-name\">:<\/span> np.round<span class=\"token punctuation\">(<\/span>trend, <span class=\"token number\">2<\/span><span class=\"token punctuation\">)<\/span>,<br \/>\n    <span class=\"token punctuation\">}<\/span><span class=\"token punctuation\">)<\/span>.to_csv<span class=\"token punctuation\">(<\/span>os.path.join<span class=\"token punctuation\">(<\/span>output_dir, <span class=\"token string\">&#039;warming_rate.csv&#039;<\/span><span class=\"token punctuation\">)<\/span>, <span class=\"token assign-left variable\">encoding<\/span><span class=\"token operator\">&#061;<\/span><span class=\"token string\">&#039;utf-8&#039;<\/span>, <span class=\"token assign-left variable\">index<\/span><span class=\"token operator\">&#061;<\/span>False<span class=\"token punctuation\">)<\/span><\/p>\n<p>def high_heat_day_count_analysis<span class=\"token punctuation\">(<\/span>spark, df, logger_obj, output_dir<span class=\"token punctuation\">)<\/span>:<br \/>\n    <span class=\"token string\">&#034;&#034;<\/span>&#034;A07 \u9ad8\u6e29\u65e5\u6570&#xff1a;Mean <span class=\"token operator\">&gt;<\/span> p95 \u6807\u8bb0\u4e3a\u9ad8\u6e29\u65e5<span class=\"token string\">&#034;&#034;<\/span>&#034;<br \/>\n    flagged <span class=\"token operator\">&#061;<\/span> df.filter<span class=\"token punctuation\">(<\/span>col<span class=\"token punctuation\">(<\/span><span class=\"token string\">&#039;Mean&#039;<\/span><span class=\"token punctuation\">)<\/span>.isNotNull<span class=\"token punctuation\">(<\/span><span class=\"token punctuation\">)<\/span> <span class=\"token operator\">&amp;<\/span> col<span class=\"token punctuation\">(<\/span><span class=\"token string\">&#039;p95&#039;<\/span><span class=\"token punctuation\">)<\/span>.isNotNull<span class=\"token punctuation\">(<\/span><span class=\"token punctuation\">))<\/span>.withColumn<span class=\"token punctuation\">(<\/span><br \/>\n        <span class=\"token string\">&#039;is_high_heat&#039;<\/span>, when<span class=\"token punctuation\">(<\/span>col<span class=\"token punctuation\">(<\/span><span class=\"token string\">&#039;Mean&#039;<\/span><span class=\"token punctuation\">)<\/span> <span class=\"token operator\">&gt;<\/span> col<span class=\"token punctuation\">(<\/span><span class=\"token string\">&#039;p95&#039;<\/span><span class=\"token punctuation\">)<\/span>, <span class=\"token number\">1<\/span><span class=\"token punctuation\">)<\/span>.otherwise<span class=\"token punctuation\">(<\/span><span class=\"token number\">0<\/span><span class=\"token punctuation\">)<\/span><br \/>\n    <span class=\"token punctuation\">)<\/span><br \/>\n    result <span class=\"token operator\">&#061;<\/span> flagged.groupBy<span class=\"token punctuation\">(<\/span><span class=\"token string\">&#039;year&#039;<\/span><span class=\"token punctuation\">)<\/span>.agg<span class=\"token punctuation\">(<\/span><br \/>\n        spark_sum<span class=\"token punctuation\">(<\/span><span class=\"token string\">&#039;is_high_heat&#039;<\/span><span class=\"token punctuation\">)<\/span>.alias<span class=\"token punctuation\">(<\/span><span class=\"token string\">&#039;high_heat_days&#039;<\/span><span class=\"token punctuation\">)<\/span>,<br \/>\n        spark_count<span class=\"token punctuation\">(<\/span>lit<span class=\"token punctuation\">(<\/span><span class=\"token number\">1<\/span><span class=\"token punctuation\">))<\/span>.alias<span class=\"token punctuation\">(<\/span><span class=\"token string\">&#039;total_days&#039;<\/span><span class=\"token punctuation\">)<\/span>,<br \/>\n    <span class=\"token punctuation\">)<\/span>.withColumn<span class=\"token punctuation\">(<\/span><br \/>\n        <span class=\"token string\">&#039;high_heat_ratio&#039;<\/span>,<br \/>\n        spark_round<span class=\"token punctuation\">(<\/span>col<span class=\"token punctuation\">(<\/span><span class=\"token string\">&#039;high_heat_days&#039;<\/span><span class=\"token punctuation\">)<\/span> \/ col<span class=\"token punctuation\">(<\/span><span class=\"token string\">&#039;total_days&#039;<\/span><span class=\"token punctuation\">)<\/span> * <span class=\"token number\">100<\/span>, <span class=\"token number\">2<\/span><span class=\"token punctuation\">)<\/span><br \/>\n    <span class=\"token punctuation\">)<\/span>.orderBy<span class=\"token punctuation\">(<\/span><span class=\"token string\">&#039;year&#039;<\/span><span class=\"token punctuation\">)<\/span><br \/>\n    write_csv<span class=\"token punctuation\">(<\/span>result, os.path.join<span class=\"token punctuation\">(<\/span>output_dir, <span class=\"token string\">&#039;high_heat_day_count.csv&#039;<\/span><span class=\"token punctuation\">))<\/span><\/p>\n<p>def anomaly_detection_analysis<span class=\"token punctuation\">(<\/span>spark, df, logger_obj, output_dir<span class=\"token punctuation\">)<\/span>:<br \/>\n    <span class=\"token string\">&#034;&#034;<\/span>&#034;A11 \u5f02\u5e38\u8bc6\u522b&#xff1a;Spark \u6708\u805a\u5408 \u2192 sklearn IsolationForest<span class=\"token string\">&#034;&#034;<\/span>&#034;<br \/>\n    monthly <span class=\"token operator\">&#061;<\/span> df.filter<span class=\"token punctuation\">(<\/span><br \/>\n        col<span class=\"token punctuation\">(<\/span><span class=\"token string\">&#039;year&#039;<\/span><span class=\"token punctuation\">)<\/span>.isNotNull<span class=\"token punctuation\">(<\/span><span class=\"token punctuation\">)<\/span> <span class=\"token operator\">&amp;<\/span> col<span class=\"token punctuation\">(<\/span><span class=\"token string\">&#039;month&#039;<\/span><span class=\"token punctuation\">)<\/span>.isNotNull<span class=\"token punctuation\">(<\/span><span class=\"token punctuation\">)<\/span><br \/>\n        <span class=\"token operator\">&amp;<\/span> col<span class=\"token punctuation\">(<\/span><span class=\"token string\">&#039;Mean&#039;<\/span><span class=\"token punctuation\">)<\/span>.isNotNull<span class=\"token punctuation\">(<\/span><span class=\"token punctuation\">)<\/span> <span class=\"token operator\">&amp;<\/span> col<span class=\"token punctuation\">(<\/span><span class=\"token string\">&#039;Max&#039;<\/span><span class=\"token punctuation\">)<\/span>.isNotNull<span class=\"token punctuation\">(<\/span><span class=\"token punctuation\">)<\/span><br \/>\n        <span class=\"token operator\">&amp;<\/span> col<span class=\"token punctuation\">(<\/span><span class=\"token string\">&#039;Std&#039;<\/span><span class=\"token punctuation\">)<\/span>.isNotNull<span class=\"token punctuation\">(<\/span><span class=\"token punctuation\">)<\/span> <span class=\"token operator\">&amp;<\/span> col<span class=\"token punctuation\">(<\/span><span class=\"token string\">&#039;p99&#039;<\/span><span class=\"token punctuation\">)<\/span>.isNotNull<span class=\"token punctuation\">(<\/span><span class=\"token punctuation\">)<\/span><br \/>\n    <span class=\"token punctuation\">)<\/span>.groupBy<span class=\"token punctuation\">(<\/span><span class=\"token string\">&#039;year&#039;<\/span>, <span class=\"token string\">&#039;month&#039;<\/span><span class=\"token punctuation\">)<\/span>.agg<span class=\"token punctuation\">(<\/span><br \/>\n        spark_avg<span class=\"token punctuation\">(<\/span><span class=\"token string\">&#039;Mean&#039;<\/span><span class=\"token punctuation\">)<\/span>.alias<span class=\"token punctuation\">(<\/span><span class=\"token string\">&#039;avg_mean&#039;<\/span><span class=\"token punctuation\">)<\/span>,<br \/>\n        spark_avg<span class=\"token punctuation\">(<\/span><span class=\"token string\">&#039;Max&#039;<\/span><span class=\"token punctuation\">)<\/span>.alias<span class=\"token punctuation\">(<\/span><span class=\"token string\">&#039;avg_max&#039;<\/span><span class=\"token punctuation\">)<\/span>,<br \/>\n        spark_avg<span class=\"token punctuation\">(<\/span><span class=\"token string\">&#039;Std&#039;<\/span><span class=\"token punctuation\">)<\/span>.alias<span class=\"token punctuation\">(<\/span><span class=\"token string\">&#039;avg_std&#039;<\/span><span class=\"token punctuation\">)<\/span>,<br \/>\n        spark_avg<span class=\"token punctuation\">(<\/span><span class=\"token string\">&#039;p99&#039;<\/span><span class=\"token punctuation\">)<\/span>.alias<span class=\"token punctuation\">(<\/span><span class=\"token string\">&#039;avg_p99&#039;<\/span><span class=\"token punctuation\">)<\/span>,<br \/>\n    <span class=\"token punctuation\">)<\/span><br \/>\n    feature_pdf <span class=\"token operator\">&#061;<\/span> monthly.toPandas<span class=\"token punctuation\">(<\/span><span class=\"token punctuation\">)<\/span><br \/>\n    feature_cols <span class=\"token operator\">&#061;<\/span> <span class=\"token punctuation\">[<\/span><span class=\"token string\">&#039;avg_mean&#039;<\/span>, <span class=\"token string\">&#039;avg_max&#039;<\/span>, <span class=\"token string\">&#039;avg_std&#039;<\/span>, <span class=\"token string\">&#039;avg_p99&#039;<\/span><span class=\"token punctuation\">]<\/span><br \/>\n    scaled <span class=\"token operator\">&#061;<\/span> StandardScaler<span class=\"token punctuation\">(<\/span><span class=\"token punctuation\">)<\/span>.fit_transform<span class=\"token punctuation\">(<\/span>feature_pdf<span class=\"token punctuation\">[<\/span>feature_cols<span class=\"token punctuation\">]<\/span>.astype<span class=\"token punctuation\">(<\/span>float<span class=\"token punctuation\">)<\/span>.values<span class=\"token punctuation\">)<\/span><\/p>\n<p>    model <span class=\"token operator\">&#061;<\/span> IsolationForest<span class=\"token punctuation\">(<\/span>contamination<span class=\"token operator\">&#061;<\/span><span class=\"token number\">0.05<\/span>, <span class=\"token assign-left variable\">random_state<\/span><span class=\"token operator\">&#061;<\/span><span class=\"token number\">42<\/span><span class=\"token punctuation\">)<\/span><br \/>\n    labels <span class=\"token operator\">&#061;<\/span> model.fit_predict<span class=\"token punctuation\">(<\/span>scaled<span class=\"token punctuation\">)<\/span><br \/>\n    scores <span class=\"token operator\">&#061;<\/span> model.decision_function<span class=\"token punctuation\">(<\/span>scaled<span class=\"token punctuation\">)<\/span><\/p>\n<p>    pd.DataFrame<span class=\"token punctuation\">(<\/span><span class=\"token punctuation\">{<\/span><br \/>\n        <span class=\"token string\">&#039;year&#039;<\/span><span class=\"token builtin class-name\">:<\/span> feature_pdf<span class=\"token punctuation\">[<\/span><span class=\"token string\">&#039;year&#039;<\/span><span class=\"token punctuation\">]<\/span>.astype<span class=\"token punctuation\">(<\/span>int<span class=\"token punctuation\">)<\/span>,<br \/>\n        <span class=\"token string\">&#039;month&#039;<\/span><span class=\"token builtin class-name\">:<\/span> feature_pdf<span class=\"token punctuation\">[<\/span><span class=\"token string\">&#039;month&#039;<\/span><span class=\"token punctuation\">]<\/span>.astype<span class=\"token punctuation\">(<\/span>int<span class=\"token punctuation\">)<\/span>,<br \/>\n        <span class=\"token string\">&#039;anomaly_count&#039;<\/span><span class=\"token builtin class-name\">:<\/span> <span class=\"token punctuation\">(<\/span>labels <span class=\"token operator\">&#061;&#061;<\/span> -1<span class=\"token punctuation\">)<\/span>.astype<span class=\"token punctuation\">(<\/span>int<span class=\"token punctuation\">)<\/span>,<br \/>\n        <span class=\"token string\">&#039;avg_anomaly_score&#039;<\/span><span class=\"token builtin class-name\">:<\/span> np.round<span class=\"token punctuation\">(<\/span>scores.astype<span class=\"token punctuation\">(<\/span>float<span class=\"token punctuation\">)<\/span>, <span class=\"token number\">2<\/span><span class=\"token punctuation\">)<\/span>,<br \/>\n    <span class=\"token punctuation\">}<\/span><span class=\"token punctuation\">)<\/span>.to_csv<span class=\"token punctuation\">(<\/span>os.path.join<span class=\"token punctuation\">(<\/span>output_dir, <span class=\"token string\">&#039;anomaly_detection.csv&#039;<\/span><span class=\"token punctuation\">)<\/span>, <span class=\"token assign-left variable\">encoding<\/span><span class=\"token operator\">&#061;<\/span><span class=\"token string\">&#039;utf-8&#039;<\/span>, <span class=\"token assign-left variable\">index<\/span><span class=\"token operator\">&#061;<\/span>False<span class=\"token punctuation\">)<\/span><\/p>\n<p>def consecutive_heat_analysis<span class=\"token punctuation\">(<\/span>spark, df, logger_obj, output_dir<span class=\"token punctuation\">)<\/span>:<br \/>\n    <span class=\"token string\">&#034;&#034;<\/span>&#034;A12 \u8fde\u7eed\u9ad8\u6e29&#xff1a;\u6309\u5e74\u7edf\u8ba1\u6700\u957f\u8fde\u7eed\u8d85\u8fc7 p95 \u7684\u5929\u6570<span class=\"token string\">&#034;&#034;<\/span>&#034;<br \/>\n    pdf <span class=\"token operator\">&#061;<\/span> df.filter<span class=\"token punctuation\">(<\/span><br \/>\n        col<span class=\"token punctuation\">(<\/span><span class=\"token string\">&#039;Date&#039;<\/span><span class=\"token punctuation\">)<\/span>.isNotNull<span class=\"token punctuation\">(<\/span><span class=\"token punctuation\">)<\/span> <span class=\"token operator\">&amp;<\/span> col<span class=\"token punctuation\">(<\/span><span class=\"token string\">&#039;Mean&#039;<\/span><span class=\"token punctuation\">)<\/span>.isNotNull<span class=\"token punctuation\">(<\/span><span class=\"token punctuation\">)<\/span> <span class=\"token operator\">&amp;<\/span> col<span class=\"token punctuation\">(<\/span><span class=\"token string\">&#039;p95&#039;<\/span><span class=\"token punctuation\">)<\/span>.isNotNull<span class=\"token punctuation\">(<\/span><span class=\"token punctuation\">)<\/span><br \/>\n    <span class=\"token punctuation\">)<\/span>.select<span class=\"token punctuation\">(<\/span><span class=\"token string\">&#039;Date&#039;<\/span>, <span class=\"token string\">&#039;year&#039;<\/span>, <span class=\"token string\">&#039;Mean&#039;<\/span>, <span class=\"token string\">&#039;p95&#039;<\/span><span class=\"token punctuation\">)<\/span>.orderBy<span class=\"token punctuation\">(<\/span><span class=\"token string\">&#039;Date&#039;<\/span><span class=\"token punctuation\">)<\/span>.toPandas<span class=\"token punctuation\">(<\/span><span class=\"token punctuation\">)<\/span><br \/>\n    pdf<span class=\"token punctuation\">[<\/span><span class=\"token string\">&#039;is_high&#039;<\/span><span class=\"token punctuation\">]<\/span> <span class=\"token operator\">&#061;<\/span> pdf<span class=\"token punctuation\">[<\/span><span class=\"token string\">&#039;Mean&#039;<\/span><span class=\"token punctuation\">]<\/span> <span class=\"token operator\">&gt;<\/span> pdf<span class=\"token punctuation\">[<\/span><span class=\"token string\">&#039;p95&#039;<\/span><span class=\"token punctuation\">]<\/span><br \/>\n    rows <span class=\"token operator\">&#061;<\/span> <span class=\"token punctuation\">[<\/span><span class=\"token punctuation\">]<\/span><br \/>\n    <span class=\"token keyword\">for<\/span> year, group <span class=\"token keyword\">in<\/span> pdf.groupby<span class=\"token punctuation\">(<\/span><span class=\"token string\">&#039;year&#039;<\/span><span class=\"token punctuation\">)<\/span>:<br \/>\n        streaks, current <span class=\"token operator\">&#061;<\/span> <span class=\"token punctuation\">[<\/span><span class=\"token punctuation\">]<\/span>, <span class=\"token number\">0<\/span><br \/>\n        <span class=\"token keyword\">for<\/span> <span class=\"token for-or-select variable\">is_high<\/span> <span class=\"token keyword\">in<\/span> group.sort_values<span class=\"token punctuation\">(<\/span><span class=\"token string\">&#039;Date&#039;<\/span><span class=\"token punctuation\">)<\/span><span class=\"token punctuation\">[<\/span><span class=\"token string\">&#039;is_high&#039;<\/span><span class=\"token punctuation\">]<\/span>:<br \/>\n            <span class=\"token keyword\">if<\/span> is_high:<br \/>\n                current <span class=\"token operator\">&#043;&#061;<\/span> <span class=\"token number\">1<\/span><br \/>\n            else:<br \/>\n                <span class=\"token keyword\">if<\/span> current <span class=\"token operator\">&gt;<\/span> <span class=\"token number\">0<\/span>: streaks.append<span class=\"token punctuation\">(<\/span>current<span class=\"token punctuation\">)<\/span><br \/>\n                current <span class=\"token operator\">&#061;<\/span> <span class=\"token number\">0<\/span><br \/>\n        <span class=\"token keyword\">if<\/span> current <span class=\"token operator\">&gt;<\/span> <span class=\"token number\">0<\/span>: streaks.append<span class=\"token punctuation\">(<\/span>current<span class=\"token punctuation\">)<\/span><br \/>\n        rows.append<span class=\"token punctuation\">(<\/span><span class=\"token punctuation\">{<\/span><br \/>\n            <span class=\"token string\">&#039;year&#039;<\/span><span class=\"token builtin class-name\">:<\/span> int<span class=\"token punctuation\">(<\/span>year<span class=\"token punctuation\">)<\/span>,<br \/>\n            <span class=\"token string\">&#039;max_consecutive_days&#039;<\/span><span class=\"token builtin class-name\">:<\/span> max<span class=\"token punctuation\">(<\/span>streaks<span class=\"token punctuation\">)<\/span> <span class=\"token keyword\">if<\/span> streaks <span class=\"token keyword\">else<\/span> <span class=\"token number\">0<\/span>,<br \/>\n            <span class=\"token string\">&#039;heat_event_count&#039;<\/span><span class=\"token builtin class-name\">:<\/span> len<span class=\"token punctuation\">(<\/span>streaks<span class=\"token punctuation\">)<\/span>,<br \/>\n            <span class=\"token string\">&#039;avg_event_length&#039;<\/span><span class=\"token builtin class-name\">:<\/span> round<span class=\"token punctuation\">(<\/span>float<span class=\"token punctuation\">(<\/span>np.mean<span class=\"token punctuation\">(<\/span>streaks<span class=\"token punctuation\">))<\/span>, <span class=\"token number\">2<\/span><span class=\"token punctuation\">)<\/span> <span class=\"token keyword\">if<\/span> streaks <span class=\"token keyword\">else<\/span> <span class=\"token number\">0.0<\/span>,<br \/>\n        <span class=\"token punctuation\">}<\/span><span class=\"token punctuation\">)<\/span><br \/>\n    pd.DataFrame<span class=\"token punctuation\">(<\/span>rows<span class=\"token punctuation\">)<\/span>.sort_values<span class=\"token punctuation\">(<\/span><span class=\"token string\">&#039;year&#039;<\/span><span class=\"token punctuation\">)<\/span>.to_csv<span class=\"token punctuation\">(<\/span><br \/>\n        os.path.join<span class=\"token punctuation\">(<\/span>output_dir, <span class=\"token string\">&#039;consecutive_heat.csv&#039;<\/span><span class=\"token punctuation\">)<\/span>, <span class=\"token assign-left variable\">encoding<\/span><span class=\"token operator\">&#061;<\/span><span class=\"token string\">&#039;utf-8&#039;<\/span>, <span class=\"token assign-left variable\">index<\/span><span class=\"token operator\">&#061;<\/span>False<br \/>\n    <span class=\"token punctuation\">)<\/span><\/p>\n<p>def thermal_cluster_profile_analysis<span class=\"token punctuation\">(<\/span>spark, df, logger_obj, output_dir<span class=\"token punctuation\">)<\/span>:<br \/>\n    <span class=\"token string\">&#034;&#034;<\/span>&#034;A17 \u70ed\u529b\u5206\u578b&#xff1a;5 \u7ef4\u7279\u5f81 \u2192 StandardScaler \u2192 K-Means<span class=\"token punctuation\">(<\/span>k<span class=\"token operator\">&#061;<\/span><span class=\"token number\">4<\/span><span class=\"token punctuation\">)<\/span><span class=\"token string\">&#034;&#034;<\/span>&#034;<br \/>\n    monthly <span class=\"token operator\">&#061;<\/span> df.groupBy<span class=\"token punctuation\">(<\/span><span class=\"token string\">&#039;year&#039;<\/span>, <span class=\"token string\">&#039;month&#039;<\/span><span class=\"token punctuation\">)<\/span>.agg<span class=\"token punctuation\">(<\/span><br \/>\n        spark_avg<span class=\"token punctuation\">(<\/span><span class=\"token string\">&#039;Mean&#039;<\/span><span class=\"token punctuation\">)<\/span>.alias<span class=\"token punctuation\">(<\/span><span class=\"token string\">&#039;avg_mean&#039;<\/span><span class=\"token punctuation\">)<\/span>,<br \/>\n        spark_avg<span class=\"token punctuation\">(<\/span><span class=\"token string\">&#039;Max&#039;<\/span><span class=\"token punctuation\">)<\/span>.alias<span class=\"token punctuation\">(<\/span><span class=\"token string\">&#039;avg_max&#039;<\/span><span class=\"token punctuation\">)<\/span>,<br \/>\n        spark_avg<span class=\"token punctuation\">(<\/span><span class=\"token string\">&#039;Std&#039;<\/span><span class=\"token punctuation\">)<\/span>.alias<span class=\"token punctuation\">(<\/span><span class=\"token string\">&#039;avg_std&#039;<\/span><span class=\"token punctuation\">)<\/span>,<br \/>\n        spark_avg<span class=\"token punctuation\">(<\/span><span class=\"token string\">&#039;p99&#039;<\/span><span class=\"token punctuation\">)<\/span>.alias<span class=\"token punctuation\">(<\/span><span class=\"token string\">&#039;avg_p99&#039;<\/span><span class=\"token punctuation\">)<\/span>,<br \/>\n        spark_avg<span class=\"token punctuation\">(<\/span><span class=\"token string\">&#039;p95&#039;<\/span><span class=\"token punctuation\">)<\/span>.alias<span class=\"token punctuation\">(<\/span><span class=\"token string\">&#039;avg_p95&#039;<\/span><span class=\"token punctuation\">)<\/span>,<br \/>\n    <span class=\"token punctuation\">)<\/span><br \/>\n    feature_pdf <span class=\"token operator\">&#061;<\/span> monthly.toPandas<span class=\"token punctuation\">(<\/span><span class=\"token punctuation\">)<\/span><br \/>\n    feature_cols <span class=\"token operator\">&#061;<\/span> <span class=\"token punctuation\">[<\/span><span class=\"token string\">&#039;avg_mean&#039;<\/span>, <span class=\"token string\">&#039;avg_max&#039;<\/span>, <span class=\"token string\">&#039;avg_std&#039;<\/span>, <span class=\"token string\">&#039;avg_p99&#039;<\/span>, <span class=\"token string\">&#039;avg_p95&#039;<\/span><span class=\"token punctuation\">]<\/span><br \/>\n    scaler <span class=\"token operator\">&#061;<\/span> StandardScaler<span class=\"token punctuation\">(<\/span><span class=\"token punctuation\">)<\/span><br \/>\n    scaled <span class=\"token operator\">&#061;<\/span> scaler.fit_transform<span class=\"token punctuation\">(<\/span>feature_pdf<span class=\"token punctuation\">[<\/span>feature_cols<span class=\"token punctuation\">]<\/span>.astype<span class=\"token punctuation\">(<\/span>float<span class=\"token punctuation\">)<\/span>.values<span class=\"token punctuation\">)<\/span><\/p>\n<p>    kmeans <span class=\"token operator\">&#061;<\/span> KMeans<span class=\"token punctuation\">(<\/span>n_clusters<span class=\"token operator\">&#061;<\/span><span class=\"token number\">4<\/span>, <span class=\"token assign-left variable\">random_state<\/span><span class=\"token operator\">&#061;<\/span><span class=\"token number\">42<\/span>, <span class=\"token assign-left variable\">n_init<\/span><span class=\"token operator\">&#061;<\/span><span class=\"token number\">10<\/span><span class=\"token punctuation\">)<\/span><br \/>\n    labels <span class=\"token operator\">&#061;<\/span> kmeans.fit_predict<span class=\"token punctuation\">(<\/span>scaled<span class=\"token punctuation\">)<\/span><br \/>\n    feature_pdf<span class=\"token punctuation\">[<\/span><span class=\"token string\">&#039;cluster_id&#039;<\/span><span class=\"token punctuation\">]<\/span> <span class=\"token operator\">&#061;<\/span> labels<br \/>\n    center_original <span class=\"token operator\">&#061;<\/span> scaler.inverse_transform<span class=\"token punctuation\">(<\/span>kmeans.cluster_centers_<span class=\"token punctuation\">)<\/span><\/p>\n<p>    cluster_labels <span class=\"token operator\">&#061;<\/span> <span class=\"token punctuation\">{<\/span><span class=\"token number\">0<\/span>: <span class=\"token string\">&#039;\u9ad8\u7a33\u6001\u578b&#039;<\/span>, <span class=\"token number\">1<\/span>: <span class=\"token string\">&#039;\u9ad8\u6ce2\u52a8\u578b&#039;<\/span>, <span class=\"token number\">2<\/span>: <span class=\"token string\">&#039;\u6781\u7aef\u5c3e\u90e8\u578b&#039;<\/span>, <span class=\"token number\">3<\/span>: <span class=\"token string\">&#039;\u6e29\u548c\u8fc7\u6e21\u578b&#039;<\/span><span class=\"token punctuation\">}<\/span><br \/>\n    rows <span class=\"token operator\">&#061;<\/span> <span class=\"token punctuation\">[<\/span><span class=\"token punctuation\">]<\/span><br \/>\n    <span class=\"token keyword\">for<\/span> <span class=\"token for-or-select variable\">cluster_id<\/span> <span class=\"token keyword\">in<\/span> range<span class=\"token punctuation\">(<\/span><span class=\"token number\">4<\/span><span class=\"token punctuation\">)<\/span>:<br \/>\n        center <span class=\"token operator\">&#061;<\/span> center_original<span class=\"token punctuation\">[<\/span>cluster_id<span class=\"token punctuation\">]<\/span><br \/>\n        rows.append<span class=\"token punctuation\">(<\/span><span class=\"token punctuation\">{<\/span><br \/>\n            <span class=\"token string\">&#039;cluster_id&#039;<\/span><span class=\"token builtin class-name\">:<\/span> cluster_id,<br \/>\n            <span class=\"token string\">&#039;cluster_label&#039;<\/span><span class=\"token builtin class-name\">:<\/span> cluster_labels.get<span class=\"token punctuation\">(<\/span>cluster_id, f<span class=\"token string\">&#039;\u7c07\u7fa4{cluster_id}&#039;<\/span><span class=\"token punctuation\">)<\/span>,<br \/>\n            <span class=\"token string\">&#039;sample_count&#039;<\/span><span class=\"token builtin class-name\">:<\/span> int<span class=\"token variable\"><span class=\"token punctuation\">((<\/span>labels <span class=\"token operator\">&#061;&#061;<\/span> cluster_id<span class=\"token punctuation\">)<\/span>.sum<span class=\"token punctuation\">(<\/span><span class=\"token punctuation\">))<\/span><\/span>,<br \/>\n            <span class=\"token string\">&#039;center_mean&#039;<\/span><span class=\"token builtin class-name\">:<\/span> round<span class=\"token punctuation\">(<\/span>float<span class=\"token punctuation\">(<\/span>center<span class=\"token punctuation\">[<\/span><span class=\"token number\">0<\/span><span class=\"token punctuation\">]<\/span><span class=\"token punctuation\">)<\/span>, <span class=\"token number\">2<\/span><span class=\"token punctuation\">)<\/span>,<br \/>\n            <span class=\"token string\">&#039;center_max&#039;<\/span><span class=\"token builtin class-name\">:<\/span> round<span class=\"token punctuation\">(<\/span>float<span class=\"token punctuation\">(<\/span>center<span class=\"token punctuation\">[<\/span><span class=\"token number\">1<\/span><span class=\"token punctuation\">]<\/span><span class=\"token punctuation\">)<\/span>, <span class=\"token number\">2<\/span><span class=\"token punctuation\">)<\/span>,<br \/>\n            <span class=\"token string\">&#039;center_std&#039;<\/span><span class=\"token builtin class-name\">:<\/span> round<span class=\"token punctuation\">(<\/span>float<span class=\"token punctuation\">(<\/span>center<span class=\"token punctuation\">[<\/span><span class=\"token number\">2<\/span><span class=\"token punctuation\">]<\/span><span class=\"token punctuation\">)<\/span>, <span class=\"token number\">2<\/span><span class=\"token punctuation\">)<\/span>,<br \/>\n            <span class=\"token string\">&#039;center_p99&#039;<\/span><span class=\"token builtin class-name\">:<\/span> round<span class=\"token punctuation\">(<\/span>float<span class=\"token punctuation\">(<\/span>center<span class=\"token punctuation\">[<\/span><span class=\"token number\">3<\/span><span class=\"token punctuation\">]<\/span><span class=\"token punctuation\">)<\/span>, <span class=\"token number\">2<\/span><span class=\"token punctuation\">)<\/span>,<br \/>\n        <span class=\"token punctuation\">}<\/span><span class=\"token punctuation\">)<\/span><br \/>\n    pd.DataFrame<span class=\"token punctuation\">(<\/span>rows<span class=\"token punctuation\">)<\/span>.to_csv<span class=\"token punctuation\">(<\/span><br \/>\n        os.path.join<span class=\"token punctuation\">(<\/span>output_dir, <span class=\"token string\">&#039;thermal_cluster_profile.csv&#039;<\/span><span class=\"token punctuation\">)<\/span>, <span class=\"token assign-left variable\">encoding<\/span><span class=\"token operator\">&#061;<\/span><span class=\"token string\">&#039;utf-8&#039;<\/span>, <span class=\"token assign-left variable\">index<\/span><span class=\"token operator\">&#061;<\/span>False<br \/>\n    <span class=\"token punctuation\">)<\/span><\/p>\n<p>def main<span class=\"token punctuation\">(<\/span><span class=\"token punctuation\">)<\/span>:<br \/>\n    spark <span class=\"token operator\">&#061;<\/span> create_spark<span class=\"token punctuation\">(<\/span><span class=\"token punctuation\">)<\/span><br \/>\n    try:<br \/>\n        <span class=\"token function\">df<\/span> <span class=\"token operator\">&#061;<\/span> load_preprocessed<span class=\"token punctuation\">(<\/span>spark<span class=\"token punctuation\">)<\/span><br \/>\n        logger.info<span class=\"token punctuation\">(<\/span><span class=\"token string\">&#039;\u4ece HDFS \u8bfb\u53d6\u6210\u529f&#xff0c;\u884c\u6570 %s&#039;<\/span>, df.count<span class=\"token punctuation\">(<\/span><span class=\"token punctuation\">))<\/span><br \/>\n        annual_trend_analysis<span class=\"token punctuation\">(<\/span>spark, df, logger, OUTPUT_DIR<span class=\"token punctuation\">)<\/span><br \/>\n        monthly_distribution_analysis<span class=\"token punctuation\">(<\/span>spark, df, logger, OUTPUT_DIR<span class=\"token punctuation\">)<\/span><br \/>\n        decade_comparison_analysis<span class=\"token punctuation\">(<\/span>spark, df, logger, OUTPUT_DIR<span class=\"token punctuation\">)<\/span><br \/>\n        seasonal_fluctuation_analysis<span class=\"token punctuation\">(<\/span>spark, df, logger, OUTPUT_DIR<span class=\"token punctuation\">)<\/span><br \/>\n        warming_rate_analysis<span class=\"token punctuation\">(<\/span>spark, df, logger, OUTPUT_DIR<span class=\"token punctuation\">)<\/span><br \/>\n        peak_year_ranking_analysis<span class=\"token punctuation\">(<\/span>spark, df, logger, OUTPUT_DIR<span class=\"token punctuation\">)<\/span><br \/>\n        high_heat_day_count_analysis<span class=\"token punctuation\">(<\/span>spark, df, logger, OUTPUT_DIR<span class=\"token punctuation\">)<\/span><br \/>\n        extreme_peak_tracking_analysis<span class=\"token punctuation\">(<\/span>spark, df, logger, OUTPUT_DIR<span class=\"token punctuation\">)<\/span><br \/>\n        percentile_comparison_analysis<span class=\"token punctuation\">(<\/span>spark, df, logger, OUTPUT_DIR<span class=\"token punctuation\">)<\/span><br \/>\n        heatwave_intensity_analysis<span class=\"token punctuation\">(<\/span>spark, df, logger, OUTPUT_DIR<span class=\"token punctuation\">)<\/span><br \/>\n        anomaly_detection_analysis<span class=\"token punctuation\">(<\/span>spark, df, logger, OUTPUT_DIR<span class=\"token punctuation\">)<\/span><br \/>\n        consecutive_heat_analysis<span class=\"token punctuation\">(<\/span>spark, df, logger, OUTPUT_DIR<span class=\"token punctuation\">)<\/span><br \/>\n        volatility_year_change_analysis<span class=\"token punctuation\">(<\/span>spark, df, logger, OUTPUT_DIR<span class=\"token punctuation\">)<\/span><br \/>\n        ci_width_analysis<span class=\"token punctuation\">(<\/span>spark, df, logger, OUTPUT_DIR<span class=\"token punctuation\">)<\/span><br \/>\n        range_comparison_analysis<span class=\"token punctuation\">(<\/span>spark, df, logger, OUTPUT_DIR<span class=\"token punctuation\">)<\/span><br \/>\n        percentile_structure_analysis<span class=\"token punctuation\">(<\/span>spark, df, logger, OUTPUT_DIR<span class=\"token punctuation\">)<\/span><br \/>\n        thermal_cluster_profile_analysis<span class=\"token punctuation\">(<\/span>spark, df, logger, OUTPUT_DIR<span class=\"token punctuation\">)<\/span><br \/>\n        logger.info<span class=\"token punctuation\">(<\/span><span class=\"token string\">&#039;\u5168\u90e8\u5206\u6790\u6267\u884c\u5b8c\u6bd5&#039;<\/span><span class=\"token punctuation\">)<\/span><br \/>\n    finally:<br \/>\n        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