{"id":102048,"date":"2026-09-08T03:43:08","date_gmt":"2026-09-07T19:43:08","guid":{"rendered":"https:\/\/www.wsisp.com\/helps\/102048.html"},"modified":"2026-09-08T03:43:08","modified_gmt":"2026-09-07T19:43:08","slug":"%e6%9c%80%e6%96%b0%e5%a4%a7%e6%95%b0%e6%8d%ae%e6%af%95%e4%b8%9a%e8%ae%be%e8%ae%a1%e9%80%89%e9%a2%98%e6%8e%a8%e8%8d%90-%e5%9f%ba%e4%ba%8e%e5%a4%a7%e6%95%b0%e6%8d%ae%e7%9a%84%e8%8d%af%e5%93%81%e7%bb%bc","status":"publish","type":"post","link":"https:\/\/www.wsisp.com\/helps\/102048.html","title":{"rendered":"\u6700\u65b0\u5927\u6570\u636e\u6bd5\u4e1a\u8bbe\u8ba1\u9009\u9898\u63a8\u8350-\u57fa\u4e8e\u5927\u6570\u636e\u7684\u836f\u54c1\u7efc\u5408\u4fe1\u606f\u6570\u636e\u53ef\u89c6\u5316\u5206\u6790-\u5927\u6570\u636e-Spark-Hadoop-Bigdata"},"content":{"rendered":"<p>\u2728\u4f5c\u8005\u4e3b\u9875&#xff1a;IT\u7814\u7a76\u5ba4\u2728 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Boot(Spring&#043;SpringMVC&#043;Mybatis)&#xff08;\u4e24\u4e2a\u7248\u672c\u90fd\u652f\u6301&#xff09;<\/li>\n<li>\u524d\u7aef&#xff1a;Vue&#043;ElementUI&#043;Echarts&#043;HTML&#043;CSS&#043;JavaScript&#043;jQuery<\/li>\n<li>\u8be6\u7ec6\u6280\u672f\u70b9&#xff1a;Hadoop\u3001HDFS\u3001Spark\u3001Spark SQL\u3001Pandas\u3001NumPy<\/li>\n<li>\u6570\u636e\u5e93&#xff1a;MySQL<\/li>\n<\/ul>\n<h2>\u4e09\u3001\u7cfb\u7edf\u754c\u9762\u5c55\u793a<\/h2>\n<ul>\n<li>\u57fa\u4e8e\u5927\u6570\u636e\u7684\u836f\u54c1\u7efc\u5408\u4fe1\u606f\u6570\u636e\u53ef\u89c6\u5316\u5206\u6790\u754c\u9762\u5c55\u793a&#xff1a; <img decoding=\"async\" src=\"https:\/\/www.wsisp.com\/helps\/wp-content\/uploads\/2026\/09\/20260907194302-6a9f13c6de352.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\/20260907194303-6a9f13c77a2e4.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\/20260907194304-6a9f13c81180c.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\/20260907194304-6a9f13c8bc222.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\/20260907194305-6a9f13c953c70.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\/20260907194305-6a9f13c9edc52.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\/20260907194306-6a9f13ca9d239.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\/20260907194307-6a9f13cb4001f.png\" alt=\"\u5728\u8fd9\u91cc\u63d2\u5165\u56fe\u7247\u63cf\u8ff0\" \/><\/li>\n<\/ul>\n<h2>\u56db\u3001\u4ee3\u7801\u53c2\u8003<\/h2>\n<ul>\n<li>\u9879\u76ee\u5b9e\u6218\u4ee3\u7801\u53c2\u8003&#xff1a;<\/li>\n<\/ul>\n<p>SparkSession spark &#061; SparkSession.builder().appName(&#034;DrugDataAnalysis&#034;).master(&#034;local[*]&#034;).getOrCreate();<br \/>\nDataset&lt;Row&gt; rawDf &#061; spark.read().option(&#034;header&#034;, true).option(&#034;inferSchema&#034;, true).csv(&#034;hdfs:\/\/master:9000\/drug_data.csv&#034;);<br \/>\nDataset&lt;Row&gt; cleanedDf &#061; rawDf.na().drop().filter(col(&#034;price&#034;).gt(0)).filter(col(&#034;sales&#034;).gt(0));<br \/>\nDataset&lt;Row&gt; totalDf &#061; cleanedDf.agg(sum(&#034;sales&#034;).alias(&#034;totalSales&#034;), avg(&#034;price&#034;).alias(&#034;avgPrice&#034;), count(&#034;id&#034;).alias(&#034;totalCount&#034;));<br \/>\nList&lt;Row&gt; totalList &#061; totalDf.collectAsList();Map&lt;String, Object&gt; totalResult &#061; new HashMap&lt;&gt;();totalResult.put(&#034;totalSales&#034;, totalList.get(0).getLong(0));totalResult.put(&#034;avgPrice&#034;, totalList.get(0).getDouble(1));totalResult.put(&#034;totalCount&#034;, totalList.get(0).getLong(2));<br \/>\nDataset&lt;Row&gt; categoryDf &#061; cleanedDf.groupBy(&#034;category&#034;).agg(sum(&#034;sales&#034;).alias(&#034;categorySales&#034;), avg(&#034;price&#034;).alias(&#034;categoryAvgPrice&#034;), count(&#034;id&#034;).alias(&#034;categoryCount&#034;)).orderBy(col(&#034;categorySales&#034;).desc());<br \/>\nList&lt;Row&gt; categoryList &#061; categoryDf.collectAsList();List&lt;Map&lt;String, Object&gt;&gt; categoryResult &#061; new ArrayList&lt;&gt;();for (Row row : categoryList) {Map&lt;String, Object&gt; map &#061; new HashMap&lt;&gt;();map.put(&#034;category&#034;, row.getString(0));map.put(&#034;sales&#034;, row.getLong(1));map.put(&#034;avgPrice&#034;, row.getDouble(2));map.put(&#034;count&#034;, row.getLong(3));categoryResult.add(map);}<br \/>\nDataset&lt;Row&gt; priceRangeDf &#061; cleanedDf.withColumn(&#034;priceRange&#034;, when(col(&#034;price&#034;).leq(10), &#034;0-10&#034;).when(col(&#034;price&#034;).leq(50), &#034;10-50&#034;).when(col(&#034;price&#034;).leq(100), &#034;50-100&#034;).otherwise(&#034;100&#043;&#034;)).groupBy(&#034;priceRange&#034;).count().orderBy(&#034;priceRange&#034;);<br \/>\nList&lt;Row&gt; priceRangeList &#061; priceRangeDf.collectAsList();List&lt;Map&lt;String, Object&gt;&gt; priceRangeResult &#061; new ArrayList&lt;&gt;();for (Row row : priceRangeList) {Map&lt;String, Object&gt; map &#061; new HashMap&lt;&gt;();map.put(&#034;range&#034;, row.getString(0));map.put(&#034;count&#034;, row.getLong(1));priceRangeResult.add(map);}<br \/>\nDataset&lt;Row&gt; enterpriseDf &#061; cleanedDf.groupBy(&#034;enterprise&#034;).agg(sum(&#034;sales&#034;).alias(&#034;enterpriseSales&#034;), avg(&#034;price&#034;).alias(&#034;enterpriseAvgPrice&#034;), count(&#034;id&#034;).alias(&#034;productCount&#034;)).orderBy(col(&#034;enterpriseSales&#034;).desc()).limit(20);<br \/>\nList&lt;Row&gt; enterpriseList &#061; enterpriseDf.collectAsList();List&lt;Map&lt;String, Object&gt;&gt; enterpriseResult &#061; new ArrayList&lt;&gt;();for (Row row : enterpriseList) {Map&lt;String, Object&gt; map &#061; new HashMap&lt;&gt;();map.put(&#034;enterprise&#034;, row.getString(0));map.put(&#034;sales&#034;, row.getLong(1));map.put(&#034;avgPrice&#034;, row.getDouble(2));map.put(&#034;count&#034;, row.getLong(3));enterpriseResult.add(map);}<br \/>\nDataset&lt;Row&gt; algorithmDf &#061; cleanedDf.groupBy(&#034;category&#034;).agg(stddev(&#034;price&#034;).alias(&#034;priceStd&#034;), max(&#034;price&#034;).alias(&#034;maxPrice&#034;), min(&#034;price&#034;).alias(&#034;minPrice&#034;)).withColumn(&#034;priceVolatility&#034;, col(&#034;priceStd&#034;).divide(col(&#034;avgPrice&#034;)));<br \/>\nList&lt;Row&gt; algorithmList &#061; algorithmDf.collectAsList();List&lt;Map&lt;String, Object&gt;&gt; algorithmResult &#061; new ArrayList&lt;&gt;();for (Row row : algorithmList) {Map&lt;String, Object&gt; map &#061; new HashMap&lt;&gt;();map.put(&#034;category&#034;, row.getString(0));map.put(&#034;std&#034;, row.getDouble(1));map.put(&#034;max&#034;, row.getDouble(2));map.put(&#034;min&#034;, row.getDouble(3));map.put(&#034;volatility&#034;, row.getDouble(4));algorithmResult.add(map);}<br \/>\nDataset&lt;Row&gt; drugCatalogDf &#061; cleanedDf.select(&#034;id&#034;, &#034;name&#034;, &#034;specification&#034;, &#034;category&#034;, &#034;enterprise&#034;, &#034;price&#034;, &#034;sales&#034;).orderBy(col(&#034;sales&#034;).desc()).limit(100);<br \/>\nList&lt;Row&gt; catalogList &#061; drugCatalogDf.collectAsList();List&lt;Map&lt;String, Object&gt;&gt; catalogResult &#061; new ArrayList&lt;&gt;();for (Row row : catalogList) {Map&lt;String, Object&gt; map &#061; new HashMap&lt;&gt;();map.put(&#034;id&#034;, row.getString(0));map.put(&#034;name&#034;, row.getString(1));map.put(&#034;spec&#034;, row.getString(2));map.put(&#034;category&#034;, row.getString(3));map.put(&#034;enterprise&#034;, row.getString(4));map.put(&#034;price&#034;, row.getDouble(5));map.put(&#034;sales&#034;, row.getLong(6));catalogResult.add(map);}<\/p>\n<h2>\u4e94\u3001\u7cfb\u7edf\u89c6\u9891<\/h2>\n<p>\u57fa\u4e8e\u5927\u6570\u636e\u7684\u836f\u54c1\u7efc\u5408\u4fe1\u606f\u6570\u636e\u53ef\u89c6\u5316\u5206\u6790\u9879\u76ee\u89c6\u9891&#xff1a; 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