300字范文 > 大数据技术之Hadoop(十一)——网站流量日志数据分析系统

大数据技术之Hadoop(十一)——网站流量日志数据分析系统

时间：2019-01-17 14:51:41

素材：

一、模块开发——数据预处理

1、分析预处理的数据

2、实现数据的预处理

（1）创建Maven项目，添加相关依赖

（2）创建JavaBean对象，封装日志记录

（3）创建MapReduce程序，执行数据预处理

二、模块开发——数据仓库开发

1、上传文件

2、实现数据仓库

三、模块开发——数据分析

四、模块开发——数据导出

五、模块开发——日志分析系统报表展示

1、搭建日志分析系统

（1）创建项目，添加相关依赖

（2）编写配置文件

2、实现报表功能展示

（1）创建持久化类

（2）实现DAO层

（3）实现Service层

（4）实现Controller层

（5）实现页面功能

3、系统功能模块展示

编辑

参考书籍：

素材：

http://链接: /s/1aNxbVjNq1z1A-oOIYy_E4Q?pwd=gjpt 提取码: gjpthttp://链接: /s/1aNxbVjNq1z1A-oOIYy_E4Q?pwd=gjpt 提取码: gjpt

一、模块开发——数据预处理

1、分析预处理的数据

在收集的日志文件中，通常情况下，不能直接将日志文件进行数据分析，这是因为日志文件中有许多不合法的数据(比如日志数据在网络传输过程中发送数据丢失)。

在数据预处理阶段,主要目的就是对收集的原始数据进行清洗和筛选，因此使用MapReduce 技术就可以轻松实现。在实际开发中，数据预处理过程通常不会直接将不合法的数据直接删除，而是对每条数据添加标识字段，从而避免其他业务使用时丢失数据。

另外,此次数据预处理只是清洗和筛选不合法的数据信息，会读取每行日志文件数据并最终输出一条数据，不会进行其他操作，因此在使用MapReduce技术进行处理过程中，只会涉及 Map 阶段，不会涉及Reduce 阶段。在默认情况下，ReduceTask值为1，因此在主运行函数中，需要设置 Job.setNumReduceTasks(0)。

2、实现数据的预处理

（1）创建Maven项目，添加相关依赖

pom.xml文件配置如下：

（2）创建JavaBean对象，封装日志记录

收集的日志数据中，每一行代表一条日志记录，并且包含有多个用空格分隔的字段信息，为了方便后续数据处理，创建一个 JavaBean 对象对每条数据进行封装。

WebLogBean.java

package cn.itcast.weblog.bean;import org.apache.hadoop.io.Writable;import java.io.DataInput;import java.io.DataOutput;import java.io.IOException;/*** 对接外部数据的层，表结构定义最好跟外部数据源保持一致* 同时实现序列号，方便网络数据传播*/public class WebLogBean implements Writable {private boolean valid = true; //标记数据是否合法private String remote_addr;//访客IP地址private String remote_user;//记录访客用户信息，忽略属性“-”private String time_local;//记录访问时间与时区private String request; //记录请求的URLprivate String status;//请求状态private String body_bytes_sent; //记录发送给客户端文件主体内容大小private String http_referer; //记录从哪个页面链接访问过来的private String http_user_agent; //记录客户浏览器的相关信息//设置 WebLogBean 进行字段数据封装public void setBean(boolean valid, String remote_addr, String remote_user,String time_local, String request, String status,String body_bytes_sent,String http_referer, String http_user_agent) {this.valid = valid;this.remote_addr = remote_addr;this.remote_user = remote_user;this.time_local = time_local;this.request = request;this.status = status;this.body_bytes_sent = body_bytes_sent;this.http_referer = http_referer;this.http_user_agent = http_user_agent;}public boolean isValid() {return valid;}public void setValid(boolean valid) {this.valid = valid;}public String getRemote_addr() {return remote_addr;}public void setRemote_addr(String remote_addr) {this.remote_addr = remote_addr;}public String getRemote_user() {return remote_user;}public void setRemote_user(String remote_user) {this.remote_user = remote_user;}public String getTime_local() {return time_local;}public void setTime_local(String time_local) {this.time_local = time_local;}public String getRequest() {return request;}public void setRequest(String request) {this.request = request;}public String getStatus() {return status;}public void setStatus(String status) {this.status = status;}public String getBody_bytes_sent() {return body_bytes_sent;}public void setBody_bytes_sent(String body_bytes_sent) {this.body_bytes_sent = body_bytes_sent;}public String getHttp_referer() {return http_referer;}public void setHttp_referer(String http_referer) {this.http_referer = http_referer;}public String getHttp_user_agent() {return http_user_agent;}public void setHttp_user_agent(String http_user_agent) {this.http_user_agent = http_user_agent;}//重写 toString() 方法，使用 Hive 默认分隔符进行分隔，为后续导入 Hive 表提供便利@Overridepublic String toString() {StringBuilder sb = new StringBuilder();sb.append(valid);sb.append("\001").append(this.getRemote_addr());sb.append("\001").append(this.getRemote_user());sb.append("\001").append(this.getTime_local());sb.append("\001").append(this.getRequest());sb.append("\001").append(this.getStatus());sb.append("\001").append(this.getBody_bytes_sent());sb.append("\001").append(this.getHttp_referer());sb.append("\001").append(this.getHttp_user_agent());return sb.toString();}//序列化方法@Overridepublic void readFields(DataInput dataInput) throws IOException {this.valid = dataInput.readBoolean();this.remote_addr = dataInput.readUTF();this.remote_user = dataInput.readUTF();this.time_local = dataInput.readUTF();this.request = dataInput.readUTF();this.status = dataInput.readUTF();this.body_bytes_sent = dataInput.readUTF();this.http_referer = dataInput.readUTF();this.http_user_agent = dataInput.readUTF();}// 反序列化方法（注意与序列化方法顺序保持一致）@Overridepublic void write(DataOutput dataOutput) throws IOException {dataOutput.writeBoolean(this.valid);dataOutput.writeUTF(this.remote_addr);dataOutput.writeUTF(this.remote_user);dataOutput.writeUTF(this.time_local);dataOutput.writeUTF(this.request);dataOutput.writeUTF(this.status);dataOutput.writeUTF(this.body_bytes_sent);dataOutput.writeUTF(this.http_referer);dataOutput.writeUTF(this.http_user_agent);}}

（3）创建MapReduce程序，执行数据预处理

创建 JavaBean 实体类后，接下来开始编写 MapReduce 程序，进行数据预处理。

WebLogPreProcess.java

package cn.itcast.weblog.preproces;import cn.itcast.weblog.bean.WebLogBean;import org.apache.hadoop.conf.Configuration;import org.apache.hadoop.fs.Path;import org.apache.hadoop.io.LongWritable;import org.apache.hadoop.io.NullWritable;import org.apache.hadoop.io.Text;import org.apache.hadoop.mapreduce.Job;import org.apache.hadoop.mapreduce.Mapper;import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;import java.io.IOException;import java.util.HashSet;import java.util.Set;/*** 日志数据处理：数据清洗、日期格式转换、缺失字段填充默认值、字段添加合法标记*/public class WebLogPreProcess {public static void main(String[] args) throws Exception{Configuration conf = new Configuration();Job job = Job.getInstance(conf);job.setJarByClass(WebLogPreProcess.class);job.setMapperClass(WebLogPreProcessMapper.class);job.setOutputKeyClass(Text.class);job.setOutputValueClass(NullWritable.class);//此次案例测试数据不是非常大，所以使用本地路径//（实际情况会对 HDFS 上存储的文件进行处理）FileInputFormat.setInputPaths(job, new Path("/home/huanganchi/Hadoop/实训项目/HadoopDemo/textHadoop/weblog/input"));FileOutputFormat.setOutputPath(job, new Path("/home/huanganchi/Hadoop/实训项目/HadoopDemo/textHadoop/weblog/output"));//将 ReduceTask 属设置为 0，不需要 Reduce 阶段job.setNumReduceTasks(0);boolean res = job.waitForCompletion(true);System.exit(res ? 0 : 1);}//mapreduce 程序 map 阶段public static class WebLogPreProcessMapper extends Mapper<LongWritable, Text, Text, NullWritable> {//用来存储网站 URL 分类数据Set<String> pages = new HashSet<String>();Text k = new Text();NullWritable v = NullWritable.get();/*** 设置初始化方法，用来表示用户请求的是合法数据*/@Overrideprotected void setup(Context context) throws IOException, InterruptedException {pages.add("/about");pages.add("/black-ip-list");pages.add("/cassendra-cluster/");pages.add("/finance-rhive-repurchase");pages.add("/hadoop-family-roadmad");pages.add("/hadoop-hive-intro/");pages.add("/hadoop-zookeeper-intro");pages.add("/hadoop-mahout-roadmap");}/*** 重写 map()方法，对每行记录重新解析转换并输出*/@Overrideprotected void map(LongWritable key, Text value, Context context) throws IOException, InterruptedException {//获取一行数据String line = value.toString();//调用解析类 WebLogParser 解析日志数据，最后封装为 WebLogBean 对象WebLogBean webLogBean = WebLogParser.parser(line);if (webLogBean != null) {//过滤 js/图片/css 等静态资源WebLogParser.filtStaticResource(webLogBean, pages);k.set(webLogBean.toString());context.write(k, v);}}}}

WebLogParser.java

package cn.itcast.weblog.preproces;import cn.itcast.weblog.bean.WebLogBean;import java.text.ParseException;import java.text.SimpleDateFormat;import java.util.Locale;import java.util.Set;public class WebLogParser {//定义时间格式public static SimpleDateFormat df1 = new SimpleDateFormat("dd/MMM/yyyy:HH:mm:ss", Locale.US);public static SimpleDateFormat df2 = new SimpleDateFormat("yyyy-MM-dd HH:mm:ss", Locale.US);/*** 根据采集的数据字段信息进行解析封装*/public static WebLogBean parser(String line) {WebLogBean webLogBean = new WebLogBean();//把一行数据以空格字符切割并存入数组arr中String[] arr = line.split(" ");//如果数组长度小于等于11，说明这条数据不完整，因此可以忽略这条数据if (arr.length > 11) {//满足条件的数据逐个赋值给webLogBean对象webLogBean.setRemote_addr(arr[0]);webLogBean.setRemote_user(arr[1]);String time_local = formatDate(arr[3].substring(1));if (null == time_local || "".equals(time_local)) time_local = "-invalid_time-";webLogBean.setTime_local(time_local);webLogBean.setRequest(arr[6]);webLogBean.setStatus(arr[8]);webLogBean.setBody_bytes_sent(arr[9]);webLogBean.setHttp_referer(arr[10]);//如果useragent元素较多，拼接useragentif (arr.length > 12) {StringBuilder sb = new StringBuilder();for (int i = 11; i < arr.length; i++) {sb.append(arr[i]);}webLogBean.setHttp_user_agent(sb.toString());} else {webLogBean.setHttp_user_agent(arr[11]);}//大于 400，HTTP 错误if (Integer.parseInt(webLogBean.getStatus()) >= 400) {webLogBean.setValid(false);}if ("-invalid_time-".equals(webLogBean.getTime_local())) {webLogBean.setValid(false);}} else {webLogBean = null;}return webLogBean;}//对请求路径资源是否合法进行标记public static void filtStaticResource(WebLogBean bean, Set<String> pages) {if (!pages.contains(bean.getRequest())) {bean.setValid(false);}}//格式化时间方法public static String formatDate(String time_local) {try {return df2.format(df1.parse(time_local));} catch (ParseException e) {return null;}}}

运行结果：

二、模块开发——数据仓库开发

1、上传文件

在启动了Hadoop的Linux系统root目录下创建目录weblog，并将预处理产生的结果文件上传到 weblog 目录下。

cdmkdir weblogcd weblog执行 rz 文件上传命令

在HDFS上创建目录，用于存放预处理过的数据，并上传数据到HDFS。

hadoop fs -mkdir -p /weblog/preprocessedhadoop fs -put part-m-00000 /weblog/preprocessed

2、实现数据仓库

启动Hive数据仓库，执行以下操作：--创建数据仓库DROP DATABASE IF EXISTS weblog;CREATE DATABASE weblog;USE weblog;--创建表CREATE TABLE ods_weblog_origin (valid string,--有效标志remote_addr string, --来源IPremote_user string,--用户标志time_local string,--访问完整时间request string,--请求的URLstatus string,--响应码body_bytes_sent string,--传输字节数http_referer string,--来源URLhttp_user_agent string--客户终端标志)partitioned by (datestr string)row format delimited fields terminated by '\001';--导入数据load data inpath '/weblog/preprocessed' overwrite into table ods_weblog_origin partition(datestr='0918');--生成明细表--1. 创建明细表 ods_weblog_detwail CREATE TABLE ods_weblog_detwail (valid string,--有效标志remote_addrstring, --来源IPremote_userstring,--用户标志time_local string,--访问完整时间daystr string,--访问日期timestr string,--访问时间month string,--访问月day string,--访问日hour string,--访问时request string,--请求的URLstatus string,--响应码body_bytes_sent string,--传输字节数http_referer string,--来源URLref_host string,--来源的hostref_pathstring,--来源路径ref_querystring,--来源参数queryref_query_idstring,--来源参数query的值http_user_agent string--客户终端标志)partitioned by (datestr string);--2. 创建临时中间表 t_ods_tmp_referurlCREATE TABLE t_ods_tmp_referurl as SELECT a.*, b.* FROM ods_weblog_origin a LATERAL VIEWparse_url_tuple(regexp_replace(http_referer, "\"", ""),'HOST', 'PATH', 'QUERY', 'QUERY:id') b as host, path, query, query_id;--3. 创建临时中间表 t_ods_tmp_detailCREATE TABLE t_ods_tmp_detail as SELECT b.*, substring(time_local, 0, 10) as daystr, substring(time_local, 12) as tmstr,substring(time_local, 6, 2) as month,substring(time_local, 9, 2) as day,substring(time_local, 11, 3) as hourFROM t_ods_tmp_referurl b;--4. 修改默认动态分区参数set hive.exec.dynamic.partition=true;set hive.exec.dynamic.partition.mode=nonstrict;--5. 向 ods_weblog_detwail 表中加载数据insert overwrite table ods_weblog_detwail partition(datestr)SELECT DISTINCT otd.valid, otd.remote_addr, otd.remote_user, otd.time_local, otd.daystr, otd.tmstr, otd.month, otd.day, otd.hour,otr.request, otr.status, otr.body_bytes_sent,otr.http_referer, otr.host, otr.path,otr.query, otr.query_id, otr.http_user_agent, otd.daystrFROM t_ods_tmp_detail as otd, t_ods_tmp_referurl as otrWHERE otd.remote_addr = otr.remote_addrAND otd.time_local = otr.time_localAND otd.body_bytes_sent = otr.body_bytes_sentAND otd.request = otr.request;

三、模块开发——数据分析

--数据分析--流量分析--创建每日访问量表dw_pvs_everydayCREATE TABLE IF NOT EXISTS dw_pvs_everyday(pvs bigint, month string, day string);--从宽表 ods_weblog_detwail 获取每日访问量数据并插入维度表 dw_pvs_everydayINSERT INTO TABLE dw_pvs_everydaySELECT COUNT(*) AS pvs, owd.month AS month, owd.day AS day FROM ods_weblog_detwail owd GROUP BY owd.month, owd.day;--人均浏览量分析--创建维度表dw_avgpv_user_everydayCREATE TABLE IF NOT EXISTS dw_avgpv_user_everyday (day string, avgpv string);--从宽表 ods_weblog_detwail 获取相关数据并插入维度表 dw_avgpv_user_everydayINSERT INTO TABLE dw_avgpv_user_everydaySELECT '-09-18', SUM(b.pvs)/COUNT(b.remote_addr) FROM(SELECT remote_addr, COUNT(1) AS pvs FROM ods_weblog_detwail WHEREdatestr = '-09-18' GROUP by remote_addr) b;INSERT INTO TABLE dw_avgpv_user_everydaySELECT '-09-19', SUM(b.pvs)/COUNT(b.remote_addr) FROM(SELECT remote_addr, COUNT(1) AS pvs FROM ods_weblog_detwail WHEREdatestr = '-09-19' GROUP by remote_addr) b;INSERT INTO TABLE dw_avgpv_user_everydaySELECT '-09-20', SUM(b.pvs)/COUNT(b.remote_addr) FROM(SELECT remote_addr, COUNT(1) AS pvs FROM ods_weblog_detwail WHEREdatestr = '-09-20' GROUP by remote_addr) b;INSERT INTO TABLE dw_avgpv_user_everydaySELECT '-09-21', SUM(b.pvs)/COUNT(b.remote_addr) FROM(SELECT remote_addr, COUNT(1) AS pvs FROM ods_weblog_detwail WHEREdatestr = '-09-21' GROUP by remote_addr) b;INSERT INTO TABLE dw_avgpv_user_everydaySELECT '-09-22', SUM(b.pvs)/COUNT(b.remote_addr) FROM(SELECT remote_addr, COUNT(1) AS pvs FROM ods_weblog_detwail WHEREdatestr = '-09-22' GROUP by remote_addr) b;INSERT INTO TABLE dw_avgpv_user_everydaySELECT '-09-23', SUM(b.pvs)/COUNT(b.remote_addr) FROM(SELECT remote_addr, COUNT(1) AS pvs FROM ods_weblog_detwail WHEREdatestr = '-09-23' GROUP by remote_addr) b;INSERT INTO TABLE dw_avgpv_user_everydaySELECT '-09-24', SUM(b.pvs)/COUNT(b.remote_addr) FROM(SELECT remote_addr, COUNT(1) AS pvs FROM ods_weblog_detwail WHEREdatestr = '-09-24' GROUP by remote_addr) b;

四、模块开发——数据导出

1. 创建 MySql 数据库和表--数据导出--创建数据仓库DROP DATABASE IF EXISTS sqoopdb;CREATE DATABASE sqoopdb;USE sqoopdb;--创建表CREATE TABLE t_avgpv_num (dateStr VARCHAR(255) DEFAULT NULL,avgPvNum DECIMAL(6,2) DEFAULT NULL) ENGINE=MyISAM DEFAULT CHARSET=utf8;2. 执行数据导出命令sqoop export \--connect jdbc:mysql://hadoop01.bgd01:3306/sqoopdb \--username root \--password 123456 \--table t_avgpv_num \--columns "dateStr,avgPvNum" \--fields-terminated-by '\001' \--export-dir /user/hive/warehouse/weblog.db/dw_avgpv_user_everyday

五、模块开发——日志分析系统报表展示

1、搭建日志分析系统

（1）创建项目，添加相关依赖

创建一个Java Web 框架的Maven工程

pom.xml

<?xml version="1.0" encoding="UTF-8"?><project xmlns="/POM/4.0.0"xmlns:xsi="/2001/XMLSchema-instance"xsi:schemaLocation="/POM/4.0.0 /xsd/maven-4.0.0.xsd"><modelVersion>4.0.0</modelVersion><groupId>cn.itcast</groupId><artifactId>Weblog</artifactId><version>1.0-SNAPSHOT</version><packaging>war</packaging><dependencies><dependency><groupId>org.springframework</groupId><artifactId>spring-context</artifactId><version>4.2.4.RELEASE</version></dependency><dependency><groupId>org.springframework</groupId><artifactId>spring-beans</artifactId><version>4.2.4.RELEASE</version></dependency><dependency><groupId>org.springframework</groupId><artifactId>spring-webmvc</artifactId><version>4.2.4.RELEASE</version></dependency><dependency><groupId>org.springframework</groupId><artifactId>spring-jdbc</artifactId><version>4.2.4.RELEASE</version></dependency><dependency><groupId>org.springframework</groupId><artifactId>spring-aspects</artifactId><version>4.2.4.RELEASE</version></dependency><dependency><groupId>org.springframework</groupId><artifactId>spring-jms</artifactId><version>4.2.4.RELEASE</version></dependency><dependency><groupId>org.springframework</groupId><artifactId>spring-context-support</artifactId><version>4.2.4.RELEASE</version></dependency><dependency><groupId>org.mybatis</groupId><artifactId>mybatis</artifactId><version>3.2.8</version></dependency><dependency><groupId>org.mybatis</groupId><artifactId>mybatis-spring</artifactId><version>1.2.2</version></dependency><dependency><groupId>com.github.miemiedev</groupId><artifactId>mybatis-paginator</artifactId><version>1.2.15</version></dependency><dependency><groupId>mysql</groupId><artifactId>mysql-connector-java</artifactId><version>5.1.32</version></dependency><dependency><groupId>com.alibaba</groupId><artifactId>druid</artifactId><version>1.0.9</version></dependency><dependency><groupId>jstl</groupId><artifactId>jstl</artifactId><version>1.2</version></dependency><dependency><groupId>javax.servlet</groupId><artifactId>servlet-api</artifactId><version>2.5</version><scope>provided</scope></dependency><dependency><groupId>javax.servlet</groupId><artifactId>jsp-api</artifactId><version>2.0</version><scope>provided</scope></dependency><dependency><groupId>junit</groupId><artifactId>junit</artifactId><version>4.12</version></dependency><dependency><groupId>com.fasterxml.jackson.core</groupId><artifactId>jackson-databind</artifactId><version>2.4.2</version></dependency></dependencies><build><finalName>${project.artifactId}</finalName><resources><resource><directory>src/main/java</directory><includes><include>**/*.properties</include><include>**/*.xml</include></includes><filtering>false</filtering></resource><resource><directory>src/main/resources</directory><includes><include>**/*.properties</include><include>**/*.xml</include></includes><filtering>false</filtering></resource></resources><plugins><plugin><groupId>org.apache.maven.plugins</groupId><artifactId>maven-compiler-plugin</artifactId><version>3.2</version><configuration><source>1.8</source><target>1.8</target><encoding>UTF-8</encoding></configuration></plugin><plugin><groupId>org.apache.tomcat.maven</groupId><artifactId>tomcat7-maven-plugin</artifactId><version>2.2</version><configuration><path>/</path><port>8080</port></configuration></plugin></plugins></build><properties><piler.source>8</piler.source><piler.target>8</piler.target><project.build.sourceEncoding>UTF-8</project.build.sourceEncoding></properties></project>

（2）编写配置文件

applicationContext.xml

<?xml version="1.0" encoding="UTF-8"?><beans xmlns="/schema/beans"xmlns:context="/schema/context" xmlns:p="/schema/beans"xmlns:aop="/schema/aop" xmlns:tx="/schema/tx"xmlns:xsi="/2001/XMLSchema-instance"xsi:schemaLocation="/schema/beans /schema/beans/spring-beans-4.2.xsd/schema/context /schema/context/spring-context-4.2.xsd/schema/aop /schema/aop/spring-aop-4.2.xsd /schema/tx /schema/tx/spring-tx-4.2.xsd/schema/util /schema/util/spring-util-4.2.xsd"><context:property-placeholder location="classpath:properties/db.properties" /><bean id="dataSource" class="com.alibaba.druid.pool.DruidDataSource"destroy-method="close"><property name="url" value="${jdbc.url}" /><property name="username" value="${jdbc.username}" /><property name="password" value="${jdbc.password}" /><property name="driverClassName" value="${jdbc.driver}" /><property name="maxActive" value="10" /><property name="minIdle" value="5" /></bean><bean id="sqlSessionFactory" class="org.mybatis.spring.SqlSessionFactoryBean"><property name="dataSource" ref="dataSource" /><property name="configLocation" value="classpath:mybatis/SqlMapConfig.xml" /></bean><bean class="org.mybatis.spring.mapper.MapperScannerConfigurer"><property name="basePackage" value="cn.itcast.mapper" /></bean><bean id="transactionManager"class="org.springframework.jdbc.datasource.DataSourceTransactionManager"><property name="dataSource" ref="dataSource" /></bean><tx:advice id="txAdvice" transaction-manager="transactionManager"><tx:attributes><tx:method name="save*" propagation="REQUIRED" /><tx:method name="insert*" propagation="REQUIRED" /><tx:method name="add*" propagation="REQUIRED" /><tx:method name="create*" propagation="REQUIRED" /><tx:method name="delete*" propagation="REQUIRED" /><tx:method name="update*" propagation="REQUIRED" /><tx:method name="find*" propagation="SUPPORTS" read-only="true" /><tx:method name="select*" propagation="SUPPORTS" read-only="true" /><tx:method name="get*" propagation="SUPPORTS" read-only="true" /></tx:attributes></tx:advice><aop:config><aop:advisor advice-ref="txAdvice"pointcut="execution(* cn.itcast.service..*.*(..))" /></aop:config><context:component-scan base-package="cn.itcast.service" /></beans>

db.properties

jdbc.driver=com.mysql.jdbc.Driverjdbc.url=jdbc:mysql://192.168.8.201:3306/sqoopdb?characterEncoding=utf-8jdbc.username=rootjdbc.password=123456

springmvc.xml

<?xml version="1.0" encoding="UTF-8"?><beans xmlns="/schema/beans"xmlns:xsi="/2001/XMLSchema-instance" xmlns:p="/schema/beans"xmlns:context="/schema/context"xmlns:mvc="/schema/mvc"xsi:schemaLocation="/schema/beans /schema/beans/spring-beans-4.2.xsd/schema/mvc /schema/mvc/spring-mvc-4.2.xsd/schema/context /schema/context/spring-context-4.2.xsd"><context:component-scan base-package="cn.itcast.controller" /><mvc:annotation-driven /><beanclass="org.springframework.web.servlet.view.InternalResourceViewResolver"><property name="prefix" value="/WEB-INF/jsp/" /><property name="suffix" value=".jsp" /></bean><mvc:resources location="/css/" mapping="/css/**"/><mvc:resources location="/js/" mapping="/js/**"/><mvc:resources location="/echarts/" mapping="/echarts/**"/><mvc:resources location="/assets/" mapping="/assets/**"/><mvc:resources location="/img/" mapping="/img/**"/></beans>

web.xml

<?xml version="1.0" encoding="UTF-8"?><web-app xmlns:xsi="/2001/XMLSchema-instance" xmlns="/xml/ns/javaee" xsi:schemaLocation="/xml/ns/javaee /xml/ns/javaee/web-app_2_5.xsd" version="2.5"><display-name>Weblog</display-name><welcome-file-list><welcome-file>index.html</welcome-file></welcome-file-list><context-param><param-name>contextConfigLocation</param-name><param-value>classpath:spring/applicationContext.xml</param-value></context-param><listener><listener-class>org.springframework.web.context.ContextLoaderListener</listener-class></listener><filter><filter-name>CharacterEncodingFilter</filter-name><filter-class>org.springframework.web.filter.CharacterEncodingFilter</filter-class><init-param><param-name>encoding</param-name><param-value>utf-8</param-value></init-param></filter><filter-mapping><filter-name>CharacterEncodingFilter</filter-name><url-pattern>/*</url-pattern></filter-mapping><servlet><servlet-name>data-report</servlet-name><servlet-class>org.springframework.web.servlet.DispatcherServlet</servlet-class><init-param><param-name>contextConfigLocation</param-name><param-value>classpath:spring/springmvc.xml</param-value></init-param><load-on-startup>1</load-on-startup></servlet><servlet-mapping><servlet-name>data-report</servlet-name><url-pattern>/</url-pattern></servlet-mapping><error-page><error-code>404</error-code><location>/WEB-INF/jsp/404.jsp</location></error-page></web-app>

SqlMapConfig.xml

<?xml version="1.0" encoding="UTF-8" ?><!DOCTYPE configuration PUBLIC "-////DTD Config 3.0//EN" "/dtd/mybatis-3-config.dtd"><configuration></configuration>

2、实现报表功能展示

（1）创建持久化类

TAvgpvNum.java

package cn.itcast.pojo;import java.math.BigDecimal;public class TAvgpvNum {private String datestr;// 日期private BigDecimal avgpvnum;// 平均PV数量public String getDatestr() {return datestr;}public void setDatestr(String datestr) {this.datestr = datestr == null ? null : datestr.trim();}public BigDecimal getAvgpvnum() {return avgpvnum;}public void setAvgpvnum(BigDecimal avgpvnum) {this.avgpvnum = avgpvnum;}}

AvgToPageBean.java

package cn.itcast.pojo;public class AvgToPageBean {private String[] dates;private double[] data;public String[] getDates() {return dates;}public void setDates(String[] dates) {this.dates = dates;}public double[] getData() {return data;}public void setData(double[] data) {this.data = data;}}

（2）实现DAO层

TAvgpvNumMapper.java

package cn.itcast.mapper;import java.util.List;import cn.itcast.pojo.TAvgpvNum;public interface TAvgpvNumMapper {public List<TAvgpvNum> selectByDate(String startDate, String endDate);}

TAvgpvNumMapper.xml

<?xml version="1.0" encoding="UTF-8" ?><!DOCTYPE mapper PUBLIC "-////DTD Mapper 3.0//EN" "/dtd/mybatis-3-mapper.dtd" ><mapper namespace="cn.itcast.mapper.TAvgpvNumMapper"><select id="selectByDate" resultType="cn.itcast.pojo.TAvgpvNum"parameterType="String">select *from t_avgpv_numwhere dateStr between #{0} and #{1} order by dateStr asc;</select></mapper>

（3）实现Service层

AvgPvService.java

package cn.itcast.service;public interface AvgPvService {//根据日期查询数据public String getAvgPvNumByDates(String startDate, String endDate);}

AvgPvServiceImpl.java

package cn.itcast.service.impl;import java.util.List;import org.springframework.beans.factory.annotation.Autowired;import org.springframework.stereotype.Service;import com.fasterxml.jackson.core.JsonProcessingException;import com.fasterxml.jackson.databind.ObjectMapper;import cn.itcast.mapper.TAvgpvNumMapper;import cn.itcast.pojo.AvgToPageBean;import cn.itcast.pojo.TAvgpvNum;import cn.itcast.service.AvgPvService;@Servicepublic class AvgPvServiceImpl implements AvgPvService {@Autowiredprivate TAvgpvNumMapper mapper;@Overridepublic String getAvgPvNumByDates(String startDate, String endDate) {//调用查询方法List<TAvgpvNum> lists = mapper.selectByDate(startDate, endDate);// 数组大小int size = 7;//保存日期数据String[] dates = new String[size];//保存人均浏览页面数据double[] datas = new double[size];int i = 0;for (TAvgpvNum tAvgpvNum : lists) {dates[i] = tAvgpvNum.getDatestr();datas[i] = tAvgpvNum.getAvgpvnum().doubleValue();i++;}//定义AvgToPageBean对象，用于前台页面展示AvgToPageBean bean = new AvgToPageBean();bean.setDates(dates);bean.setData(datas);//Jackson提供的类，用于把对象转换成Json字符串ObjectMapper om = new ObjectMapper();String beanJson = null;try {beanJson = om.writeValueAsString(bean);} catch (JsonProcessingException e) {e.printStackTrace();}//返回Json格式的对象return beanJson;}}

（4）实现Controller层

IndexController.java

package cn.itcast.controller;import org.springframework.beans.factory.annotation.Autowired;import org.springframework.stereotype.Controller;import org.springframework.web.bind.annotation.RequestMapping;import org.springframework.web.bind.annotation.ResponseBody;import cn.itcast.service.AvgPvService;@Controllerpublic class IndexController {@Autowiredprivate AvgPvService pvService;@RequestMapping("/index")public String showIndex() {return "index";}@RequestMapping(value = "/avgPvNum", produces = "application/json;charset=UTF-8")@ResponseBodypublic String getChart() {System.out.println("获取平均pv数据..");String data = pvService.getAvgPvNumByDates("-09-18", "-09-24");return data;}}

（5）实现页面功能

index.jsp

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</a></li></ul></li></ul></nav><div class="top-nav "><ul class="nav pull-right top-menu"><li><input type="text" class="form-control search"placeholder="Search"></li><li class="dropdown"><a data-toggle="dropdown"class="dropdown-toggle" href="#"> <img alt=""src="img/avatar1_small.jpg"> <span class="username">ADMIN BLACK </span> <b class="caret"> </b></a><ul class="dropdown-menu extended logout"><li class="log-arrow-up"></li><li><a href="#"> <i class=" fa fa-suitcase"> </i>Profile</a></li><li><a href="#"> <i class="fa fa-cog"> </i> Settings</a></li><li><a href="#"> <i class="fa fa-bell-o"> </i>Notification</a></li><li><a href="login.html"> <i class="fa fa-key"> </i> LogOut</a></li></ul></li></ul></div></header><aside><div id="sidebar" class="nav-collapse"><ul class="sidebar-menu" id="nav-accordion"><li><a href="index.html" class="active"> <iclass="fa fa-dashboard"> </i> <span> 流量概况 </span></a></li><li class="sub-menu"><a href="javascript:;"> <iclass="fa fa-book"> </i> <span> 流量分析 </span></a><ul class="sub"><li><a href="flow-trend.html"> 趋势分析 </a></li><li><a href="flow-contract.html"> 对比分析 </a></li><li><a href="flow-online.html"> 当前在线 </a></li><li><a href="flow-detail.html"> 访问明细 </a></li></ul></li><li class="sub-menu"><a href="javascript:;"> <iclass="fa fa-th"> </i> <span> 来源分析 </span></a><ul class="sub"><li><a href="#"> 来源分类 </a></li><li><a href="#"> 搜索引擎 </a></li><li><a href="#"> 搜索词 </a></li><li><a href="#"> 来路域名 </a></li><li><a href="#"> 来路页面 </a></li></ul></li><li class="sub-menu"><a href="javascript:;"> <iclass="fa fa-book"> </i> <span> 受访分析 </span></a><ul class="sub"><li><a href="#"> 受访分析 </a></li><li><a href="#"> 受访域名 </a></li><li><a href="#"> 受访页面 </a></li><li><a href="#"> 受访升降榜 </a></li><li><a href="#"> 热点图 </a></li></ul></li><li class="sub-menu"><a href="javascript:;"> <iclass="fa fa-th"> </i> <span> 访客分析 </span></a><ul class="sub"><li><a href="basic_table.html"> 地区/运营商 </a></li><li><a href="responsive_table.html">终端详情 </a></li><li><a href="dynamic_table.html"> 新老访客</a></li><li><a href="advanced_table.html"> 忠诚度 </a></li><li><a href="editable_table.html"> 活跃度 </a></li></ul></li></ul></div></aside><section id="main-content"><section class="wrapper"><div class="row"><div class="col-lg-12 col-sm-12"><section class="panel"><div class="panel-body"><div><span><h3>流量信息概况</h3></span></div><div id="trendtable" style="width: 90%;"><table id='pv_table' class="table table-bordered" margin=auto><thead style='font-weight: bold'><tr><td>日期</td><td>浏览次数（PV）</td><td>独立访客(UV)</td><td>IP</td><td>新独立访客</td><td>访问次数</td></tr></thead><tbody><tr><td>1001</td><td>4702</td><td>3096</td><td>2880</td><td>2506</td><td>3773</td></tr><tr><td>1002</td><td>7528</td><td>4860</td><td>4435</td><td>4209</td><td>5975</td></tr><tr><td>1003</td><td>7286</td><td>4741</td><td>4409</td><td>4026</td><td>5817</td></tr></tbody></table></div></div></section></div></div><div class="row"><div class="col-lg-6 col-sm-6"><section class="panel"><div class="panel-body"><div id="main1" style="width: 100%; height: 400px;"></div><script type="text/javascript">$(document).ready(function() {var myChart = echarts.init(document.getElementById('main1'));// 显示标题，图例和空的坐标轴myChart.setOption({title : {text : '最近7天日平均PV量',subtext : '动态数据'},tooltip : {},legend : {data : [ '日平均PV量' ]},xAxis : {data : []},yAxis : {},series : [ {name : '日平均PV量',type : 'bar',data : []} ]});//loading 动画myChart.showLoading();// 异步加载数据$.get('http://localhost:8080/avgPvNum').done(function(data) {//填入数据myChart.setOption({xAxis : {data : data.dates},series : [ {// 根据名字对应到相应的系列name : 'PV量',data : data.data} ]});//数据加载完成后再调用 hideLoading 方法隐藏加载动画myChart.hideLoading();});});</script></div></section></div><div class="col-lg-6 col-sm-6"><section class="panel"><div class="panel-body"><div id="main2" style="width: 600px; height: 400px;"align="center"></div><script type="text/javascript">// 基于准备好的dom，初始化echarts实例var myChart = echarts.init(document.getElementById('main2'));myChart.setOption({series : [ {name : '访问来源',type : 'pie',radius : '55%',data : [ {value : 235,name : '视频广告'}, {value : 274,name : '联盟广告'}, {value : 310,name : '邮件营销'}, {value : 335,name : '直接访问'}, {value : 400,name : '搜索引擎'} ]} ],itemStyle : {normal : {// 阴影的大小shadowBlur : 200,// 阴影水平方向上的偏移shadowOffsetX : 0,// 阴影垂直方向上的偏移shadowOffsetY : 0,// 阴影颜色shadowColor : 'rgba(0, 0, 0, 0.5)'}}})</script></div></section></div></div><div class="row"><div class="col-lg-12 col-sm-12"><section class="panel"><div class="panel-body"><div id="main3" style="width: 100%; height: 500px;"></div><script type="text/javascript">// 基于准备好的dom，初始化echarts实例var myChart3 = echarts.init(document.getElementById('main3'));option = {title : {text : '访客来源地区分布图',subtext : '模拟数据',x : 'center'},tooltip : {trigger : 'item'},legend : {orient : 'vertical',x : 'left',data : [ '访客UV' ]},dataRange : {min : 0,max : 2500,x : 'left',y : 'bottom',text : [ '高', '低' ], // 文本，默认为数值文本calculable : true},toolbox : {show : true,orient : 'vertical',x : 'right',y : 'center',feature : {mark : {show : true},dataView : {show : true,readOnly : false},restore : {show : true},saveAsImage : {show : true}}},roamController : {show : true,x : 'right',mapTypeControl : {'china' : true}},series : [{name : '访客UV',type : 'map',mapType : 'china',roam : false,itemStyle : {normal : {label : {show : true}},emphasis : {label : {show : true}}},data : [{name : '北京',value : Math.round(Math.random() * 1000)},{name : '天津',value : Math.round(Math.random() * 1000)},{name : '上海',value : Math.round(Math.random() * 1000)},{name : '重庆',value : Math.round(Math.random() * 1000)},{name : '河北',value : Math.round(Math.random() * 1000)},{name : '河南',value : Math.round(Math.random() * 1000)},{name : '云南',value : Math.round(Math.random() * 1000)},{name : '辽宁',value : Math.round(Math.random() * 1000)},{name : '黑龙江',value : Math.round(Math.random() * 1000)},{name : '湖南',value : Math.round(Math.random() * 1000)},{name : '安徽',value : Math.round(Math.random() * 1000)},{name : '山东',value : Math.round(Math.random() * 1000)},{name : '新疆',value : Math.round(Math.random() * 1000)},{name : '江苏',value : Math.round(Math.random() * 1000)},{name : '浙江',value : Math.round(Math.random() * 1000)},{name : '江西',value : Math.round(Math.random() * 1000)},{name : '湖北',value : Math.round(Math.random() * 1000)},{name : '广西',value : Math.round(Math.random() * 1000)},{name : '甘肃',value : Math.round(Math.random() * 1000)},{name : '山西',value : Math.round(Math.random() * 1000)},{name : '内蒙古',value : Math.round(Math.random() * 1000)},{name : '陕西',value : Math.round(Math.random() * 1000)},{name : '吉林',value : Math.round(Math.random() * 1000)},{name : '福建',value : Math.round(Math.random() * 1000)},{name : '贵州',value : Math.round(Math.random() * 1000)},{name : '广东',value : Math.round(Math.random() * 1000)},{name : '青海',value : Math.round(Math.random() * 1000)},{name : '西藏',value : Math.round(Math.random() * 1000)},{name : '四川',value : Math.round(Math.random() * 1000)},{name : '宁夏',value : Math.round(Math.random() * 1000)},{name : '海南',value : Math.round(Math.random() * 1000)},{name : '台湾',value : Math.round(Math.random() * 1000)},{name : '香港',value : Math.round(Math.random() * 1000)},{name : '澳门',value : Math.round(Math.random() * 1000)} ]},]};myChart3.setOption(option);</script></div></section></div></div><div class="row"><div class="col-lg-12 col-sm-12"><section class="panel"><div class="panel-body"><div id="main4" style="width: 100%; height: 400px;"></div><script type="text/javascript">// 基于准备好的dom，初始化echarts实例var myChart4 = echarts.init(document.getElementById('main4'));// 指定图表的配置项和数据option = {title : {text : '近一周访客数量变化趋势',subtext : '动态数据'},tooltip : {trigger : 'axis'},legend : {data : [ '独立访客', '新独立访客' ]},toolbox : {show : true,feature : {mark : {show : true},dataView : {show : true,readOnly : false},magicType : {show : true,type : [ 'line', 'bar' ]},restore : {show : true},saveAsImage : {show : true}}},calculable : true,xAxis : [ {type : 'category',boundaryGap : false,data : []} ],yAxis : [ {type : 'value',axisLabel : {formatter : '{value} 人'}} ],series : [ {name : '独立访客',type : 'line',data : [],markPoint : {data : [ {type : 'max',name : '最大值'}, {type : 'min',name : '最小值'} ]},markLine : {data : [ {type : 'average',name : '平均值'} ]}}, {name : '新独立访客',type : 'line',data : [],markPoint : {data : [ {type : 'max',name : '最大值'}, {type : 'min',name : '最小值'} ]},markLine : {data : [ {type : 'average',name : '平均值'} ]}} ]};// 使用刚指定的配置项和数据显示图表。myChart4.setOption(option);myChart4.showLoading();// 异步加载数据$.get('http://localhost:8080/flowNum').done(function(data) {// 填入数据myChart4.setOption({xAxis : {data : data.dates},series : [ {name : '独立访客',data : data.uvs}, {name : '新独立访客',data : data.new_uvs} ]});myChart4.hideLoading();});</script></div></section></div></div><div class="row"><div class="col-lg-6"><div class="panel"><div 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3、系统功能模块展示

参考书籍：

《Hadoop大数据技术原理与应用》

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