Hadoop好友推荐系统-数据库过滤数据到HDFS

客官°小女子只卖身不卖艺 2022-06-12 01:49 219阅读 0赞

### 项目总目录：[基于Hadoop的好友推荐系统项目综述][Hadoop] ###

## 数据库过滤数据到HDFS ##

### 1、前端展示 ###

*  jsp页面

<table>
    
                <tr>
                    <td><label for="name">输出路径:</label>
                    </td>
                    <td><input class="easyui-validatebox" type="text"
                        id="preprocess_output_id" data-options="required:true" style="width:300px"
                        value="/user/root/_filter/preparevectors" /></td>
    
                </tr>
                <tr>
                    <td><label for="name">生成文件个数:</label>
                    </td>
                    <td><input class="easyui-validatebox" type="text"
                        id="preprocess_record_id" data-options="required:true" style="width:300px"
                        value="4" /></td>
    
                </tr>
                <tr>
                    <td></td>
                    <td><a id="preprocess_submit_id" href="" class="easyui-linkbutton"
                        data-options="iconCls:'icon-door_in'">预处理</a></td>
                </tr>
    
            </table>
        </div>

*  js逻辑

// ===== 数据预处理 数据库到HDFS
        $('#preprocess_submit_id').bind('click', function(){
        
            var record_=$('#preprocess_record_id').val();
            var output_=$('#preprocess_output_id').val();
            // 弹出进度框
            popupProgressbar('请等待','数据库数据解析并序列化到HFDS中...',1000);
            // ajax 异步提交任务
            callByAJax('cloud/cloud_db2hdfs.action',{record:record_,output:output_});
        });

## 2、后端逻辑 ##

*  action层

/**
         * 数据库数据解析到云平台,为序列文件，是聚类运行的输入文件
         * 
         * [IntWritable,DoubleArrIntWritable]
         */
        public void db2hdfs(){
            List<Object> list = dBService.getTableAllData("UserData");
            Map<String,Object> map = new HashMap<String,Object>();
            if(list.size()==0){
                map.put("flag", "false");
                Utils.write2PrintWriter(JSON.toJSONString(map));
                return ;
            }
            try{
                HUtils.db2hdfs(list,output,Integer.parseInt(record));//解析入库
            }catch(Exception e){
                map.put("flag", "false");
                map.put("msg", e.getMessage());
                Utils.write2PrintWriter(JSON.toJSONString(map));
                return ;
            }
            map.put("flag", "true");
            Utils.write2PrintWriter(JSON.toJSONString(map));
            return ;
        }

其中HUtils.db2hdfs的定义如下：

/**
         * List  解析入HDFS
         * 
         * @param list
         * @param fileNums 
         * @throws IOException
         */
        public static void db2hdfs(List<Object> list,String url, int fileNums) throws IOException {
            if(fileNums<=0||fileNums>9){
                fileNums=HUtils.FILTER_PREPAREVECTORS_FILES;
            }
            int everyFileNum=(int)Math.ceil((double)list.size()/fileNums);//根据输入记录数和输出文件数计算每个文件存储的记录数
            Path path=null;
            int start=0;
            int end=start+everyFileNum;
            for(int i=0;i<fileNums;i++){
                // 如果url为空，那么使用默认的即可，否则使用提供的路径
                path= new Path(url==null?HUtils.FILTER_PREPAREVECTORS:url+"/part-r-0000"+i);//指定文件输出目录和文件名
                if(end>list.size()){
                    end=list.size();
                }
                try{
                    db2hdfs(list.subList(start, end),path);
                    start=end;
                    end+=everyFileNum;
                }catch(IOException e){
                    throw e;
                }
            }
    
            Utils.simpleLog("db2HDFS 全部解析上传完成！");
        }
    
        private static boolean db2hdfs(List<Object> list, Path path) throws IOException {
            boolean flag =false;
            int recordNum=0;
            SequenceFile.Writer writer = null;
            Configuration conf = getConf();
            try {
                Option optPath = SequenceFile.Writer.file(path);
                Option optKey = SequenceFile.Writer
                        .keyClass(IntWritable.class);
                Option optVal = SequenceFile.Writer.valueClass(DoubleArrIntWritable.class);
                writer = SequenceFile.createWriter(conf, optPath, optKey, optVal);
                DoubleArrIntWritable dVal = new DoubleArrIntWritable();
                IntWritable dKey = new IntWritable();
                for (Object user : list) {
                    if(!checkUser(user)){
                        continue; // 不符合规则 
                    }
                    dVal.setValue(getDoubleArr(user),-1);
                    dKey.set(getIntVal(user));
                    writer.append(dKey, dVal);// 用户id,<type,用户的有效向量 >// 后面执行分类的时候需要统一格式，所以这里需要反过来
                    recordNum++;
                }
            } catch (IOException e) {
                Utils.simpleLog("db2HDFS失败,+hdfs file:"+path.toString());
                e.printStackTrace();
                flag =false;
                throw e;
            } finally {
                IOUtils.closeStream(writer);
            }
            flag=true;
            Utils.simpleLog("db2HDFS 完成,hdfs file:"+path.toString()+",records:"+recordNum);
            return flag;
        }
    
        /**
         * 检查用户是否符合规则
         * 规则 ：reputation>15,upVotes>0,downVotes>0,views>0的用户
         * @param user
         * @return
         */
        private static boolean checkUser(Object user) {
            UserData ud = (UserData)user;
            if(ud.getReputation()<=15) return false;
            if(ud.getUpVotes()<=0) return false;
            if(ud.getDownVotes()<=0) return false;
            if(ud.getViews()<=0) return false;
            return true;
        }

*  service层

/**
         * 获得tableName的所有数据并返回
         * 
         * @param tableName
         * @return
         */
        public List<Object> getTableAllData(String tableName) {
            String hql = "from " + tableName + " ";
            List<Object> list = null;
            try {
                list = baseDao.find(hql);
            } catch (Exception e) {
                e.printStackTrace();
            }
            return list;
        }

## 二、程序运行截图 ##

### 1、前端 ###

![这里写图片描述][20170712154337943]

### 2、后台 ###

![这里写图片描述][20170712154421855]

### 3、查看HDFS目录 ###

![这里写图片描述][20170712154559921]

[Hadoop]: http://blog.csdn.net/xiaokang123456kao/article/details/75006624
[20170712154337943]: /images/20220612/86c4623fee714c65a31967239566bab0.png
[20170712154421855]: /images/20220612/b7353cd104f74e50bff3d7d24434c23f.png
[20170712154559921]: /images/20220612/2c3f1a976fb24a2e864401b153d62c6a.png