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用户Session聚合统计功能完成

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用户Session聚合统计功能完成，使用自定义Accumulator，重构部分代码
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oeljeklaus-you 7 years ago
parent 0bef49fb85
commit 46490e6d66
46 changed files with 1922 additions and 241 deletions
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.idea/libraries/Maven__joda_time_joda_time_2_9.xml → .idea/libraries/Maven__joda_time_joda_time_2_5.xml
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.idea/libraries/Maven__net_razorvine_pyrolite_4_9.xml → .idea/libraries/Maven__net_razorvine_pyrolite_4_4.xml
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.idea/libraries/Maven__net_sf_py4j_py4j_0_9.xml
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.idea/libraries/Maven__org_apache_curator_curator_client_2_6_0.xml → .idea/libraries/Maven__org_apache_curator_curator_client_2_1_0_incubating.xml
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.idea/libraries/Maven__org_apache_spark_spark_catalyst_2_10_1_6_1.xml → .idea/libraries/Maven__org_apache_spark_spark_catalyst_2_10_1_5_1.xml
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.idea/libraries/Maven__org_apache_spark_spark_core_2_10_1_6_1.xml → .idea/libraries/Maven__org_apache_spark_spark_core_2_10_1_5_1.xml
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.idea/libraries/Maven__org_apache_spark_spark_hive_2_10_1_6_1.xml → .idea/libraries/Maven__org_apache_spark_spark_hive_2_10_1_5_1.xml
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.idea/libraries/Maven__org_apache_spark_spark_launcher_2_10_1_6_1.xml → .idea/libraries/Maven__org_apache_spark_spark_launcher_2_10_1_5_1.xml
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.idea/libraries/Maven__org_apache_spark_spark_network_common_2_10_1_6_1.xml → .idea/libraries/Maven__org_apache_spark_spark_network_common_2_10_1_5_1.xml
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.idea/libraries/Maven__org_apache_spark_spark_network_shuffle_2_10_1_6_1.xml → .idea/libraries/Maven__org_apache_spark_spark_network_shuffle_2_10_1_5_1.xml
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.idea/libraries/Maven__org_apache_spark_spark_sql_2_10_1_6_1.xml → .idea/libraries/Maven__org_apache_spark_spark_sql_2_10_1_5_1.xml
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8
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8
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8
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Unescape View File

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13
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8
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711
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3
README.md
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@ -327,3 +327,6 @@ task_param：最最重要，用来使用JSON的格式，来封装用户提交的
完成了数据调研、需求分析、技术方案设计、数据设计以后，正式进入编码实现和功能测试阶段。最后才是性能调优阶段。
## 用户访问Session的比较高端技术
### 自定义Accumulator
&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;使用自定义Accumulator降低维护成本，一个就可以搞定很多业务需求

47
UserActionAnalyzePlatform.iml
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@ -12,7 +12,7 @@
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@ -23,12 +23,10 @@
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@ -44,9 +42,9 @@
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@ -76,17 +74,17 @@
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@ -95,11 +93,8 @@
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@ -155,7 +152,6 @@
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8
pom.xml
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@ -16,22 +16,22 @@
<dependency>
<groupId>org.apache.spark</groupId>
<artifactId>spark-core_2.10</artifactId>
<version>1.6.1</version>
<version>1.5.1</version>
</dependency>
<dependency>
<groupId>org.apache.spark</groupId>
<artifactId>spark-sql_2.10</artifactId>
<version>1.6.1</version>
<version>1.5.1</version>
</dependency>
<dependency>
<groupId>org.apache.spark</groupId>
<artifactId>spark-hive_2.10</artifactId>
<version>1.6.1</version>
<version>1.5.1</version>
</dependency>
<dependency>
<groupId>org.apache.spark</groupId>
<artifactId>spark-streaming_2.10</artifactId>
<version>1.6.1</version>
<version>1.5.1</version>
</dependency>
<dependency>
<groupId>org.apache.hadoop</groupId>

37
src/main/java/cn/edu/hust/conf/ConfigurationManager.java
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@ -35,4 +35,41 @@ public class ConfigurationManager {
{
return prop.getProperty(key);
}
/**
* 获取整数变量
* @param key
* @return
*/
public static Integer getInteger(String key)
{
String value=getProperty(key);
try
{
Integer result=Integer.valueOf(value);
return result;
}
catch (Exception e)
{
e.printStackTrace();
}
return 0;
}
/**
* 获取布尔型
* @param key
* @return
*/
public static Boolean getBoolean(String key)
{
String value=getProperty(key);
if("false".equals(value))
{
return false;
}
return true;
}
}

59
src/main/java/cn/edu/hust/constant/Constants.java
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@ -0,0 +1,59 @@
package cn.edu.hust.constant;
public class Constants {
/**
* 项目配置常量
*/
public static final String JDBC_DRIVER="jdbc.driver";
public static final String JDBC_URL="jdbc.url";
public static final String JDBC_USERNAME="jdbc.username";
public static final String JDBC_PSSWORD="jdbc.password";
public static final String JDBC_ACTIVE="jdbc.active";
/**
* Spark作业相关常量
*/
public static final String APP_NAME_SESSION="UserVisitAnalyze";
public static final String SPARK_LOCAL="spark_local";
public static final String FIELD_SESSIONID="sessionId";
public static final String FIELD_SERACH_KEYWORDS="searchKeywords";
public static final String FIELD_CLICK_CATEGORYIDS="clickCategoryIds";
public static final String FIELD_AGE="age";
public static final String FIELD_CITY="city";
public static final String FIELD_SEX="sex";
public static final String FIELD_PROFESSIONAL="professional";
public static final String FIELD_VISIT_LENGTH="visitLength";
public static final String FIELD_STEP_LENGTH="stepLength";
/**
* Spark任务相关厂常量
*/
public static final String PARAM_STARTTIME ="startDate";
public static final String PARAM_ENDTIME ="endDate";
public static final String PARAM_STARTAGE ="startAge";
public static final String PARAM_ENDAGE ="endAge";
public static final String PARAM_PROFESSONALS ="professionals";
public static final String PARAM_CIYTIES ="cities";
public static final String PARAM_SEX ="sex";
public static final String PARAM_SERACH_KEYWORDS="searchKeywords";
public static final String PARAM_CLICK_CATEGORYIDS="clickCategoryIds";
public static final String SESSION_COUNT = "session_count";
public static final String TIME_PERIOD_1s_3s = "1s_3s";
public static final String TIME_PERIOD_4s_6s = "4s_6s";
public static final String TIME_PERIOD_7s_9s = "7s_9s";
public static final String TIME_PERIOD_10s_30s = "10s_30s";
public static final String TIME_PERIOD_30s_60s = "30s_60s";
public static final String TIME_PERIOD_1m_3m = "1m_3m";
public static final String TIME_PERIOD_3m_10m = "3m_10m";
public static final String TIME_PERIOD_10m_30m = "10m_30m";
public static final String TIME_PERIOD_30m = "30m";
public static final String STEP_PERIOD_1_3 = "1_3";
public static final String STEP_PERIOD_4_6 = "4_6";
public static final String STEP_PERIOD_7_9 = "7_9";
public static final String STEP_PERIOD_10_30 = "10_30";
public static final String STEP_PERIOD_30_60 = "30_60";
public static final String STEP_PERIOD_60 = "60";
}

7
src/main/java/cn/edu/hust/dao/TaskDao.java
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@ -0,0 +1,7 @@
package cn.edu.hust.dao;
import cn.edu.hust.domain.Task;
public interface TaskDao {
Task findTaskById(Long id);
}

15
src/main/java/cn/edu/hust/dao/factory/DaoFactory.java
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@ -0,0 +1,15 @@
package cn.edu.hust.dao.factory;
import cn.edu.hust.dao.TaskDao;
import cn.edu.hust.dao.impl.TaskDaoImpl;
public class DaoFactory {
/**
* 使用工厂模式
* @return
*/
public static TaskDao getTaskDao()
{
return new TaskDaoImpl();
}
}

38
src/main/java/cn/edu/hust/dao/impl/TaskDaoImpl.java
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@ -0,0 +1,38 @@
package cn.edu.hust.dao.impl;
import cn.edu.hust.dao.TaskDao;
import cn.edu.hust.domain.Task;
import cn.edu.hust.jdbc.JDBCHelper;
import java.sql.ResultSet;
import java.sql.SQLException;
public class TaskDaoImpl implements TaskDao{
@Override
public Task findTaskById(Long id) {
String sql="select * from task where task_id=?";
final Task task=new Task();
JDBCHelper.getInstance().excuteQuery(sql, new Object[]{id}, new JDBCHelper.QueryCallBack() {
@Override
public void process(ResultSet rs) {
try {
if(rs.next())
{
Long id=rs.getLong(1);
String taskName=rs.getString(2);
String createTime=rs.getString(3);
String startTime=rs.getString(4);
String finishTime=rs.getString(5);
String taskType=rs.getString(6);
String taskStatus=rs.getString(7);
String taskParam=rs.getString(8);
task.set(id,taskName,createTime,startTime,finishTime,taskType,taskStatus,taskParam);
}
} catch (SQLException e) {
e.printStackTrace();
}
}
});
return task;
}
}

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src/main/java/cn/edu/hust/demo/Singleton.java
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package cn.edu.hust.demo;
/**
* 单例模式几种实现方式
*/
public class Singleton {
/**
* 饿汉模式实现单例模式，线程安全
*/
/**
private static Singleton instance=new Singleton();
private Singleton()
{
}
public static Singleton getInstance()
{
return instance;
}*/
/**
* 懒汉模式实现单例模式 线程不安全的写法
private static Singleton instance=null;
private Singleton()
{
}
public static Singleton getInstance()
{
if(instance==null) instance=new Singleton();
return instance;
}*/
/**
* 懒汉模式线程安全的写法
*/
private static Singleton instance=null;
private Singleton()
{
}
public static Singleton getInstance()
{
if(instance==null)
{
synchronized (Singleton.class)
{
if(instance==null)
{
instance=new Singleton();
}
}
}
return instance;
}
}

92
src/main/java/cn/edu/hust/domain/Task.java
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package cn.edu.hust.domain;
import java.io.Serializable;
public class Task implements Serializable{
private Long taskId;
private String taskName;
private String createTime;
private String startTime;
private String finishTime;
private String taskType;
private String taskStatus;
private String taskParam;
public Task() {
}
public void set(Long taskId, String taskName, String createTime, String startTime, String finishTime, String taskType, String taskStatus, String taskParam) {
this.taskId = taskId;
this.taskName = taskName;
this.createTime = createTime;
this.startTime = startTime;
this.finishTime = finishTime;
this.taskType = taskType;
this.taskStatus = taskStatus;
this.taskParam = taskParam;
}
public Long getTaskId() {
return taskId;
}
public void setTaskId(Long taskId) {
this.taskId = taskId;
}
public String getTaskName() {
return taskName;
}
public void setTaskName(String taskName) {
this.taskName = taskName;
}
public String getCreateTime() {
return createTime;
}
public void setCreateTime(String createTime) {
this.createTime = createTime;
}
public String getStartTime() {
return startTime;
}
public void setStartTime(String startTime) {
this.startTime = startTime;
}
public String getFinishTime() {
return finishTime;
}
public void setFinishTime(String finishTime) {
this.finishTime = finishTime;
}
public String getTaskType() {
return taskType;
}
public void setTaskType(String taskType) {
this.taskType = taskType;
}
public String getTaskStatus() {
return taskStatus;
}
public void setTaskStatus(String taskStatus) {
this.taskStatus = taskStatus;
}
public String getTaskParam() {
return taskParam;
}
public void setTaskParam(String taskParam) {
this.taskParam = taskParam;
}
}

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src/main/java/cn/edu/hust/jdbc/JDBCHelper.java
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package cn.edu.hust.jdbc;
import cn.edu.hust.conf.ConfigurationManager;
import cn.edu.hust.constant.Constants;
import java.sql.*;
import java.util.List;
import java.util.concurrent.ArrayBlockingQueue;
import java.util.concurrent.LinkedBlockingQueue;
public class JDBCHelper {
private static JDBCHelper instance=new JDBCHelper();
//使用阻塞队列
private LinkedBlockingQueue<Connection> queue=new LinkedBlockingQueue<Connection>();
static{
try {
Class.forName(ConfigurationManager.getProperty(Constants.JDBC_DRIVER));
}
catch (Exception e)
{
e.printStackTrace();
}
}
/**
* 在构造函数创建数据库连接池
* 结合单例模式，确保数据库连接池单例
*/
private JDBCHelper(){
int dataSourceSize=ConfigurationManager.getInteger(Constants.JDBC_ACTIVE);
String url=ConfigurationManager.getProperty(Constants.JDBC_URL);
String username=ConfigurationManager.getProperty(Constants.JDBC_USERNAME);
String passward=ConfigurationManager.getProperty(Constants.JDBC_PSSWORD);
try
{
for(int i=0;i<dataSourceSize;i++)
{
Connection connection=DriverManager.getConnection(url,username,passward);
queue.put(connection);
}
}
catch (Exception e)
{
e.printStackTrace();
}
};
public static JDBCHelper getInstance()
{
return instance;
}
/**
* 获取数据库连接
* 使用阻塞队列
* @return
*/
public Connection getConnection()
{
try {
return queue.take();
} catch (InterruptedException e) {
e.printStackTrace();
}
return null;
}
/**
* 更新数据
* @param sql
* @param params
* @return
*/
public int excuteUpdate(String sql,Object[] params)
{
int re=0;
Connection conn=null;
PreparedStatement statement=null;
try
{
conn=getConnection();
statement=conn.prepareStatement(sql);
for (int i = 0; i < params.length; i++) {
statement.setObject(i+1,params[i]);
}
re=statement.executeUpdate();
return re;
}
catch (Exception e)
{
e.printStackTrace();
}
finally {
if(conn!=null)
{
try {
queue.put(conn);
} catch (InterruptedException e) {
e.printStackTrace();
}
}
}
return re;
}
public static interface QueryCallBack
{
void process(ResultSet rs);
}
/**
* 查询数据的处理
* 使用接口回掉，根据用户的自定义接口来进行处理
* @param sql
* @param params
* @param queryCallBack
*/
public void excuteQuery(String sql,Object[] params,QueryCallBack queryCallBack)
{
Connection conn=null;
PreparedStatement statement=null;
try
{
conn=getConnection();
statement=conn.prepareStatement(sql);
for (int i = 0; i < params.length; i++) {
statement.setObject(i+1,params[i]);
}
ResultSet rs=statement.executeQuery();
queryCallBack.process(rs);
}catch (Exception e)
{
}
finally {
if(conn!=null)
{
try {
queue.put(conn);
} catch (InterruptedException e) {
e.printStackTrace();
}
}
}
}
/**
* 批量执行sql语句
* @param sql
* @param params
* @return
*/
public int[] excuteBatch(String sql,List<Object[]> params)
{
Connection connection=null;
PreparedStatement statement=null;
int[] res=null;
try
{
connection=getConnection();
statement=connection.prepareStatement(sql);
//1.取消自动提交
connection.setAutoCommit(false);
//2.设置参数
for (Object[] param:
params) {
for (int i = 0; i < param.length; i++) {
statement.setObject(i+1,param[i]);
}
statement.addBatch();
}
//3.批量执行
res=statement.executeBatch();
//4.最后一步提交
connection.commit();
return res;
} catch (SQLException e) {
e.printStackTrace();
}
finally {
if(connection!=null)
{
try {
queue.put(connection);
} catch (InterruptedException e) {
e.printStackTrace();
}
}
}
return res;
}
}

147
src/main/java/cn/edu/hust/mockData/MockData.java
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package cn.edu.hust.mockData;
import java.util.ArrayList;
import java.util.Arrays;
import java.util.List;
import java.util.Random;
import java.util.UUID;
import cn.edu.hust.util.DateUtils;
import cn.edu.hust.util.StringUtils;
import org.apache.spark.api.java.JavaRDD;
import org.apache.spark.api.java.JavaSparkContext;
import org.apache.spark.sql.DataFrame;
import org.apache.spark.sql.Row;
import org.apache.spark.sql.RowFactory;
import org.apache.spark.sql.SQLContext;
import org.apache.spark.sql.types.DataTypes;
import org.apache.spark.sql.types.StructType;
/**
* 模拟数据程序
* @author Administrator
*
*/
public class MockData {
/**
* 弄你数据
* @param sc
* @param sqlContext
*/
public static void mock(JavaSparkContext sc,
SQLContext sqlContext) {
List<Row> rows = new ArrayList<Row>();
String[] searchKeywords = new String[] {"火锅", "蛋糕", "重庆辣子鸡", "重庆小面",
"呷哺呷哺", "新辣道鱼火锅", "国贸大厦", "太古商场", "日本料理", "温泉"};
String date = DateUtils.getTodayDate();
String[] actions = new String[]{"search", "click", "order", "pay"};
Random random = new Random();
for(int i = 0; i < 100; i++) {
long userid = random.nextInt(100);
for(int j = 0; j < 10; j++) {
String sessionid = UUID.randomUUID().toString().replace("-", "");
String baseActionTime = date + " " + random.nextInt(23);
for(int k = 0; k < random.nextInt(100); k++) {
long pageid = random.nextInt(10);
String actionTime = baseActionTime + ":" + StringUtils.fulfuill(String.valueOf(random.nextInt(59))) + ":" + StringUtils.fulfuill(String.valueOf(random.nextInt(59)));
String searchKeyword = null;
Long clickCategoryId = null;
Long clickProductId = null;
String orderCategoryIds = null;
String orderProductIds = null;
String payCategoryIds = null;
String payProductIds = null;
String action = actions[random.nextInt(4)];
if("search".equals(action)) {
searchKeyword = searchKeywords[random.nextInt(10)];
} else if("click".equals(action)) {
clickCategoryId = Long.valueOf(String.valueOf(random.nextInt(100)));
clickProductId = Long.valueOf(String.valueOf(random.nextInt(100)));
} else if("order".equals(action)) {
orderCategoryIds = String.valueOf(random.nextInt(100));
orderProductIds = String.valueOf(random.nextInt(100));
} else if("pay".equals(action)) {
payCategoryIds = String.valueOf(random.nextInt(100));
payProductIds = String.valueOf(random.nextInt(100));
}
Row row = RowFactory.create(date, userid, sessionid,
pageid, actionTime, searchKeyword,
clickCategoryId, clickProductId,
orderCategoryIds, orderProductIds,
payCategoryIds, payProductIds);
rows.add(row);
}
}
}
JavaRDD<Row> rowsRDD = sc.parallelize(rows);
StructType schema = DataTypes.createStructType(Arrays.asList(
DataTypes.createStructField("date", DataTypes.StringType, true),
DataTypes.createStructField("user_id", DataTypes.LongType, true),
DataTypes.createStructField("session_id", DataTypes.StringType, true),
DataTypes.createStructField("page_id", DataTypes.LongType, true),
DataTypes.createStructField("action_time", DataTypes.StringType, true),
DataTypes.createStructField("search_keyword", DataTypes.StringType, true),
DataTypes.createStructField("click_category_id", DataTypes.LongType, true),
DataTypes.createStructField("click_product_id", DataTypes.LongType, true),
DataTypes.createStructField("order_category_ids", DataTypes.StringType, true),
DataTypes.createStructField("order_product_ids", DataTypes.StringType, true),
DataTypes.createStructField("pay_category_ids", DataTypes.StringType, true),
DataTypes.createStructField("pay_product_ids", DataTypes.StringType, true)));
DataFrame df = sqlContext.createDataFrame(rowsRDD, schema);
df.registerTempTable("user_visit_action");
for(Row _row : df.take(1)) {
System.out.println(_row);
}
/**
* ==================================================================
*/
rows.clear();
String[] sexes = new String[]{"male", "female"};
for(int i = 0; i < 100; i ++) {
long userid = i;
String username = "user" + i;
String name = "name" + i;
int age = random.nextInt(60);
String professional = "professional" + random.nextInt(100);
String city = "city" + random.nextInt(100);
String sex = sexes[random.nextInt(2)];
Row row = RowFactory.create(userid, username, name, age,
professional, city, sex);
rows.add(row);
}
rowsRDD = sc.parallelize(rows);
StructType schema2 = DataTypes.createStructType(Arrays.asList(
DataTypes.createStructField("user_id", DataTypes.LongType, true),
DataTypes.createStructField("username", DataTypes.StringType, true),
DataTypes.createStructField("name", DataTypes.StringType, true),
DataTypes.createStructField("age", DataTypes.IntegerType, true),
DataTypes.createStructField("professional", DataTypes.StringType, true),
DataTypes.createStructField("city", DataTypes.StringType, true),
DataTypes.createStructField("sex", DataTypes.StringType, true)));
DataFrame df2 = sqlContext.createDataFrame(rowsRDD, schema2);
for(Row _row : df2.take(1)) {
System.out.println(_row);
}
df2.registerTempTable("user_info");
}
}

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src/main/java/cn/edu/hust/session/SessionAggrStatAccumulator.java
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package cn.edu.hust.session;
import cn.edu.hust.constant.Constants;
import cn.edu.hust.util.StringUtils;
import org.apache.spark.AccumulatorParam;
public class SessionAggrStatAccumulator implements AccumulatorParam<String>{
@Override
public String addAccumulator(String s, String t1) {
return add(s,t1);
}
@Override
public String addInPlace(String s, String r1) {
return add(s,r1);
}
//主要用于数据的初始化，这里主要返回一个值就是所有范围区间得的数量
@Override
public String zero(String s) {
return Constants.SESSION_COUNT + "=0|"
+ Constants.TIME_PERIOD_1s_3s + "=0|"
+ Constants.TIME_PERIOD_4s_6s + "=0|"
+ Constants.TIME_PERIOD_7s_9s + "=0|"
+ Constants.TIME_PERIOD_10s_30s + "=0|"
+ Constants.TIME_PERIOD_30s_60s + "=0|"
+ Constants.TIME_PERIOD_1m_3m + "=0|"
+ Constants.TIME_PERIOD_3m_10m + "=0|"
+ Constants.TIME_PERIOD_10m_30m + "=0|"
+ Constants.TIME_PERIOD_30m + "=0|"
+ Constants.STEP_PERIOD_1_3 + "=0|"
+ Constants.STEP_PERIOD_4_6 + "=0|"
+ Constants.STEP_PERIOD_7_9 + "=0|"
+ Constants.STEP_PERIOD_10_30 + "=0|"
+ Constants.STEP_PERIOD_30_60 + "=0|"
+ Constants.STEP_PERIOD_60 + "=0";
}
private String add(String v1,String v2)
{
if(StringUtils.isEmpty(v1)) return v2;
String value=StringUtils.getFieldFromConcatString(v1,"\\|",v2);
if(value!=null)
{
int newValue=Integer.valueOf(value)+1;
StringUtils.setFieldInConcatString(v1,"\\|",v2,String.valueOf(newValue));
}
return v1;
}
}

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src/main/java/cn/edu/hust/session/UserVisitAnalyze.java
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package cn.edu.hust.session;
import cn.edu.hust.conf.ConfigurationManager;
import cn.edu.hust.constant.Constants;
import cn.edu.hust.dao.TaskDao;
import cn.edu.hust.dao.factory.DaoFactory;
import cn.edu.hust.domain.Task;
import cn.edu.hust.mockData.MockData;
import cn.edu.hust.util.DateUtils;
import cn.edu.hust.util.ParamUtils;
import cn.edu.hust.util.StringUtils;
import cn.edu.hust.util.ValidUtils;
import com.alibaba.fastjson.JSONObject;
import org.apache.spark.Accumulator;
import org.apache.spark.AccumulatorParam;
import org.apache.spark.SparkConf;
import org.apache.spark.SparkContext;
import org.apache.spark.api.java.JavaPairRDD;
import org.apache.spark.api.java.JavaRDD;
import org.apache.spark.api.java.JavaSparkContext;
import org.apache.spark.api.java.function.Function;
import org.apache.spark.api.java.function.PairFunction;
import org.apache.spark.sql.DataFrame;
import org.apache.spark.sql.Row;
import org.apache.spark.sql.SQLContext;
import org.apache.spark.sql.hive.HiveContext;
import org.joda.time.DateTime;
import scala.Tuple2;
import java.util.Date;
/**
* 用户可以查询的范围包含
* 1。用户的职业
* 2。用户的性别
* 3。用户城市
* 4。用户年龄
* 5。获取搜索词
* 6。获取点击品类
*/
public class UserVisitAnalyze {
public static void main(String[] args)
{
/**
* 构建spark上下文
*/
SparkConf conf=new SparkConf().setAppName(Constants.APP_NAME_SESSION).setMaster("local[3]");
JavaSparkContext context=new JavaSparkContext(conf);
SQLContext sc=getSQLContext(context.sc());
//生成模拟数据
mock(context,sc);
//拿到相应的Dao组建
TaskDao dao= DaoFactory.getTaskDao();
//从外部传入的参数获取任务的id
Long taskId=ParamUtils.getTaskIdFromArgs(args);
//从数据库中查询出相应的task
Task task=dao.findTaskById(taskId);
JSONObject jsonObject=JSONObject.parseObject(task.getTaskParam());
//获取指定范围内的Sesssion
JavaRDD<Row> sessionRangeDate=getActionRDD(sc,jsonObject);
//按照Sesson进行聚合
JavaPairRDD<String,String> sesssionAggregateInfoRDD=aggregateBySessionId(sc,sessionRangeDate);
//通过条件对RDD进行筛选
// 重构，同时统计
Accumulator<String> sessionAggrStatAccumulator=context.accumulator("",new SessionAggrStatAccumulator());
JavaPairRDD<String,String> filteredSessionRDD=filterSessionAndAggrStat(sesssionAggregateInfoRDD,jsonObject,sessionAggrStatAccumulator);
//session聚合统计，统计出访问时长和访问步长的各个区间所占的比例
/**
* 重构实现的思路：
* 1。不要去生成任何的新RDD
* 2。不要去单独遍历一遍sesion的数据
* 3。可以在聚合数据的时候可以直接计算session的访问时长和访问步长
* 4。在以前的聚合操作中，可以在以前的基础上进行计算加上自己实现的Accumulator来进行一次性解决
* 开发Spark的经验准则
* 1。尽量少生成RDD
* 2。尽量少对RDD进行蒜子操作，如果可能，尽量在一个算子里面，实现多个需求功能
* 3。尽量少对RDD进行shuffle算子操作，比如groupBykey、reduceBykey、sortByKey
* shuffle操作，会导致大量的磁盘读写，严重降低性能
* 有shuffle的算子，和没有shuffle的算子，甚至性能相差极大
* 有shuffle的算子，很容易造成性能倾斜，一旦数据倾斜，简直就是性能杀手
* 4。无论做什么功能，性能第一
* 在大数据项目中，性能最重要。主要是大数据以及大数据项目的特点，决定了大数据的程序和项目速度，都比较满
* 如果不考虑性能的话，就会导致一个大数据处理程序运行长达数个小时，甚至是数个小时，对用户的体验，简直是
* 一场灾难。
*/
//关闭spark上下文
context.close();
}
/**
* 用于判断是否是生产环境
* @param sc
* @return
*/
public static SQLContext getSQLContext(SparkContext sc)
{
boolean local= ConfigurationManager.getBoolean(Constants.SPARK_LOCAL);
if(local)
{
return new SQLContext(sc);
}
return new HiveContext(sc);
}
private static void mock(JavaSparkContext context,SQLContext sc)
{
boolean local= ConfigurationManager.getBoolean(Constants.SPARK_LOCAL);
if(local)
{
MockData.mock(context,sc);
}
}
/**
* 获取指定日期范围内的数据
* @param sc
* @param taskParam
* @return
*/
private static JavaRDD<Row> getActionRDD(SQLContext sc, JSONObject taskParam)
{
String startTime=ParamUtils.getParam(taskParam,Constants.PARAM_STARTTIME);
String endTime=ParamUtils.getParam(taskParam,Constants.PARAM_ENDTIME);
String sql="select *from user_visit_action where date>='"+startTime+"' and date<='"+endTime+"'";
DataFrame df=sc.sql(sql);
return df.javaRDD();
}
private static JavaPairRDD<String,String> aggregateBySessionId(SQLContext sc, JavaRDD<Row> sessionRangeDate) {
/**
* 先将数据映射成map格式
*/
JavaPairRDD<String,Row> sessionActionPair=sessionRangeDate.mapToPair(new PairFunction<Row, String,Row>() {
@Override
public Tuple2<String, Row> call(Row row) throws Exception {
return new Tuple2<String, Row>(row.getString(2),row);
}
});
/**
* 根据sessionId进行分组
*/
JavaPairRDD<String,Iterable<Row>> sessionActionGrouped=sessionActionPair.groupByKey();
JavaPairRDD<Long,String> sessionPartInfo=sessionActionGrouped.mapToPair(new PairFunction<Tuple2<String, Iterable<Row>>, Long, String>() {
@Override
public Tuple2<Long, String> call(Tuple2<String, Iterable<Row>> stringIterableTuple2) throws Exception {
String sessionId=stringIterableTuple2._1;
Iterable<Row> rows=stringIterableTuple2._2;
StringBuffer searchKeywords=new StringBuffer();
StringBuffer clickCategoryIds=new StringBuffer();
Long userId=null;
Date startTime=null;
Date endTime=null;
int stepLength=0;
for (Row row:rows)
{
if(userId==null)
userId=row.getLong(1);
String searchKeyword=row.getString(5);
Long clickCategoryId=row.getLong(6);
//判断是否需要拼接
if(StringUtils.isNotEmpty(searchKeyword))
{
if(!searchKeywords.toString().contains(searchKeyword))
searchKeywords.append(searchKeyword+",");
}
if(clickCategoryId!=null)
{
if(!clickCategoryId.toString().contains(String.valueOf(clickCategoryId)))
clickCategoryIds.append(String.valueOf(clickCategoryId)+",");
}
//计算session开始时间和结束时间
Date actionTime= DateUtils.parseTime(row.getString(4));
if(startTime==null)
startTime=actionTime;
if(endTime==null)
endTime=null;
if(actionTime.before(startTime))
{
startTime=actionTime;
}
if(actionTime.after(endTime))
{
endTime=actionTime;
}
stepLength++;
}
//访问时长(s)
Long visitLengtth=(endTime.getTime()-startTime.getTime())/1000;
String searchKeywordsInfo=StringUtils.trimComma(searchKeywords.toString());
String clickCategoryIdsInfo=StringUtils.trimComma(clickCategoryIds.toString());
String info=Constants.FIELD_SESSIONID+"="+sessionId+"|"+Constants.FIELD_SERACH_KEYWORDS+"="+searchKeywordsInfo+"|"
+Constants.FIELD_CLICK_CATEGORYIDS+"="+clickCategoryIdsInfo+Constants.FIELD_VISIT_LENGTH+"="+visitLengtth+"|"
+Constants.FIELD_STEP_LENGTH+"="+stepLength;
return new Tuple2<Long, String>(userId,info);
}
});
//查询所有的用户数据
String sql="select * from user_info";
JavaRDD<Row> userInfoRDD=sc.sql(sql).javaRDD();
//将用户信息映射成map
JavaPairRDD<Long,Row> userInfoPariRDD=userInfoRDD.mapToPair(new PairFunction<Row, Long, Row>() {
@Override
public Tuple2<Long, Row> call(Row row) throws Exception {
return new Tuple2<Long, Row>(row.getLong(0),row);
}
});
//将两个信息join在一起
JavaPairRDD<Long,Tuple2<String,Row>> tuple2JavaPairRDD=sessionPartInfo.join(userInfoPariRDD);
/**
* 拿到所需的session
*/
JavaPairRDD<String,String> sessionInfo=tuple2JavaPairRDD.mapToPair(new PairFunction<Tuple2<Long,Tuple2<String,Row>>, String, String>() {
@Override
public Tuple2<String, String> call(Tuple2<Long, Tuple2<String, Row>> longTuple2Tuple2) throws Exception {
String sessionPartInfo=longTuple2Tuple2._2._1;
Row userInfo=longTuple2Tuple2._2._2;
//拿到需要的用户信息
int age=userInfo.getInt(3);
String professional=userInfo.getString(4);
String city=userInfo.getString(5);
String sex=userInfo.getString(6);
//拼接字符串
String fullInfo=sessionPartInfo+"|"+Constants.FIELD_AGE+"="+age+"|"
+Constants.FIELD_PROFESSIONAL+"="+professional+"|"+Constants.FIELD_CITY+"="+city+"|"+Constants.FIELD_SEX+"="+sex;
String session=StringUtils.getFieldFromConcatString(sessionPartInfo,"\\|",Constants.FIELD_SESSIONID);
return new Tuple2<String, String>(session,fullInfo);
}
});
return sessionInfo;
}
/**
* 根据条件进行session的筛选
* @param sessionInfoRDD
* @param taskParam
* @param sessionAggrStatAccumulator
* @return
*/
private static JavaPairRDD<String,String> filterSessionAndAggrStat(JavaPairRDD<String, String> sessionInfoRDD, final JSONObject taskParam, final Accumulator<String> sessionAggrStatAccumulator){
//得到条件
String startAge=ParamUtils.getParam(taskParam,Constants.PARAM_STARTAGE);
String endAge=ParamUtils.getParam(taskParam,Constants.PARAM_ENDAGE);
String professionals=ParamUtils.getParam(taskParam,Constants.PARAM_PROFESSONALS);
String cities=ParamUtils.getParam(taskParam,Constants.PARAM_CIYTIES);
String sex= ParamUtils.getParam(taskParam,Constants.PARAM_SEX);
String keyWords=ParamUtils.getParam(taskParam,Constants.PARAM_SERACH_KEYWORDS);
String categoryIds=ParamUtils.getParam(taskParam,Constants.PARAM_CLICK_CATEGORYIDS);
//拼接时间
String _paramter=(startAge!=null?Constants.PARAM_STARTAGE+"="+startAge+"|":"")+
(endAge!=null?Constants.PARAM_ENDAGE+"="+endAge+"|":"")+(professionals!=null?Constants.PARAM_PROFESSONALS+"="+professionals+"|":"")+
(cities!=null?Constants.PARAM_CIYTIES+"="+cities+"|":"")+(sex!=null?Constants.PARAM_SEX+"="+sex+"|":"")+
(keyWords!=null?Constants.PARAM_SERACH_KEYWORDS+"="+keyWords+"|":"")+(categoryIds!=null?Constants.PARAM_CLICK_CATEGORYIDS+"="+categoryIds+"|":"");
if(_paramter.endsWith("\\|"))
_paramter=_paramter.substring(0,_paramter.length()-1);
final String paramter=_paramter;
JavaPairRDD<String,String> filteredSessionRDD=sessionInfoRDD.filter(new Function<Tuple2<String, String>, Boolean>() {
@Override
public Boolean call(Tuple2<String, String> tuple2) throws Exception {
String sessionInfo=tuple2._2;
//按照条件进行过滤
//按照年龄进行过滤
if(!ValidUtils.between(sessionInfo,Constants.FIELD_AGE,paramter,Constants.PARAM_STARTAGE,Constants.PARAM_ENDAGE))
return false;
//按照职业进行过滤
if(!ValidUtils.in(sessionInfo,Constants.FIELD_PROFESSIONAL,paramter,Constants.PARAM_PROFESSONALS))
return false;
//按照城市进行过滤
if(!ValidUtils.in(sessionInfo,Constants.FIELD_CITY,paramter,Constants.PARAM_CIYTIES))
return false;
//按照性别进行筛选
if(!ValidUtils.equal(sessionInfo,Constants.FIELD_SEX,paramter,Constants.PARAM_SEX))
return false;
//按照搜索词进行过滤，只要有一个搜索词即可
if(!ValidUtils.in(sessionInfo,Constants.FIELD_SERACH_KEYWORDS,paramter,Constants.PARAM_PROFESSONALS))
return false;
if(!ValidUtils.in(sessionInfo,Constants.FIELD_CLICK_CATEGORYIDS,paramter,Constants.FIELD_CLICK_CATEGORYIDS))
return false;
//如果经过了之前的所有的过滤条件，也就是满足用户筛选条件
sessionAggrStatAccumulator.add(Constants.SESSION_COUNT);
//计算出访问时长和访问步长的范围并进行相应的累加
Long visitLength=Long.valueOf(StringUtils.getFieldFromConcatString(sessionInfo,"\\|",Constants.FIELD_VISIT_LENGTH));
Long stepLength=Long.valueOf(StringUtils.getFieldFromConcatString(sessionInfo,"\\|",Constants.FIELD_STEP_LENGTH));
//使用函数进行统计
calculateVisitLength(visitLength);
calculateStepLength(stepLength);
return true;
}
//统计访问时长的数量
private void calculateVisitLength(Long visitLegth)
{
if(visitLegth>=1&&visitLegth<=3)
sessionAggrStatAccumulator.add(Constants.TIME_PERIOD_1s_3s);
else if(visitLegth>=4&&visitLegth<=6)
sessionAggrStatAccumulator.add(Constants.TIME_PERIOD_4s_6s);
else if(visitLegth>=7&&visitLegth<=9)
sessionAggrStatAccumulator.add(Constants.TIME_PERIOD_7s_9s);
else if(visitLegth>=10&&visitLegth<=30)
sessionAggrStatAccumulator.add(Constants.TIME_PERIOD_10s_30s);
else if(visitLegth>30&&visitLegth<=60)
sessionAggrStatAccumulator.add(Constants.TIME_PERIOD_30s_60s);
else if(visitLegth>60&&visitLegth<=180)
sessionAggrStatAccumulator.add(Constants.TIME_PERIOD_1m_3m);
else if(visitLegth>180&&visitLegth<=600)
sessionAggrStatAccumulator.add(Constants.TIME_PERIOD_3m_10m);
else if(visitLegth>600&&visitLegth<=1800)
sessionAggrStatAccumulator.add(Constants.TIME_PERIOD_10m_30m);
else if(visitLegth>1800)
sessionAggrStatAccumulator.add(Constants.TIME_PERIOD_30m);
}
//统计访问步长的数量
private void calculateStepLength(Long stepLength)
{
if(stepLength>=1&&stepLength<=3)
sessionAggrStatAccumulator.add(Constants.STEP_PERIOD_1_3);
else if(stepLength>=4&&stepLength<=6)
sessionAggrStatAccumulator.add(Constants.STEP_PERIOD_4_6);
else if(stepLength>=7&&stepLength<=9)
sessionAggrStatAccumulator.add(Constants.STEP_PERIOD_7_9);
else if(stepLength>=10&&stepLength<=30)
sessionAggrStatAccumulator.add(Constants.STEP_PERIOD_10_30);
else if(stepLength>30&&stepLength<=60)
sessionAggrStatAccumulator.add(Constants.STEP_PERIOD_30_60);
else if(stepLength>60)
sessionAggrStatAccumulator.add(Constants.STEP_PERIOD_60);
}
});
return filteredSessionRDD;
}
}

11
src/main/java/cn/edu/hust/util/DateUtils.java
Unescape View File

@ -1,5 +1,6 @@
package cn.edu.hust.util;
import java.text.ParseException;
import java.text.SimpleDateFormat;
import java.util.Calendar;
import java.util.Date;
@ -127,5 +128,15 @@ public class DateUtils {
public static String formatTime(Date date) {
return TIME_FORMAT.format(date);
}
public static Date parseTime(String time)
{
try {
return TIME_FORMAT.parse(time);
} catch (ParseException e) {
e.printStackTrace();
}
return null;
}
}

10
src/main/java/cn/edu/hust/util/StringUtils.java
Unescape View File

@ -64,10 +64,12 @@ public class StringUtils {
String delimiter, String field) {
String[] fields = str.split(delimiter);
for(String concatField : fields) {
String fieldName = concatField.split("=")[0];
String fieldValue = concatField.split("=")[1];
if(fieldName.equals(field)) {
return fieldValue;
if(concatField.split("=").length==2) {
String fieldName = concatField.split("=")[0];
String fieldValue = concatField.split("=")[1];
if (fieldName.equals(field)) {
return fieldValue;
}
}
}
return null;

8
src/main/resources/conf.properties
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@ -1,2 +1,6 @@
key1=value1
key2=value2
jdbc.driver=com.mysql.jdbc.Driver
jdbc.url=jdbc:mysql://10.211.55.16:3306/BigDataPlatm?useUnicode=true&&characterEncoding=UTF-8
jdbc.username=root
jdbc.password=root
jdbc.active=10
spark.local=true;

14
src/test/java/cn/edu/hust/dao/TaskDaoTest.java
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@ -0,0 +1,14 @@
package cn.edu.hust.dao;
import cn.edu.hust.dao.factory.DaoFactory;
import cn.edu.hust.domain.Task;
import org.junit.Test;
public class TaskDaoTest {
@Test
public void testDao()
{
Task task=DaoFactory.getTaskDao().findTaskById(1L);
System.out.println(task.getTaskName()+":"+task.getTaskParam());
};
}

49
src/test/java/cn/edu/hust/jdbc/JDBCHelperTest.java
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@ -0,0 +1,49 @@
package cn.edu.hust.jdbc;
import org.junit.Test;
import java.sql.ResultSet;
import java.sql.SQLException;
import java.util.ArrayList;
import java.util.List;
public class JDBCHelperTest {
@Test
public void testUpdate()
{
String sql="insert into user(username,age) values(?,?)";
Object[] params={"zhangsan",12};
JDBCHelper.getInstance().excuteUpdate(sql,params);
}
@Test
public void testBatch()
{
String sql="insert into user(username,age) values(?,?)";
List<Object[]> params=new ArrayList();
params.add(new Object[]{"lisi",23});
params.add(new Object[]{"wangwu",28});
JDBCHelper.getInstance().excuteBatch(sql,params);
}
@Test
public void testQuery()
{
String sql="select * from user where username=?";
Object[] params={"zhangsan"};
JDBCHelper.getInstance().excuteQuery(sql, params, new JDBCHelper.QueryCallBack() {
@Override
public void process(ResultSet rs) {
try {
if(rs.next())
{
System.out.println("结果是"+rs.getInt(2));
}
} catch (SQLException e) {
e.printStackTrace();
}
}
});
}
}

17
src/test/java/cn/edu/hust/json/FastJsonTest.java
Unescape View File

@ -0,0 +1,17 @@
package cn.edu.hust.json;
import com.alibaba.fastjson.JSONArray;
import org.junit.Test;
public class FastJsonTest {
/**
* Json测试
*/
@Test
public void test1()
{
String json="[{'name':'Tom','age':23},{'name':'LiLi','age':24}]";
JSONArray array=JSONArray.parseArray(json);
System.out.println(array.getJSONObject(0).get("name"));
}
}

16
src/test/java/cn/edu/hust/utils/ParamUtilsTest.java
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@ -0,0 +1,16 @@
package cn.edu.hust.utils;
import cn.edu.hust.util.ParamUtils;
import com.alibaba.fastjson.JSONObject;
import org.junit.Test;
public class ParamUtilsTest {
@Test
public void test2()
{
String json="{\"startAge\":[\"10\"],\"endAge\":[\"34\"],\"startDate\":[\"2018-06-22\"],\"endDate\":[\"2018-06-22\"]}";
JSONObject param=JSONObject.parseObject(json);
//param.getJSONArray("startAge");
System.out.println(ParamUtils.getParam(param,"startDate"));
}
}

8
target/classes/conf.properties
Unescape View File

@ -1,2 +1,6 @@
key1=value1
key2=value2
jdbc.driver=com.mysql.jdbc.Driver
jdbc.url=jdbc:mysql://10.211.55.16:3306/BigDataPlatm?useUnicode=true&&characterEncoding=UTF-8
jdbc.username=root
jdbc.password=root
jdbc.active=10
spark.local=true;

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