MockData.java

import java.util.ArrayList;
import java.util.Arrays;
import java.util.List;
import java.util.Random;
import java.util.UUID;

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;

import com.ibeifeng.sparkproject.util.DateUtils;
import com.ibeifeng.sparkproject.util.StringUtils;

/**
 * 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");  
    }
    
}

UserVisitSessionAnalyzeSpark.java

import org.apache.spark.SparkConf;
import org.apache.spark.SparkContext;
import org.apache.spark.api.java.JavaSparkContext;
import org.apache.spark.sql.SQLContext;
import org.apache.spark.sql.hive.HiveContext;

import com.ibeifeng.sparkproject.conf.ConfigurationManager;
import com.ibeifeng.sparkproject.constant.Constants;
import com.ibeifeng.sparkproject.test.MockData;

/**
 * 用户访问session分析Spark作业
 * @author Administrator
 *
 */
public class UserVisitSessionAnalyzeSpark {

    public static void main(String[] args) {
        // 构建Spark上下文
        SparkConf conf = new SparkConf()
                .setAppName(Constants.SPARK_APP_NAME_SESSION)
                .setMaster("local");    
        JavaSparkContext sc = new JavaSparkContext(conf);
        SQLContext sqlContext = getSQLContext(sc.sc());
        
        // 生成模拟测试数据
        mockData(sc, sqlContext);
        
        // 关闭Spark上下文
        sc.close(); 
    }
    
    /**
     * 获取SQLContext
     * 如果是在本地测试环境的话，那么就生成SQLContext对象
     * 如果是在生产环境运行的话，那么就生成HiveContext对象
     * @param sc SparkContext
     * @return SQLContext
     */
    private static SQLContext getSQLContext(SparkContext sc) {
        boolean local = ConfigurationManager.getBoolean(Constants.SPARK_LOCAL);
        if(local) {
            return new SQLContext(sc);
        } else {
            return new HiveContext(sc);
        }
    }
    
    /**
     * 生成模拟数据（只有本地模式，才会去生成模拟数据）
     * @param sc 
     * @param sqlContext
     */
    private static void mockData(JavaSparkContext sc, SQLContext sqlContext) {
        boolean local = ConfigurationManager.getBoolean(Constants.SPARK_LOCAL);
        if(local) {
            MockData.mock(sc, sqlContext);  
        }
    }
    
}