一、实验目的
1. 理解如何通过Java API连接MongoDB数据库。
2. 学习在Java中使用MongoDB进行数据库操作，包括插入数据、查询数据以及数据统计等。
3. 掌握电子商务日志数据在MongoDB中的存储和操作方法。
二、实验环境准备
1. JAVA环境准备：确保Java Development Kit (JDK) 已安装并配置好环境变量。
2. Hadoop环境准备：安装并配置Hadoop环境，确保Hadoop的各个组件可以在伪分布式模式下运行。
三、实验教材参考
《大数据存储》，谭旭，人民邮电出版社，2022，ISBN 978-7-115-59414-3。
四、实验内容与步骤
1、连接MongoDB
使用Java API连接到MongoDB数据库，确保连接过程正确，可以通过主机名、端口号等方式连接到MongoDB服务器。
1. 首先在pom.xml中添加MongoDB的Maven依赖
2. 使用MongoDB Java驱动连接到MongoDB数据库。
（1）代码实现
private static final String DATABASE_NAME = "ECommerceDB";
private static final String COLLECTION_NAME = "Logs";
private static final String CONNECTION_STRING = "mongodb://192.168.10.200:27017";public static void main(String[] args) {try (MongoClient mongoClient = MongoClients.create(CONNECTION_STRING)) {System.out.println("Connected to MongoDB!");}
}（2）运行结果
2、创建数据库和集合
在MongoDB中创建一个新的数据库，然后在该数据库中创建一个用于存储电子商务日志数据的集合。
1. 代码实现
private static MongoCollection<Document> setupDatabaseAndCollection(MongoDatabase database) {// 删除并重新创建集合（仅用于实验目的）MongoCollection<Document> collection = database.getCollection(COLLECTION_NAME);collection.drop();database.createCollection(COLLECTION_NAME);System.out.println("Database and Collection created!");return database.getCollection(COLLECTION_NAME);
}
2. 运行结果
3、插入日志数据
编写 Java 代码，将模拟的电子商务日志数据插入到 MongoDB 的集合中，确保插入操作成功。
1. 代码实现
private static void insertLogData(MongoCollection<Document> collection) {List<Document> logs = Arrays.asList(new Document("timestamp", "2025-01-08T10:00:00").append("product", "Laptop").append("category", "Electronics").append("price", 1200).append("quantity", 1),new Document("timestamp", "2025-01-08T11:30:00").append("product", "Phone").append("category", "Electronics").append("price", 800).append("quantity", 2),new Document("timestamp", "2025-01-08T12:00:00").append("product", "Headphones").append("category", "Accessories").append("price", 200).append("quantity", 5),new Document("timestamp", "2025-01-08T13:15:00").append("product", "Keyboard").append("category", "Accessories").append("price", 100).append("quantity", 3));collection.insertMany(logs);System.out.println("Log data inserted successfully!");
}
2. 运行结果
4、 查询日志数据
编写Java代码实现对MongoDB中日志数据的查询操作，可以包括基本的查询（如按时间范围查询、按商品名称查询）和复杂的查询（如多条件组合查询）。
1. 按时间范围查询
（1）代码实现
private static void queryLogsByTimeRange(MongoCollection<Document> collection, String startTime, String endTime) {System.out.println("\nQuery: Logs from " + startTime + " to " + endTime);Bson filter = Filters.and(Filters.gte("timestamp", startTime),Filters.lte("timestamp", endTime));FindIterable<Document> results = collection.find(filter);for (Document doc : results) {System.out.println(doc.toJson());}
}
（2）运行结果
2. 按商品名称查询
（1）代码实现
private static void queryLogsByProductName(MongoCollection<Document> collection, String productName) {System.out.println("\nQuery: Logs for product '" + productName + "'");Bson filter = Filters.eq("product", productName);FindIterable<Document> results = collection.find(filter);for (Document doc : results) {System.out.println(doc.toJson());}
}
（2）运行结果
5、分类统计
实现对日志数据的分类统计，例如统计某个时间段内的日志数量、按商品类别统计销售额等，确保统计结果准确。
1. 统计某时间段内日志数量
（1）代码实现
private static void countLogsByTimeRange(MongoCollection<Document> collection, String startTime, String endTime) {System.out.println("\nCount: Logs from " + startTime + " to " + endTime);Bson filter = Filters.and(Filters.gte("timestamp", startTime),Filters.lte("timestamp", endTime));long count = collection.countDocuments(filter);System.out.println("Number of logs in the specified time range: " + count);
}
（2）运行结果
2. 按商品类别统计销售额
（1）代码实现
private static void calculateSalesByCategory(MongoCollection<Document> collection) {System.out.println("\nSales by Category:");List<Bson> pipeline = Arrays.asList(Aggregates.group("$category",Accumulators.sum("total_sales", new Document("$multiply", Arrays.asList("$price", "$quantity")))));AggregateIterable<Document> results = collection.aggregate(pipeline);for (Document doc : results) {System.out.println(doc.toJson());}
}
（2）运行结果
6、完整代码
package com.example;
import com.mongodb.client.*;
import com.mongodb.client.model.*;
import org.bson.Document;
import org.bson.conversions.Bson;
import java.util.ArrayList;
import java.util.Arrays;
import java.util.List;
public class MongoDBConnection { private static final String DATABASE_NAME = "ECommerceDB";private static final String COLLECTION_NAME = "Logs";private static final String CONNECTION_STRING = "mongodb://192.168.10.200:27017";public static void main(String[] args) {try (MongoClient mongoClient = MongoClients.create(CONNECTION_STRING)) {System.out.println("Connected to MongoDB!");MongoDatabase database = mongoClient.getDatabase(DATABASE_NAME);MongoCollection<Document> collection = setupDatabaseAndCollection(database);insertLogData(collection);queryLogsByTimeRange(collection, "2025-01-08T10:00:00", "2025-01-08T12:00:00");queryLogsByProductName(collection, "Laptop");countLogsByTimeRange(collection, "2025-01-08T10:00:00", "2025-01-08T13:00:00");calculateSalesByCategory(collection);} catch (Exception e) {e.printStackTrace();}}/*** 初始化数据库和集合*/private static MongoCollection<Document> setupDatabaseAndCollection(MongoDatabase database) {// 删除并重新创建集合（仅用于实验目的）MongoCollection<Document> collection = database.getCollection(COLLECTION_NAME);collection.drop();database.createCollection(COLLECTION_NAME);System.out.println("Database and Collection created!");return database.getCollection(COLLECTION_NAME);}/*** 插入日志数据*/private static void insertLogData(MongoCollection<Document> collection) {List<Document> logs = Arrays.asList(new Document("timestamp", "2025-01-08T10:00:00").append("product", "Laptop").append("category", "Electronics").append("price", 1200).append("quantity", 1),new Document("timestamp", "2025-01-08T11:30:00").append("product", "Phone").append("category", "Electronics").append("price", 800).append("quantity", 2),new Document("timestamp", "2025-01-08T12:00:00").append("product", "Headphones").append("category", "Accessories").append("price", 200).append("quantity", 5),new Document("timestamp", "2025-01-08T13:15:00").append("product", "Keyboard").append("category", "Accessories").append("price", 100).append("quantity", 3));collection.insertMany(logs);System.out.println("Log data inserted successfully!");}/*** 按时间范围查询日志数据*/private static void queryLogsByTimeRange(MongoCollection<Document> collection, String startTime, String endTime) {System.out.println("\nQuery: Logs from " + startTime + " to " + endTime);Bson filter = Filters.and(Filters.gte("timestamp", startTime),Filters.lte("timestamp", endTime));FindIterable<Document> results = collection.find(filter);for (Document doc : results) {System.out.println(doc.toJson());}}/*** 按商品名称查询日志数据*/private static void queryLogsByProductName(MongoCollection<Document> collection, String productName) {System.out.println("\nQuery: Logs for product '" + productName + "'");Bson filter = Filters.eq("product", productName);FindIterable<Document> results = collection.find(filter);for (Document doc : results) {System.out.println(doc.toJson());}}/*** 统计某时间段内的日志数量*/private static void countLogsByTimeRange(MongoCollection<Document> collection, String startTime, String endTime) {System.out.println("\nCount: Logs from " + startTime + " to " + endTime);Bson filter = Filters.and(Filters.gte("timestamp", startTime),Filters.lte("timestamp", endTime));long count = collection.countDocuments(filter);System.out.println("Number of logs in the specified time range: " + count);}/*** 按商品类别统计销售额*/private static void calculateSalesByCategory(MongoCollection<Document> collection) {System.out.println("\nSales by Category:");List<Bson> pipeline = Arrays.asList(Aggregates.group("$category",Accumulators.sum("total_sales", new Document("$multiply", Arrays.asList("$price", "$quantity")))));AggregateIterable<Document> results = collection.aggregate(pipeline);for (Document doc : results) {System.out.println(doc.toJson());}}
}
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