MongoDB实训：电子商务日志存储任务

一、实验目的

理解如何通过Java API连接MongoDB数据库。
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。
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

JAVA环境准备：确保Java Development Kit (JDK) 已安装并配置好环境变量。
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。

首先在pom.xml中添加MongoDB的Maven依赖

使用MongoDB Java驱动连接到MongoDB数据库。

（1）代码实现

java 复制代码

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。

代码实现

java 复制代码

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);
}

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。

代码实现

java 复制代码

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!");
}

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）。

按时间范围查询

（1）代码实现

java 复制代码

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

按商品名称查询

（1）代码实现

java 复制代码

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。

统计某时间段内日志数量

（1）代码实现

java 复制代码

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

按商品类别统计销售额

（1）代码实现

java 复制代码

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

java 复制代码

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());
        }
    }
}