feat:提交代码

.gitignore

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+/.venv/

.idea/.gitignore

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+# 默认忽略的文件
+/shelf/
+/workspace.xml

.idea/inspectionProfiles/Project_Default.xml

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+<component name="InspectionProjectProfileManager">
+  <profile version="1.0">
+    <option name="myName" value="Project Default" />
+    <inspection_tool class="PyPackageRequirementsInspection" enabled="true" level="WARNING" enabled_by_default="true">
+      <option name="ignoredPackages">
+        <value>
+          <list size="3">
+            <item index="0" class="java.lang.String" itemvalue="confluent-kafka" />
+            <item index="1" class="java.lang.String" itemvalue="pymysql" />
+            <item index="2" class="java.lang.String" itemvalue="Flask" />
+          </list>
+        </value>
+      </option>
+    </inspection_tool>
+  </profile>
+</component>

.idea/inspectionProfiles/profiles_settings.xml

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+<component name="InspectionProjectProfileManager">
+  <settings>
+    <option name="USE_PROJECT_PROFILE" value="false" />
+    <version value="1.0" />
+  </settings>
+</component>

.idea/misc.xml

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+<?xml version="1.0" encoding="UTF-8"?>
+<project version="4">
+  <component name="Black">
+    <option name="sdkName" value="Python 3.8 (pythonProject) (2)" />
+  </component>
+  <component name="ProjectRootManager" version="2" project-jdk-name="Python 3.12" project-jdk-type="Python SDK" />
+</project>

.idea/modules.xml

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+<?xml version="1.0" encoding="UTF-8"?>
+<project version="4">
+  <component name="ProjectModuleManager">
+    <modules>
+      <module fileurl="file://$PROJECT_DIR$/.idea/pythonProject.iml" filepath="$PROJECT_DIR$/.idea/pythonProject.iml" />
+    </modules>
+  </component>
+</project>

.idea/pythonProject.iml

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+<?xml version="1.0" encoding="UTF-8"?>
+<module type="PYTHON_MODULE" version="4">
+  <component name="NewModuleRootManager">
+    <content url="file://$MODULE_DIR$">
+      <excludeFolder url="file://$MODULE_DIR$/.venv" />
+    </content>
+    <orderEntry type="jdk" jdkName="Python 3.12" jdkType="Python SDK" />
+    <orderEntry type="sourceFolder" forTests="false" />
+  </component>
+</module>

.idea/vcs.xml

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+<?xml version="1.0" encoding="UTF-8"?>
+<project version="4">
+  <component name="VcsDirectoryMappings">
+    <mapping directory="$PROJECT_DIR$" vcs="Git" />
+  </component>
+</project>

cf.py

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+from confluent_kafka import Consumer, KafkaException
+import json
+import time
+
+# Kafka 配置
+conf = {
+    'bootstrap.servers': 'niit-node3:9092',
+    'group.id': 'recommendation-group',
+    'auto.offset.reset': 'earliest'
+}
+
+consumer = Consumer(conf)
+consumer.subscribe(['orders'])
+
+# 状态存储：category -> { product -> (total_rating, count) }
+product_ratings = {}
+
+def update_product_rating(category, product, rating):
+    if category not in product_ratings:
+        product_ratings[category] = {}
+    ratings = product_ratings[category]
+    if product in ratings:
+        total, cnt = ratings[product]
+        ratings[product] = (total + rating, cnt + 1)
+    else:
+        ratings[product] = (rating, 1)
+
+def get_top_n_products(ratings_dict, n=3):
+    # 计算平均评分并排序
+    rated_products = [
+        (prod, total / cnt) for prod, (total, cnt) in ratings_dict.items()
+    ]
+    rated_products.sort(key=lambda x: x[1], reverse=True)
+    return [p[0] for p in rated_products[:n]]
+
+try:
+    while True:
+        msg = consumer.poll(timeout=1.0)
+        if msg is None:
+            continue
+        if msg.error():
+            if msg.error().code() == KafkaException._PARTITION_EOF:
+                print(f"Reached end of partition: {msg.topic()} [{msg.partition()}]")
+            else:
+                raise KafkaException(msg.error())
+        else:
+            # 解析消息内容
+            try:
+                # 注意：Java 生产者发送的是 tab 分隔的字符串，不是 JSON
+                line = msg.value().decode('utf-8').strip()
+                parts = line.split('\t')
+                if len(parts) != 6:
+                    continue
+                category, product, quantity, date, rating_str, is_valid = parts
+                if is_valid != "Y":
+                    continue
+                rating = int(rating_str)
+
+                # 更新评分
+                update_product_rating(category, product, rating)
+
+                # 获取当前类别下的 Top 3
+                top3 = get_top_n_products(product_ratings[category])
+                print(f"[{category}] Top 3: {', '.join(top3)}")
+
+            except Exception as e:
+                print("Error parsing message:", str(e))
+                continue
+
+except KeyboardInterrupt:
+    print("Stopping consumer...")
+
+finally:
+    consumer.close()

cf2.py

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+from confluent_kafka import Consumer, KafkaException
+import json
+import time
+import mysql.connector
+from mysql.connector import Error
+
+# =================== Kafka 配置 ===================
+conf = {
+    'bootstrap.servers': 'niit-node3:9092',
+    'group.id': 'recommendation-group',
+    'auto.offset.reset': 'earliest'
+}
+
+consumer = Consumer(conf)
+consumer.subscribe(['orders'])
+
+# =================== MySQL 配置 ===================
+mysql_config = {
+    'host': '172.16.5.3',
+    'port': 3306,
+    'user': 'root',
+    'password': '123456',
+    'database': 'orders_db'
+}
+
+# 创建数据库连接
+try:
+    conn = mysql.connector.connect(**mysql_config)
+    if conn.is_connected():
+        print("✅ 成功连接到 MySQL 数据库")
+        cursor = conn.cursor()
+except Error as e:
+    print("❌ 连接 MySQL 失败:", e)
+    exit(1)
+
+# =================== 状态存储 ===================
+product_ratings = {}
+
+def update_product_rating(category, product, rating):
+    if category not in product_ratings:
+        product_ratings[category] = {}
+    ratings = product_ratings[category]
+    if product in ratings:
+        total, cnt = ratings[product]
+        ratings[product] = (total + rating, cnt + 1)
+    else:
+        ratings[product] = (rating, 1)
+
+def get_top_n_products(ratings_dict, n=3):
+    rated_products = [
+        (prod, total / cnt) for prod, (total, cnt) in ratings_dict.items()
+    ]
+    rated_products.sort(key=lambda x: x[1], reverse=True)
+    return [p[0] for p in rated_products[:n]]
+
+# =================== 插入 MySQL 函数 ===================
+def insert_top_products_to_mysql(category, top_products_list):
+    try:
+        # 将商品列表转为 JSON 字符串
+        top_products_json = json.dumps(top_products_list, ensure_ascii=False)
+        query = """
+        INSERT INTO category_top_products (category, top_products)
+        VALUES (%s, %s)
+        """
+        cursor.execute(query, (category, top_products_json))
+        conn.commit()
+        print(f"🟢 已插入数据库：[{category}] {top_products_json}")
+    except Error as e:
+        print(f"🔴 插入数据库失败 [{category}]:", e)
+        conn.rollback()
+
+# =================== 主循环 ===================
+try:
+    while True:
+        msg = consumer.poll(timeout=1.0)
+        if msg is None:
+            continue
+        if msg.error():
+            if msg.error().code() == KafkaException._PARTITION_EOF:
+                print(f"Reached end of partition: {msg.topic()} [{msg.partition()}]")
+            else:
+                raise KafkaException(msg.error())
+        else:
+            try:
+                line = msg.value().decode('utf-8').strip()
+                parts = line.split('\t')
+                if len(parts) != 6:
+                    continue
+                category, product, quantity, date, rating_str, is_valid = parts
+                if is_valid != "Y":
+                    continue
+                rating = int(rating_str)
+
+                update_product_rating(category, product, rating)
+
+                top3 = get_top_n_products(product_ratings[category])
+                print(f"[{category}] Top 3: {', '.join(top3)}")
+
+                # 插入 MySQL
+                insert_top_products_to_mysql(category, top3)
+
+            except Exception as e:
+                print("⚠️ 解析消息错误:", str(e))
+                continue
+
+except KeyboardInterrupt:
+    print("\n🛑 停止消费者...")
+
+finally:
+    consumer.close()
+    cursor.close()
+    conn.close()
+    print("🔌 数据库和 Kafka 连接已关闭")

cf3.py

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+from confluent_kafka import Consumer, KafkaException
+import json
+import time
+import mysql.connector
+from mysql.connector import Error
+from collections import defaultdict
+
+# Kafka 配置
+conf = {
+    'bootstrap.servers': 'niit-node3:9092',
+    'group.id': 'recommendation-group',
+    'auto.offset.reset': 'earliest'
+}
+
+consumer = Consumer(conf)
+consumer.subscribe(['orders'])
+
+# MySQL 配置
+mysql_config = {
+    'host': '172.16.5.3',
+    'port': 3306,
+    'user': 'root',
+    'password': '123456',
+    'database': 'orders_db'
+}
+
+# 创建数据库连接
+try:
+    conn = mysql.connector.connect(**mysql_config)
+    if conn.is_connected():
+        print(" 成功连接到 MySQL 数据库")
+        cursor = conn.cursor()
+except Error as e:
+    print(" 连接 MySQL 失败:", e)
+    exit(1)
+
+# =================== 状态存储
+window_duration = 300  # 5 分钟
+current_window_start = int(time.time())
+
+# 缓存当前窗口的商品评分：{ category -> { product -> (total_rating, count) } }
+product_ratings_window = defaultdict(lambda: defaultdict(lambda: [0, 0]))
+
+def get_top_n_products(ratings_dict, n=3):
+    rated_products = [
+        (prod, total / cnt) for prod, (total, cnt) in ratings_dict.items()
+    ]
+    rated_products.sort(key=lambda x: x[1], reverse=True)
+    return [p[0] for p in rated_products[:n]]
+
+# =================== 插入 MySQL 函数
+def insert_top_products_to_mysql(category, top_products_list, window_end_time):
+    try:
+        top_products_json = json.dumps(top_products_list, ensure_ascii=False)
+        timestamp = time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(window_end_time))
+        query = """
+        INSERT INTO category_top_products (category, top_products, timestamp)
+        VALUES (%s, %s, %s)
+        """
+        cursor.execute(query, (category, top_products_json, timestamp))
+        conn.commit()
+        print(f" 已插入数据库：[{category}] {top_products_json} @ {timestamp}")
+    except Error as e:
+        print(f" 插入数据库失败 [{category}]:", e)
+        conn.rollback()
+
+# =================== 主循环
+try:
+    while True:
+        msg = consumer.poll(timeout=1.0)
+        current_time = int(time.time())
+
+        # 判断是否到了窗口结束时间
+        if current_time - current_window_start >= window_duration:
+            print(f"\n 开始处理从 {time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(current_window_start))} 到现在的时间窗口...")
+
+            # 为每个类别生成 Top 3 推荐
+            for category, products in product_ratings_window.items():
+                top3 = get_top_n_products(products)
+                insert_top_products_to_mysql(category, top3, current_time)
+
+            # 清空窗口缓存，更新窗口起始时间
+            product_ratings_window.clear()
+            current_window_start = current_time
+            print(" 窗口已重置\n")
+
+        # 如果有消息，则继续处理
+        if msg is None:
+            continue
+        if msg.error():
+            if msg.error().code() == KafkaException._PARTITION_EOF:
+                print(f"Reached end of partition: {msg.topic()} [{msg.partition()}]")
+            else:
+                raise KafkaException(msg.error())
+        else:
+            try:
+                line = msg.value().decode('utf-8').strip()
+                parts = line.split('\t')
+                if len(parts) != 6:
+                    continue
+                category, product, quantity, date, rating_str, is_valid = parts
+                if is_valid != "Y":
+                    continue
+                rating = int(rating_str)
+
+                # 更新当前窗口评分
+                product_ratings_window[category][product][0] += rating
+                product_ratings_window[category][product][1] += 1
+
+            except Exception as e:
+                print("⚠ 解析消息错误:", str(e))
+                continue
+
+except KeyboardInterrupt:
+    print("\n 停止消费者...")
+
+finally:
+    consumer.close()
+    cursor.close()
+    conn.close()
+    print(" 数据库和 Kafka 连接已关闭")

cf_test.py

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+from collections import defaultdict
+import random
+
+# 商品类别和商品名称映射
+CATEGORIES = ["电器", "服饰", "食品", "玩具", "手机"]
+
+PRODUCT_NAMES = {
+    "电器": ["电视", "冰箱", "洗衣机", "空调", "吸尘器", "电饭煲", "微波炉", "电磁炉", "热水器", "空气净化器"],
+    "服饰": ["T恤", "牛仔裤", "羽绒服", "衬衫", "运动鞋", "夹克", "卫衣", "连衣裙", "短裤", "风衣"],
+    "食品": ["巧克力", "饼干", "方便面", "牛奶", "饮料", "面包", "糖果", "果冻", "薯片", "蛋挞"],
+    "玩具": ["积木", "拼图", "玩偶", "遥控车", "毛绒玩具", "魔方", "乐高", "变形金刚", "洋娃娃", "电子琴"],
+    "手机": ["华为", "苹果", "小米", "OPPO", "vivo", "荣耀", "三星", "魅族", "联想", "努比亚"]
+}
+
+# 用户评分 (0, 50, 100) -> 不喜欢、还行、很喜欢
+RATINGS = [0, 50, 100]
+IS_VALID = ["Y", "N"]
+
+
+# ================== 生成假数据 ==================
+def generate_fake_orders(n=50):
+    orders = []
+    for _ in range(n):
+        category = random.choice(CATEGORIES)
+        product = random.choice(PRODUCT_NAMES[category])
+        rating = random.choice(RATINGS)
+        is_valid = random.choice(IS_VALID)
+
+        orders.append({
+            'category': category,
+            'product': product,
+            'rating': rating,
+            'isValid': is_valid
+        })
+    return orders
+
+
+# ================== 推荐逻辑 ==================
+def recommend_top_n(orders, n=3):
+    # 存储：{ category: { product: (total_rating, count) } }
+    product_ratings = defaultdict(lambda: defaultdict(lambda: [0, 0]))  # [总评分, 数量]
+
+    for order in orders:
+        if order['isValid'] != 'Y':
+            continue
+        category = order['category']
+        product = order['product']
+        rating = order['rating']
+
+        product_ratings[category][product][0] += rating
+        product_ratings[category][product][1] += 1
+
+    # 计算平均评分并排序
+    recommendations = {}
+    for category, products in product_ratings.items():
+        rated_products = [
+            (product, total / count) for product, (total, count) in products.items()
+        ]
+        rated_products.sort(key=lambda x: x[1], reverse=True)
+        recommendations[category] = [p[0] for p in rated_products[:n]]
+
+    return recommendations
+
+
+# ================== 主程序入口 ==================
+if __name__ == '__main__':
+    fake_data = generate_fake_orders(100)
+
+    print("=== 假数据样本 ===")
+    for d in fake_data[:10]:  # 打印前10条数据看看
+        print(d)
+
+    print("\n=== 开始推荐 Top 3 商品 ===")
+    result = recommend_top_n(fake_data, n=3)
+
+    for category, top_products in result.items():
+        print(f"[{category}] 推荐商品：{', '.join(top_products)}")