docs(BD-exp-3): 添加项目文档和示例代码

- 新增 App.java 和 AppTest.java 文件作为项目示例
- 添加 command.md、origin.md 和 sql.md 文件，包含项目相关命令和 SQL 语句
- 创建 pom.xml 文件定义项目依赖

command.md

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+sed 's/::/,/g' users.dat > users_cleaned.dat
+sed 's/::/,/g' movies.dat > movies_cleaned.dat
+sed 's/::/,/g' ratings.dat > ratings_cleaned.dat
+
+hadoop fs -rm /user/hadoop/movie_data/users.dat
+hadoop fs -rm /user/hadoop/movie_data/movies.dat
+hadoop fs -rm /user/hadoop/movie_data/ratings.dat
+
+hadoop fs -mkdir /user/hadoop/movie_data/users
+hadoop fs -mkdir /user/hadoop/movie_data/movies
+hadoop fs -mkdir /user/hadoop/movie_data/ratings
+
+hadoop fs -put users_cleaned.dat /user/hadoop/movie_data/users/users.dat
+hadoop fs -put movies_cleaned.dat /user/hadoop/movie_data/movies/movies.dat
+hadoop fs -put ratings_cleaned.dat /user/hadoop/movie_data/ratings/ratings.dat

origin.md

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+好的，我们可以使用 **HDFS** 存储数据，并利用 **Hive** 进行 SQL 查询分析。以下是实验步骤和指令：
+
+---
+
+## **1. 数据准备**
+### **1.1 上传数据到 HDFS**
+1. **解压数据包**
+   ```bash
+   unzip data.zip
+   ```
+
+2. **创建 HDFS 目录并上传数据**
+   ```bash
+   hdfs dfs -mkdir -p /user/hadoop/movie_data
+   hdfs dfs -put users.dat /user/hadoop/movie_data/
+   hdfs dfs -put movies.dat /user/hadoop/movie_data/
+   hdfs dfs -put ratings.dat /user/hadoop/movie_data/
+   ```
+
+---
+
+## **2. 创建 Hive 数据库和表**
+### **2.1 进入 Hive**
+```bash
+hive
+```
+### **2.2 创建数据库**
+```sql
+CREATE DATABASE IF NOT EXISTS movie_analysis;
+USE movie_analysis;
+```
+
+### **2.3 创建表**
+```sql
+-- 用户表
+CREATE EXTERNAL TABLE users (
+    UserID BIGINT,
+    Gender STRING,
+    Age INT,
+    Occupation STRING,
+    Zipcode STRING
+)
+ROW FORMAT DELIMITED
+FIELDS TERMINATED BY '::'
+STORED AS TEXTFILE
+LOCATION '/user/hadoop/movie_data/';
+
+-- 电影表
+CREATE EXTERNAL TABLE movies (
+    MovieID BIGINT,
+    Title STRING,
+    Genres STRING
+)
+ROW FORMAT DELIMITED
+FIELDS TERMINATED BY '::'
+STORED AS TEXTFILE
+LOCATION '/user/hadoop/movie_data/';
+
+-- 评分表
+CREATE EXTERNAL TABLE ratings (
+    UserID BIGINT,
+    MovieID BIGINT,
+    Rating DOUBLE,
+    Timestamp STRING
+)
+ROW FORMAT DELIMITED
+FIELDS TERMINATED BY '::'
+STORED AS TEXTFILE
+LOCATION '/user/hadoop/movie_data/';
+```
+
+### **2.4 验证数据是否正确导入**
+```sql
+SELECT * FROM users LIMIT 5;
+SELECT * FROM movies LIMIT 5;
+SELECT * FROM ratings LIMIT 5;
+```
+
+---
+
+## **3. 数据分析任务**
+### **3.1 评分次数最多的10部电影**
+```sql
+SELECT m.Title, COUNT(r.MovieID) AS RatingCount
+FROM ratings r
+JOIN movies m ON r.MovieID = m.MovieID
+GROUP BY m.Title
+ORDER BY RatingCount DESC
+LIMIT 10;
+```
+
+### **3.2 男性、女性评分最高的10部电影**
+```sql
+-- 男性
+SELECT u.Gender, m.Title, AVG(r.Rating) AS AvgRating
+FROM ratings r
+JOIN users u ON r.UserID = u.UserID
+JOIN movies m ON r.MovieID = m.MovieID
+WHERE u.Gender = 'M'
+GROUP BY u.Gender, m.Title
+ORDER BY AvgRating DESC
+LIMIT 10;
+
+-- 女性
+SELECT u.Gender, m.Title, AVG(r.Rating) AS AvgRating
+FROM ratings r
+JOIN users u ON r.UserID = u.UserID
+JOIN movies m ON r.MovieID = m.MovieID
+WHERE u.Gender = 'F'
+GROUP BY u.Gender, m.Title
+ORDER BY AvgRating DESC
+LIMIT 10;
+```
+
+### **3.3 电影 ID 为 2116 的各年龄段平均影评分**
+```sql
+SELECT u.Age, AVG(r.Rating) AS AvgRating
+FROM ratings r
+JOIN users u ON r.UserID = u.UserID
+WHERE r.MovieID = 2116
+GROUP BY u.Age
+ORDER BY u.Age;
+```
+
+### **3.4 观看次数最多的女性评最高分的10部电影**
+```sql
+WITH MostActiveFemale AS (
+   SELECT UserID
+   FROM (
+           SELECT UserID, COUNT(MovieID) AS rating_count
+           FROM ratings
+           WHERE UserID IN (SELECT UserID FROM users WHERE Gender = 'F')
+           GROUP BY UserID
+           ORDER BY rating_count DESC
+              LIMIT 1
+        ) t
+)
+SELECT r.UserID, m.Title, AVG(r.Rating) AS AvgRating
+FROM ratings r
+        JOIN movies m ON r.MovieID = m.MovieID
+        JOIN MostActiveFemale u ON r.UserID = u.UserID
+GROUP BY r.UserID, m.Title
+ORDER BY AvgRating DESC
+   LIMIT 10;
+```
+
+### **3.5 好片（评分≥4.0）最多的年份的前10部电影**
+```sql
+
+WITH YearlyGoodMovies AS (
+   SELECT
+   YEAR(FROM_UNIXTIME(CAST(r.Timestamped AS BIGINT))) AS Year,
+   COUNT(DISTINCT r.MovieID) AS GoodMovieCount
+FROM ratings r
+WHERE r.Rating >= 4.0
+GROUP BY YEAR(FROM_UNIXTIME(CAST(r.Timestamped AS BIGINT)))
+ORDER BY GoodMovieCount DESC
+   LIMIT 1
+   ),
+
+
+   TopMovies AS (
+SELECT
+   YEAR(FROM_UNIXTIME(CAST(r.Timestamped AS BIGINT))) AS Year,
+   m.Title,
+   COUNT(r.MovieID) AS RatingCount,
+   AVG(r.Rating) AS AvgRating
+FROM ratings r
+   JOIN movies m ON r.MovieID = m.MovieID
+WHERE r.Rating >= 4.0
+GROUP BY YEAR(FROM_UNIXTIME(CAST(r.Timestamped AS BIGINT))), m.Title
+   )
+
+SELECT t.Year, t.Title, t.RatingCount, t.AvgRating
+FROM TopMovies t
+        JOIN YearlyGoodMovies y ON t.Year = y.Year
+ORDER BY t.RatingCount DESC, t.AvgRating DESC
+LIMIT 10;
+```
+
+### **3.6 1997年上映的评分最高的10部Comedy电影**
+```sql
+SELECT m.Title, AVG(r.Rating) AS AvgRating
+FROM ratings r
+JOIN movies m ON r.MovieID = m.MovieID
+WHERE m.Title LIKE '%(1997)%' AND m.Genres LIKE '%Comedy%'
+GROUP BY m.Title
+ORDER BY AvgRating DESC
+LIMIT 10;
+```
+
+### **3.7 各类型电影中评价最高的5部电影**
+```sql
+SELECT m.Genres, m.Title, AVG(r.Rating) AS AvgRating
+FROM ratings r
+JOIN movies m ON r.MovieID = m.MovieID
+GROUP BY m.Genres, m.Title
+ORDER BY m.Genres, AvgRating DESC
+LIMIT 5;
+```
+
+### **3.8 各年评分最高的电影类型**
+```sql
+SELECT YEAR(FROM_UNIXTIME(CAST(r.Timestamp AS BIGINT))) AS Year, m.Genres, AVG(r.Rating) AS AvgRating
+FROM ratings r
+JOIN movies m ON r.MovieID = m.MovieID
+GROUP BY Year, m.Genres
+ORDER BY Year, AvgRating DESC;
+```
+
+### **3.9 每个地区最高评分的电影名**
+```sql
+INSERT OVERWRITE DIRECTORY '/user/hadoop/movie_results'
+ROW FORMAT DELIMITED
+FIELDS TERMINATED BY ','
+SELECT u.Zipcode, m.Title, AVG(r.Rating) AS AvgRating
+FROM ratings r
+JOIN users u ON r.UserID = u.UserID
+JOIN movies m ON r.MovieID = m.MovieID
+GROUP BY u.Zipcode, m.Title
+ORDER BY u.Zipcode, AvgRating DESC;
+```
+
+---
+
+## **4. 结果存入 HDFS**
+执行后，查询结果会存储在 `/user/hadoop/movie_results/` 目录下，可用以下命令查看：
+```bash
+hdfs dfs -ls /user/hadoop/movie_results/
+hdfs dfs -cat /user/hadoop/movie_results/part-00000
+```
+
+---
+
+### **总结**
+1. **数据准备**
+    - 解压并上传数据到 HDFS
+    - 创建 Hive 数据库和表
+    - 验证数据是否正确导入
+
+2. **数据分析**
+    - 计算评分最多的电影
+    - 计算男女评分最高的电影
+    - 计算不同年龄段对某部电影的评分
+    - 找出最活跃女性的最爱电影
+    - 计算评分最高的电影年份及类别
+    - 存储地区最高评分电影至 HDFS
+
+---
+
+这就是完整的实验报告步骤和指令，你可以直接复制执行。如果有任何问题，欢迎交流！🚀

pom.xml

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+<project xmlns="http://maven.apache.org/POM/4.0.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
+  xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd">
+  <modelVersion>4.0.0</modelVersion>
+
+  <groupId>org.example</groupId>
+  <artifactId>BD-exp-3</artifactId>
+  <version>1.0-SNAPSHOT</version>
+  <packaging>jar</packaging>
+
+  <name>BD-exp-3</name>
+  <url>http://maven.apache.org</url>
+
+  <properties>
+    <project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
+  </properties>
+
+  <dependencies>
+    <dependency>
+      <groupId>junit</groupId>
+      <artifactId>junit</artifactId>
+      <version>3.8.1</version>
+      <scope>test</scope>
+    </dependency>
+  </dependencies>
+</project>

sql.md

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+DROP TABLE IF EXISTS ratings;
+DROP TABLE IF EXISTS movies;
+DROP TABLE IF EXISTS users;
+
+CREATE EXTERNAL TABLE users (
+UserID BIGINT,
+Gender STRING,
+Age INT,
+Occupation STRING,
+Zipcode STRING
+)
+ROW FORMAT DELIMITED
+FIELDS TERMINATED BY ','
+STORED AS TEXTFILE
+LOCATION '/user/hadoop/movie_data/users';
+
+
+CREATE EXTERNAL TABLE movies (
+MovieID BIGINT,
+Title STRING,
+Genres STRING
+)
+ROW FORMAT DELIMITED
+FIELDS TERMINATED BY ','
+STORED AS TEXTFILE
+LOCATION '/user/hadoop/movie_data/movies';
+
+
+CREATE EXTERNAL TABLE ratings (
+UserID BIGINT,
+MovieID BIGINT,
+Rating DOUBLE,
+Timestamped STRING
+)
+ROW FORMAT DELIMITED
+FIELDS TERMINATED BY ','
+STORED AS TEXTFILE
+LOCATION '/user/hadoop/movie_data/ratings';
+
+SELECT * FROM users LIMIT 5;
+SELECT * FROM movies LIMIT 5;
+SELECT * FROM ratings LIMIT 5;

src/main/java/org/example/App.java

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+package org.example;
+
+/**
+ * Hello world!
+ *
+ */
+public class App 
+{
+    public static void main( String[] args )
+    {
+        System.out.println( "Hello World!" );
+    }
+}

src/test/java/org/example/AppTest.java

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+package org.example;
+
+import junit.framework.Test;
+import junit.framework.TestCase;
+import junit.framework.TestSuite;
+
+/**
+ * Unit test for simple App.
+ */
+public class AppTest 
+    extends TestCase
+{
+    /**
+     * Create the test case
+     *
+     * @param testName name of the test case
+     */
+    public AppTest( String testName )
+    {
+        super( testName );
+    }
+
+    /**
+     * @return the suite of tests being tested
+     */
+    public static Test suite()
+    {
+        return new TestSuite( AppTest.class );
+    }
+
+    /**
+     * Rigourous Test :-)
+     */
+    public void testApp()
+    {
+        assertTrue( true );
+    }
+}