-- 方法1: 使用DISTINCT关键字
SELECT DISTINCT * FROM table_name;

-- 方法2: 使用GROUP BY
SELECT column1, column2, ... 
FROM table_name
GROUP BY column1, column2, ...;

-- 方法3: 使用ROW_NUMBER()窗口函数(保留最新记录)
WITH CTE AS (
    SELECT *,
           ROW_NUMBER() OVER (PARTITION BY column1, column2, ... ORDER BY id DESC) AS rn
    FROM table_name
)
DELETE FROM CTE WHERE rn > 1;

# 使用pandas处理DataFrame
import pandas as pd

# 读取数据
df = pd.read_csv('data.csv')

# 删除完全重复的行
df.drop_duplicates(inplace=True)

# 基于特定列删除重复行
df.drop_duplicates(subset=['column1', 'column2'], keep='first', inplace=True)

# 使用集合处理列表
original_list = [1, 2, 2, 3, 4, 4, 5]
unique_list = list(set(original_list))  # 顺序会改变
# 保持顺序的方法
from collections import OrderedDict
unique_list = list(OrderedDict.fromkeys(original_list))

// 数组去重
const array = [1, 2, 2, 3, 4, 4, 5];
const uniqueArray = [...new Set(array)];

// 对象数组去重
const objectArray = [{id: 1}, {id: 2}, {id: 1}];
const uniqueObjectArray = objectArray.filter(
  (obj, index, self) => index === self.findIndex((o) => o.id === obj.id)
);

import java.util.*;

public class RemoveDuplicates {
    public static void main(String[] args) {
        // List去重
        List<Integer> list = Arrays.asList(1, 2, 2, 3, 4, 4, 5);
        List<Integer> uniqueList = new ArrayList<>(new LinkedHashSet<>(list));
        
        // 对象列表去重
        List<Person> persons = Arrays.asList(
            new Person(1, "John"),
            new Person(2, "Jane"),
            new Person(1, "John")
        );
        List<Person> uniquePersons = persons.stream()
            .collect(Collectors.collectingAndThen(
                Collectors.toCollection(() -> new TreeSet<>(Comparator.comparing(Person::getId))),
                ArrayList::new
            ));
    }
}

class Person {
    private int id;
    private String name;
    // 构造方法、getter和setter省略
}