Hive 是一個基于 Hadoop 的數(shù)據(jù)倉庫架構(gòu)，它通過 Hadoop 的 MapReduce 進行數(shù)據(jù)讀取和計算，大大提高了數(shù)據(jù)的處理效率。

MySQL 是一種關(guān)系型數(shù)據(jù)庫，常用于 Web 應用程序的數(shù)據(jù)管理和處理。

Hive 可以通過 JDBC 驅(qū)動程序和 MySQL 進行交互，將 Hive 中存儲的數(shù)據(jù)導入到 MySQL 中，也可以將 MySQL 的數(shù)據(jù)導入到 Hive 中。

#將 Hive 中的數(shù)據(jù)導入到 MySQL
#在 Hive 中創(chuàng)建一個表，并將數(shù)據(jù)導入到該表中
CREATE TABLE student (
id INT,
name STRING,
age INT 
);
LOAD DATA LOCAL INPATH '/user/hive/warehouse/student' INTO TABLE student;
#通過 JDBC 驅(qū)動程序連接 MySQL 并導入數(shù)據(jù)
import java.sql.Connection;
import java.sql.DriverManager;
import java.sql.Statement;
public class HiveToMySQL {
public static void main(String[] args) {
String driver = "com.mysql.jdbc.Driver";
String url = "jdbc:mysql://localhost:3306/test";
String user = "root";
String password = "123456";
Connection conn;
try {
Class.forName(driver);
conn = DriverManager.getConnection(url, user, password);
Statement statement = conn.createStatement();
String sql = "INSERT INTO student (id, name, age) SELECT id, name, age FROM hive.student";
statement.executeUpdate(sql);
conn.close();
} catch (Exception e) {
e.printStackTrace();
}
}
}
#將 MySQL 中的數(shù)據(jù)導入到 Hive
#在 Hive 中創(chuàng)建一個表
CREATE TABLE student (
id INT,
name STRING,
age INT 
);
#通過 JDBC 驅(qū)動程序連接 MySQL 并將數(shù)據(jù)導入到 Hive
import java.sql.Connection;
import java.sql.DriverManager;
import java.sql.ResultSet;
import java.sql.Statement;
public class MySQLToHive {
public static void main(String[] args) {
String driver = "com.mysql.jdbc.Driver";
String url = "jdbc:mysql://localhost:3306/test";
String user = "root";
String password = "123456";
Connection conn;
try {
Class.forName(driver);
conn = DriverManager.getConnection(url, user, password);
Statement statement = conn.createStatement();
String sql = "SELECT * FROM student";
ResultSet resultSet = statement.executeQuery(sql);
while (resultSet.next()) {
int id = resultSet.getInt("id");
String name = resultSet.getString("name");
int age = resultSet.getInt("age");
String hiveSql = "INSERT INTO TABLE student VALUES (" + id + ", '" + name + "', " + age + ")";
statement.executeUpdate(hiveSql);
}
conn.close();
} catch (Exception e) {
e.printStackTrace();
}
}
}