Spring boot with Apache Hive

转自

Maven

<dependency>
			<groupId>org.springframework.boot</groupId>
			<artifactId>spring-boot-starter-jdbc</artifactId>
		</dependency>
		<dependency>
			<groupId>org.springframework.data</groupId>
			<artifactId>spring-data-hadoop</artifactId>
			<version>2.5.0.RELEASE</version>
		</dependency>
		<!-- https://mvnrepository.com/artifact/org.apache.hive/hive-jdbc -->
		<dependency>
			<groupId>org.apache.hive</groupId>
			<artifactId>hive-jdbc</artifactId>
			<version>2.3.0</version>
			<exclusions>
				<exclusion>
					<groupId>org.eclipse.jetty.aggregate</groupId>
					<artifactId>*</artifactId>
				</exclusion>
			</exclusions>
		</dependency>
		<dependency>
			<groupId>org.apache.tomcat</groupId>
			<artifactId>tomcat-jdbc</artifactId>
			<version>8.5.20</version>
		</dependency>

application.properties

hive 数据源配置项

hive.url=jdbc:hive2://172.16.0.10:10000/default
hive.driver-class-name=org.apache.hive.jdbc.HiveDriver
hive.username=hadoop
hive.password=

用户名是需要具有 hdfs 写入权限，密码可以不用写

如果使用 yaml 格式 application.yml 配置如下

hive:  
  url: jdbc:hive2://172.16.0.10:10000/default
  driver-class-name: org.apache.hive.jdbc.HiveDriver 
  type: com.alibaba.druid.pool.DruidDataSource
  username: hive
  password: hive	

Configuration

package cn.netkiller.config;

import org.apache.tomcat.jdbc.pool.DataSource;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.beans.factory.annotation.Qualifier;
import org.springframework.context.annotation.Bean;
import org.springframework.context.annotation.Configuration;
import org.springframework.core.env.Environment;
import org.springframework.jdbc.core.JdbcTemplate;

@Configuration
public class HiveConfig {
	private static final Logger logger = LoggerFactory.getLogger(HiveConfig.class);

	@Autowired
	private Environment env;

	@Bean(name = "hiveJdbcDataSource")
	@Qualifier("hiveJdbcDataSource")
	public DataSource dataSource() {
		DataSource dataSource = new DataSource();
		dataSource.setUrl(env.getProperty("hive.url"));
		dataSource.setDriverClassName(env.getProperty("hive.driver-class-name"));
		dataSource.setUsername(env.getProperty("hive.username"));
		dataSource.setPassword(env.getProperty("hive.password"));
		logger.debug("Hive DataSource");
		return dataSource;
	}

	@Bean(name = "hiveJdbcTemplate")
	public JdbcTemplate hiveJdbcTemplate(@Qualifier("hiveJdbcDataSource") DataSource dataSource) {
		return new JdbcTemplate(dataSource);
	}
}

你也可以使用 DruidDataSource

package cn.netkiller.api.config; 

@Configuration  
public class HiveDataSource {  
      
    @Autowired  
    private Environment env;  
  
    @Bean(name = "hiveJdbcDataSource")
    @Qualifier("hiveJdbcDataSource")
    public DataSource dataSource() {
        DruidDataSource dataSource = new DruidDataSource();
        dataSource.setUrl(env.getProperty("hive.url"));
        dataSource.setDriverClassName(env.getProperty("hive.driver-class-name"));
        dataSource.setUsername(env.getProperty("hive.username"));
        dataSource.setPassword(env.getProperty("hive.password"));
        return dataSource;
    }

    @Bean(name = "hiveJdbcTemplate") 
    public JdbcTemplate hiveJdbcTemplate(@Qualifier("hiveJdbcDataSource") DataSource dataSource) {
        return new JdbcTemplate(dataSource);
    }

}

CURD 操作实例

Hive 数据库的增删插改操作与其他数据库没有什么不同。

package cn.netkiller.web;

import java.util.Iterator;
import java.util.List;
import java.util.Map;

import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.beans.factory.annotation.Qualifier;
import org.springframework.jdbc.core.JdbcTemplate;
import org.springframework.stereotype.Controller;
import org.springframework.web.bind.annotation.RequestMapping;
import org.springframework.web.servlet.ModelAndView;

@Controller
@RequestMapping("/hive")
public class HiveController {
	private static final Logger logger = LoggerFactory.getLogger(HiveController.class);

	@Autowired
	@Qualifier("hiveJdbcTemplate")
	private JdbcTemplate hiveJdbcTemplate;

	@RequestMapping("/create")
	public ModelAndView create() {

		StringBuffer sql = new StringBuffer("create table IF NOT EXISTS ");
		sql.append("HIVE_TEST");
		sql.append("(KEY INT, VALUE STRING)");
		sql.append("PARTITIONED BY (CTIME DATE)"); // 分区存储
		sql.append("ROW FORMAT DELIMITED FIELDS TERMINATED BY '\t' LINES TERMINATED BY '\n' "); // 定义分隔符
		sql.append("STORED AS TEXTFILE"); // 作为文本存储

		logger.info(sql.toString());
		hiveJdbcTemplate.execute(sql.toString());

		return new ModelAndView("index");

	}

	@RequestMapping("/insert")
	public String insert() {
		hiveJdbcTemplate.execute("insert into hive_test(key, value) values('Neo','Chen')");
		return "Done";
	}

	@RequestMapping("/select")
	public String select() {
		String sql = "select * from HIVE_TEST";
		List<Map<String, Object>> rows = hiveJdbcTemplate.queryForList(sql);
		Iterator<Map<String, Object>> it = rows.iterator();
		while (it.hasNext()) {
			Map<String, Object> row = it.next();
			System.out.println(String.format("%s\t%s", row.get("key"), row.get("value")));
		}
		return "Done";
	}

	@RequestMapping("/delete")
	public String delete() {
		StringBuffer sql = new StringBuffer("DROP TABLE IF EXISTS ");
		sql.append("HIVE_TEST");
		logger.info(sql.toString());
		hiveJdbcTemplate.execute(sql.toString());
		return "Done";
	}
}