Spring boot with Hive-白红宇

Spring boot with Hive

阅读量：6590 次

发布时间：2019-06-24

本文共 5402 字，大约阅读时间需要 18 分钟。

本文节选自《Netkiller Java 手札》

作者：netkiller 他的网站: http://www.netkiller.cn, QQ: 13721218

5.29. Spring boot with Apache Hive

5.29.1. Maven


    			
     
      org.springframework.boot
     			
     
      spring-boot-starter-jdbc
     		
    		
    			
     
      org.springframework.data
     			
     
      spring-data-hadoop
     			
     
      2.5.0.RELEASE
     		
    		
    		
    			
     
      org.apache.hive
     			
     
      hive-jdbc
     			
     
      2.3.0
     			
     				
      					
       
        org.eclipse.jetty.aggregate
       					
       
        *
       				
      			
     		
    		
    			
     
      org.apache.tomcat
     			
     
      tomcat-jdbc
     			
     
      8.5.20

5.29.2. application.properties

hive 数据源配置项

hive.url=jdbc:hive2://172.16.0.10:10000/defaulthive.driver-class-name=org.apache.hive.jdbc.HiveDriverhive.username=hadoophive.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

5.29.3. 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;@Configurationpublic 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);    }}

5.29.4. 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		// drop table		// StringBuffer sql = new StringBuffer("DROP TABLE IF EXISTS ");		// sql.append("HIVE_TEST1");		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
     
      > rows = hiveJdbcTemplate.queryForList(sql);		Iterator
      
       
        > it = rows.iterator();		while (it.hasNext()) {			Map
        
          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";	}}