精华内容
下载资源
问答
  • 将统计信息导出到HDFS上,导出了3个字段,HIVE默认字段分隔符为'\001',我将导出到HDFS的数据拷贝到了本地D盘重命名为testdata,尝试解析它,解析代码如下: public static void main(String[] args) throws ...

    通过HQL语句:

    insert overwrite directory '/COMP/206/OUT/LDAPD_BUSI_CMNCTN_ACCU/${current_date}'

    select callingnum,custphone,count(*) as callcount

    from DAPD_VOICE_LOG_TMP

    group by callingnum,custphone;

    将统计信息导出到HDFS上,导出了3个字段,HIVE默认字段分隔符为'\001',我将导出到HDFS的数据拷贝到了本地D盘重命名为testdata,尝试解析它,解析代码如下:

    public static void main(String[] args) throws Exception {

    // TODO Auto-generated method stub

    FileReader reader = new FileReader("d:\\testdata");

    BufferedReader br = new BufferedReader(reader);

    String line = "";

    String[] arrs = null;

    while ((line = br.readLine()) != null) {

    byte[] bytes = new byte[] { 1 };

    String sendString = new String(bytes, "GBK");

    arrs = line.split(sendString);

    System.out.println(arrs[0] + " : " + arrs[1] + " : " + arrs[2]);

    }

    br.close();

    reader.close();

    }

    输出为:

    13860393195 : 114 : 1

    15280154404 : 0591-87677500 : 1

    18059386085 : 0593-7668885 : 1

    说明可以被正确的解析。

    展开全文
  • Java 读取Hive

    千次阅读 2021-01-12 13:08:21
    Java读取HDFS/Hive表的代码1.[代码][Java]代码import java.io.BufferedReader;import java.io.IOException;import java.io.InputStreamReader;import java.net.URI;import org.apache.hadoop.conf.Configuration;...

    Java读取 HDFS/Hive 表的代码

    1.[代码][Java]代码

    import java.io.BufferedReader;

    import java.io.IOException;

    import java.io.InputStreamReader;

    import java.net.URI;

    import org.apache.hadoop.conf.Configuration;

    import org.apache.hadoop.fs.FSDataInputStream;

    import org.apache.hadoop.fs.FileSystem;

    import org.apache.hadoop.fs.Path;

    import org.apache.hadoop.io.IOUtils;

    public class ReadHDFS {

    public static void main(String[] argvs){

    Configuration conf = new Configuration();

    //String uri = "hdfs://xxxx:8020" + "/user/hive/warehouse/lib/col_iplib.txt";

    String uri = "hdfs://xxxx:8020" + "/user/hive/warehouse/snapshot.db/stat_all_info/stat_date=20150913/softid=201/000000_0";

    FileSystem fs = null;

    FSDataInputStream in = null;

    BufferedReader br = null;

    try {

    fs = FileSystem.get(URI.create(uri), conf);

    in = fs.open(new Path(uri));

    br = new BufferedReader(new InputStreamReader(in));

    String readline;

    int counter = 0;

    while ((readline = br.readLine()) != null && counter <=10) {

    String[] pars = readline.split("\001");

    System.out.println(pars[12]);

    counter++;

    }

    } catch (IOException e) {

    System.out.println(e.getMessage());

    } finally {

    IOUtils.closeStream(in);

    }

    }

    }

    展开全文
  • } } 数据源util层: DruidDataSourceFactory: package org.example; import com.alibaba.druid.pool.DruidDataSource; import org.apache.ibatis.datasource.DataSourceFactory; import javax.sql.DataSource; ...

    在这里插入图片描述

    1.pom文件需要的依赖

        <!-- https://mvnrepository.com/artifact/mysql/mysql-connector-java -->
        <dependency>
          <groupId>mysql</groupId>
          <artifactId>mysql-connector-java</artifactId>
          <version>5.1.38</version>
        </dependency>
       <!-- https://mvnrepository.com/artifact/org.apache.spark/spark-hive -->
        <dependency>
          <groupId>org.apache.spark</groupId>
          <artifactId>spark-hive_2.11</artifactId>
          <version>2.4.4</version>
        </dependency>
        <!-- https://mvnrepository.com/artifact/org.mybatis/mybatis -->
        <dependency>
          <groupId>org.mybatis</groupId>
          <artifactId>mybatis</artifactId>
          <version>3.4.6</version>
        </dependency>
        <!-- https://mvnrepository.com/artifact/com.alibaba/druid -->
        <dependency>
          <groupId>com.alibaba</groupId>
          <artifactId>druid</artifactId>
          <version>1.1.10</version>
        </dependency>
        <!-- https://mvnrepository.com/artifact/org.apache.hive/hive-jdbc -->
        <dependency>
          <groupId>org.apache.hive</groupId>
          <artifactId>hive-jdbc</artifactId>
          <version>1.1.0</version>
        </dependency>
    

    2.xml文件配置
    mybatis-xml:

    <?xml version="1.0" encoding="UTF-8" ?>
    <!DOCTYPE configuration PUBLIC
            "-//mybatis.org//DTD Config 3.0//EN"
            "http://mybatis.org/dtd/mybatis-3-config.dtd">
    <configuration>
        <typeAliases>
            <typeAlias type="org.example.DruidDataSourceFactory" alias="DRUID"></typeAlias>
            <typeAlias type="org.entry.Events" alias="event"></typeAlias>
        </typeAliases>
        <environments default="zjy">
            <environment id="zjy">
                <transactionManager type="JDBC"></transactionManager>
                <dataSource type="DRUID">
                    <property name="driver" value="com.mysql.jdbc.Driver"/>
                    <property name="url" value="jdbc:mysql://192.168.181.132:3306/ms_dm_intes"/>
                    <property name="username" value="root"/>
                    <property name="password" value="root"/>
                </dataSource>
            </environment>
            <environment id="zjy1">
                <transactionManager type="JDBC"></transactionManager>
                <dataSource type="DRUID">
                    <property name="driver" value="org.apache.hive.jdbc.HiveDriver"/>
                    <property name="url" value="jdbc:hive2://192.168.181.132:10000/dwd_intes"/>
                    <property name="username" value=""/>
                    <property name="password" value=""/>
                </dataSource>
            </environment>
        </environments>
    
        <mappers>
            <mapper resource="mapper/mysql-events.xml"></mapper>
            <mapper resource="mapper/hive-events.xml"></mapper>
        </mappers>
    </configuration>
    

    hive-events.xml:

    <?xml version="1.0" encoding="UTF-8" ?>
    <!DOCTYPE mapper PUBLIC
            "-//mybatis.org//DTD Mapper 3.0//EN"
            "http://mybatis.org/dtd/mybatis-3-mapper.dtd">
    <mapper namespace="org.dao.HiveEventDAO">
        <select id="findAll" resultType="java.util.Map" parameterType="int">
            select eventid,userid,starttime,city,states,zip,country,lat,lng,features from dwd_intes.tmp where flag=#{flag}
        </select>
    </mapper>
    

    mysql-events.xml:

    <?xml version="1.0" encoding="UTF-8" ?>
    <!DOCTYPE mapper PUBLIC
            "-//mybatis.org//DTD Mapper 3.0//EN"
            "http://mybatis.org/dtd/mybatis-3-mapper.dtd">
    <mapper namespace="org.dao.MySQLEventDAO">
        <insert id="batchInsert" parameterType="java.util.List">
            insert into dm_events_bak1 values
            <foreach collection="list" item="eve" separator=",">
                (
                #{eve.eventid},#{eve.userid},#{eve.starttime},#{eve.city},
                #{eve.states},#{eve.zip},#{eve.country},#{eve.lat},#{eve.lng},#{eve.features}
                )
            </foreach>
        </insert>
    </mapper>
    

    3.JAVA代码

    dao层:
    

    HiveEventDAO

    package org.dao;
    
    import org.entry.Events;
    
    import java.util.List;
    import java.util.Map;
    
    public interface HiveEventDAO {
        public List<Events>findAll(int page);
    }
    
    

    MySQLEventDAO:

    package org.dao;
    
    import org.entry.Events;
    
    import java.util.List;
    
    public interface MySQLEventDAO {
        public List<Events> findAll();
        public void batchInsert(List<Events>evs);
    }
    
    
    实体类entry层:
    

    Events:

    package org.entry;
    
    public class Events {
        private String eventid;
        private String userid;
        private String starttime;
        private String city;
        private String states;
        private String zip;
        private String country;
        private String lat;
        private String lng;
        private String features;
    
        public String getEventid() {
            return eventid;
        }
    
        public void setEventid(String eventid) {
            this.eventid = eventid;
        }
    
        public String getUserid() {
            return userid;
        }
    
        public void setUserid(String userid) {
            this.userid = userid;
        }
    
        public String getStarttime() {
            return starttime;
        }
    
        public void setStarttime(String starttime) {
            this.starttime = starttime;
        }
    
        public String getCity() {
            return city;
        }
    
        public void setCity(String city) {
            this.city = city;
        }
    
        public String getStates() {
            return states;
        }
    
        public void setStates(String states) {
            this.states = states;
        }
    
        public String getZip() {
            return zip;
        }
    
        public void setZip(String zip) {
            this.zip = zip;
        }
    
        public String getCountry() {
            return country;
        }
    
        public void setCountry(String country) {
            this.country = country;
        }
    
        public String getLat() {
            return lat;
        }
    
        public void setLat(String lat) {
            this.lat = lat;
        }
    
        public String getLng() {
            return lng;
        }
    
        public void setLng(String lng) {
            this.lng = lng;
        }
    
        public String getFeatures() {
            return features;
        }
    
        public void setFeatures(String features) {
            this.features = features;
        }
    }
    
    
    数据源util层:
    

    DruidDataSourceFactory:

    package org.example;
    
    import com.alibaba.druid.pool.DruidDataSource;
    import org.apache.ibatis.datasource.DataSourceFactory;
    
    import javax.sql.DataSource;
    import java.sql.SQLException;
    import java.util.Properties;
    
    public class DruidDataSourceFactory implements DataSourceFactory
    {
        private Properties prop;
        @Override
        public void setProperties(Properties properties) {
            this.prop=properties;
        }
    
        @Override
        public DataSource getDataSource() {
            DruidDataSource druid = new DruidDataSource();
            druid.setDriverClassName(this.prop.getProperty("driver"));
            druid.setUrl(this.prop.getProperty("url"));
            druid.setUsername(this.prop.getProperty("username"));
            druid.setPassword(this.prop.getProperty("password"));
    //        druid.setMaxActive(Integer.parseInt(this.prop.getProperty("maxactive")));
    //        druid.setInitialSize(Integer.parseInt(this.prop.getProperty("initialsize")));
            try {
                druid.init();
            } catch (SQLException e) {
                e.printStackTrace();
            }
            return druid;
        }
    }
    
    

    DatabaseUtils:

    package org.example;
    
    import org.apache.ibatis.io.Resources;
    import org.apache.ibatis.session.SqlSession;
    import org.apache.ibatis.session.SqlSessionFactory;
    import org.apache.ibatis.session.SqlSessionFactoryBuilder;
    
    import java.io.IOException;
    import java.io.InputStream;
    
    public class DatabaseUtils {
        private static final String configPath="mybatis-config.xml";
    
        public static SqlSession getSession(String db){
            SqlSession session = null;
            try {
                InputStream is = Resources.getResourceAsStream(configPath);
                SqlSessionFactory factory = new SqlSessionFactoryBuilder().build(is,db.equals("mysql")?"zjy":"zjy1");
                session = factory.openSession();
            } catch (IOException e) {
                e.printStackTrace();
            }
    
            return session;
    
        }
        public static void close(SqlSession session){
            session.close();
        }
    }
    
    
    services层:
    
    package org.services;
    
    import org.apache.ibatis.session.SqlSession;
    import org.dao.HiveEventDAO;
    import org.dao.MySQLEventDAO;
    import org.entry.Events;
    import org.example.DatabaseUtils;
    import java.util.List;
    
    
    public class HiveToMySqlService {
        private List<Events> change(int page){
            //通过hiveeventdao查找hive中的数据
            SqlSession hiveSession = DatabaseUtils.getSession("hive");
            HiveEventDAO hivedao = hiveSession.getMapper(HiveEventDAO.class);
    
            List<Events> lst = hivedao.findAll(page);
            return lst;
        }
    
        public void fillMySql(){
            //准备mysql的数据库连接
            SqlSession session = DatabaseUtils.getSession("mysql");
            MySQLEventDAO medao = session.getMapper(MySQLEventDAO.class);
    
            //调用转换方法获取hive中的数据
            for (int i = 0; i <= 627; i++) {
                List<Events> eves = change(i);
                medao.batchInsert(eves);
                session.commit();
            }
    
        }
    
    }
    
    
    运行层:
    
    package org.example;
    
    import org.services.HiveToMySqlService;
    
    
    public class App 
    {
        public static void main(String[] args)
        {
            HiveToMySqlService hts = new HiveToMySqlService();
            hts.fillMySql();
        }
    }
    
    

    由于service层的中是hive每次读取5000条数据,就往mysql里面塞5000条,而程序中hive读取数据的速度是远大于5000的,所以对这个类进行了优化

    package org.services;
    
    import org.apache.ibatis.session.SqlSession;
    import org.dao.HiveDao;
    import org.dao.MysqlDao;
    import org.entry.Events;
    import org.util.DatabaseUtil;
    
    import java.util.ArrayList;
    import java.util.List;
    
    public class HiveToMysql {
        static HiveDao hdao;
        static{
            SqlSession hiveSession = DatabaseUtil.getSession("hive");
            hdao = hiveSession.getMapper(HiveDao.class);
        }
    
    
        public void fillMysql(){
            SqlSession mysqlSession = DatabaseUtil.getSession("mysql");
            MysqlDao mdao = mysqlSession.getMapper(MysqlDao.class);
            //本来对hive的数据进行开窗row_number排序,在对序号进行取余操作得到另一列flag,本来是对5000取余,所以之前的类中循环写的到627,这一次对hive读取数据优化,所以加大了每次读取的量,对50000取余,所以得到62组
            for (int flag = 0; flag < 63; flag++) {
                List<Events> eves = hdao.findAll(flag);
                //创建数组用来存放每组flag的数据,插入到mysql后,再清空
                List<Events> tmpdata = new ArrayList<>();
                for (int i = 1; i <= eves.size(); i++) {
                    tmpdata.add(eves.get(i-1));
                    if (i%8000==0||i==eves.size()) {
                    //当临时存放数据的数组存放到8000条时,或者到最后一个flag不满8000但是长度达到hive中数据的长度时,mysql就提交批量插入
                        mdao.batchInsert(tmpdata);
                        mysqlSession.commit();
                        tmpdata.clear();
                    }
                }
            }
        }
    }
    
    
    展开全文
  • 如果是CDH,设置如下:# export HIVE_HOME=/opt/cloudera/parcels/CDH-5.16.1-1.cdh5.16.1.p0.3/lib/hive执行导入# bin/import-hive.sh...Failed to import Hive Meta Data!!!报错,查看日志#more...

    首先要有HIVE_HOME环境变量,

    如果是apache,直接配置为解压目录;如果是CDH,设置如下:

    # export HIVE_HOME=/opt/cloudera/parcels/CDH-5.16.1-1.cdh5.16.1.p0.3/lib/hive

    执行导入

    # bin/import-hive.sh

    ...

    Failed to import Hive Meta Data!!!

    报错,查看日志

    #more logs/import-hive.log

    2020-01-11 14:42:38,951 INFO - [main:] ~ Looking for atlas-application.properties in classpath (ApplicationProperties:110)2020-01-11 14:42:38,955 INFO - [main:] ~ Looking for /atlas-application.properties in classpath (ApplicationProperties:115)2020-01-11 14:42:38,956 INFO - [main:] ~ Loading atlas-application.properties from null (ApplicationProperties:123)2020-01-11 14:42:38,984 ERROR - [main:] ~ Import failed (HiveMetaStoreBridge:176)

    org.apache.atlas.AtlasException: Failed to load application properties

    at org.apache.atlas.ApplicationProperties.get(ApplicationProperties.java:134)

    at org.apache.atlas.ApplicationProperties.get(ApplicationProperties.java:86)

    at org.apache.atlas.hive.bridge.HiveMetaStoreBridge.main(HiveMetaStoreBridge.java:120)

    Caused by: org.apache.commons.configuration.ConfigurationException: Cannot locate configuration source null

    at org.apache.commons.configuration.AbstractFileConfiguration.load(AbstractFileConfiguration.java:259)

    at org.apache.commons.configuration.AbstractFileConfiguration.load(AbstractFileConfiguration.java:238)

    at org.apache.commons.configuration.AbstractFileConfiguration.(AbstractFileConfiguration.java:197)

    at org.apache.commons.configuration.PropertiesConfiguration.(PropertiesConfiguration.java:284)

    at org.apache.atlas.ApplicationProperties.(ApplicationProperties.java:69)

    at org.apache.atlas.ApplicationProperties.get(ApplicationProperties.java:125)

    ...2 more

    提示找不到atlas-application.properties,将其拷贝到hive conf目录

    # cp conf/atlas-application.properties /etc/hive/conf/

    再次执行

    #bin/import-hive.sh

    ...

    Enter usernamefor atlas :-admin

    Enter passwordfor atlas :-Exceptionin thread "main" java.lang.NoClassDefFoundError: com/fasterxml/jackson/jaxrs/json/JacksonJaxbJsonProvider

    at org.apache.atlas.AtlasBaseClient.getClient(AtlasBaseClient.java:270)

    at org.apache.atlas.AtlasBaseClient.initializeState(AtlasBaseClient.java:453)

    at org.apache.atlas.AtlasBaseClient.initializeState(AtlasBaseClient.java:448)

    at org.apache.atlas.AtlasBaseClient.(AtlasBaseClient.java:132)

    at org.apache.atlas.AtlasClientV2.(AtlasClientV2.java:82)

    at org.apache.atlas.hive.bridge.HiveMetaStoreBridge.main(HiveMetaStoreBridge.java:131)

    Caused by: java.lang.ClassNotFoundException: com.fasterxml.jackson.jaxrs.json.JacksonJaxbJsonProvider

    at java.net.URLClassLoader.findClass(URLClassLoader.java:381)

    at java.lang.ClassLoader.loadClass(ClassLoader.java:424)

    at sun.misc.Launcher$AppClassLoader.loadClass(Launcher.java:335)

    at java.lang.ClassLoader.loadClass(ClassLoader.java:357)

    ...6more

    Failed toimport Hive Meta Data!!!

    还是报错,提示找不到类,从server目录下拷贝到hook/hive目录下

    #cp server/webapp/atlas/WEB-INF/lib/jackson-jaxrs-1.8.3.jar hook/hive/atlas-hive-plugin-impl/#cp server/webapp/atlas/WEB-INF/lib/jackson-jaxrs-json-provider-2.9.2.jar hook/hive/atlas-hive-plugin-impl/#cp server/webapp/atlas/WEB-INF/lib/jackson-module-jaxb-annotations-2.9.8.jar hook/hive/atlas-hive-plugin-impl/

    再次执行成功,到atlas里可以看到hive相关数据

    导入成功

    展开全文
  • 通过Hcatalog的java接口,获取hive表的元数据信息一、获取hive表元数据的方式:1、通过hive的beeline客户端命令获取表元数据,如在beeline客户端中执行desc tablename;2、通过hive的jdbc接口获取获取表元数据;3、...
  • 1866) at org.apache.hadoop.ipc.Server$Handler.run(Server.java:2345) 3、将数据上传到hdfs中时,设置的分隔符必须和建表时设置的分割符相同,不然查询到的数据是null 建表时设置分隔符的命令: CREATE TABLE ...
  • 模板概述基于 Antlr4 编译 hive 相关 xxx.g 文件生成对应的模板,如 hive 源码中:image.png编译完成生成对应 *.java 文件,Antlr4 详见:Antlr4解析流程Parserimage.png重点:获取SELECT操作中的表和列的相关操作。...
  • 注意:将mysql的驱动包拷贝到spark/lib下,将hive-site.xml拷贝到项目resources下,远程调试不要使用主机名import org.apache.spark._import org.apache.spark.SparkConfimport org.apache.spark.SparkContextimport...
  • flink 读取hive数据

    2021-02-05 05:16:04
    flink1.8 对hive 的支持不够好,造成300W的数据,居然读了2个小时,打算将程序迁移至spark。 先把代码贴上mavenorg.apache.hivehive-jdbc1.1.0org.apache.hadoophadoop-common3.1.2jdk.toolsjdk.tools1.8system${...
  • hive精确数据类型

    2021-02-26 14:09:43
    hive也支持varchar,date,datetime,decaimal等类型,下面对这些类型与关系型数据库的差别进行探索。```create table test.type_tab(id bigint,col1 varchar(10),col2 date,col3 timestamp,col4 decimal(22,6));...
  • spark读取hive数据的两种方式

    千次阅读 2021-06-04 13:05:30
    spark读取hive数据常用的有两种方式 一是通过访问hive metastore的方式,这种方式通过访问hive的metastore元数据的方式获取表结构信息和该表数据所存放的HDFS路径,这种方式的特点是效率高、数据量大、使用spark...
  • 使用bin/sql-client.sh embedded 进入客户端,查询hive中表数据 现象1:创建的hive小表src,type: streaming flinksql是可以读取的。type: batch flinksql可以读取。 现象2:创建flink的kafka user_log流表
  • 1、pom依赖 <dependency>...org.apache.hive</groupId> <artifactId>hive-jdbc</artifactId> <version>${hive.version}</version> </dependency> <dependen
  • 1,mr代码如下package ...import java.io.IOException;import org.apache.hadoop.conf.Configuration;import org.apache.hadoop.fs.Path;import org.apache.hadoop.io.NullWritable;import org.apache.hadoo...
  • java jdbc查询hive数据,并将结果存为列表显示 1.代码 import java.sql.*; import java.util.ArrayList; import java.util.HashMap; import java.util.List; import java.util.Map; public class HiveConnect { ...
  • 1.首先将集群的这3个文件hive-site.xml,core-size.xml,hdfs-site.xml放到资源文件里(必须,否则报错)2.代码方面。下面几个测试都可以运行。1)test03.javaimport org.apache.spark.sql.SparkSession;import java....
  • 我想使用Javahive中创建一个表.使用以下方法执行此操作:public class HiveCreateTable {private static String driverName = "com.facebook.presto.jdbc.PrestoDriver";public static void main(String[] args) ...
  • 第一步,启动hadoop,命令:./start-all.sh第二步,启动hive,命令:./hive --auxpath /home/dream-victor/hive-0.6.0/lib/hive_hbase-handler.jar,/home/dream-victor/hive-0.6.0/lib/hbase-0.20.3.jar,/home/dream...
  • Hive数据同步到es

    2021-03-15 01:18:09
    这种加载本地文件数据hive表中,在beeline中识别不到本地路径,可能是beeline的sever多台,所以识别不到,只能用hdfs系统导入,如下 load data inpath '/user/projectquene001/publictest/wb.txt' into table wb_...
  • Hivejava对数据库、表的操作

    千次阅读 2021-03-14 19:40:01
    在应用Hive之前,首先搭建Hive环境,关于Hive的搭建 参考之前的搭建文档java代码执行Hive脚本java代码执行Hive脚本,需要启动Hive的内部服务,供其他或者java代码链接,Hive内部服务启动命令# ./hive --service ...
  • Java API操作Hive

    2020-12-20 11:25:14
    环境:IDEA2017.3+Maven-3.3.9+Hive1.1.01. pom.xml里面的依赖包配置1.1.0org.apache.hivehive-jdbc${hive.version}2. 新建HiveJdbcClient.java 文件package com.ruozedata.day6;import java.sql.*;public class ...
  • package com.nbdpt.work4_hive2hbase2019 import com.nbdpt.util.BaseUtil import org.apache.hadoop.hbase.client.{ConnectionFactory, Get, Put} import org.apache.hadoop.hbase.io.ImmutableBytesWritable ...
  • 通过hive元数据获取hive分区表的元数据信息 通过hive元数据获取hive分区表的元数据信息 项目中需要获取hive所有分区表的分区信息并显示到页面 如图 方案:通过JDBC连接hive数据库,sql语句实现 编写sql语句:...
  • importjava.io.FileNotFoundException;importjava.io.IOException;importorg.apache.hadoop.conf.Configuration;importorg.apache.hadoop.fs.FileStatus;importorg.apache.hadoop.fs.FileSyst...
  • 本文中的代码,在本地使用Java程序生成ORC文件,然后加载到Hive表。代码如下:package com.lxw1234.hive.orc;import org.apache.hadoop.conf.Configuration;import org.apache.hadoop.fs.FileSy...
  • 本篇博客,小菌为大家带来关于如何将本地的多个文件导入到Hive分区表中对应的分区上的方法。一共有四种方法,本篇将介绍第一种—Java代码。首先编写代码,通过MapReduce将处理好的数据写入到HDFS的目录下。下面提供一种...
  • I want to pass the location of hive-site.xml file in my java program.What is the best way to find out the location of this file automatically in java code?I do not want to hard code the path to /etc/h...
  • Spark通过HiveServer2 JDBC方式访问Hive数据(Java语言) 1、环境信息准备 jdbc连接url ,通常都是 端口为10000的连接 jdbc用户名 jdbc密码 2、代码实战 public static void main(String[] args) { SparkConf...
  • 问题:Caused by: java.util.concurrent.ExecutionException: java.lang.IndexOutOfBoundsException: Index: 0at java.util.concurrent.FutureTask.report(FutureTask.java:122)at java.util.concurrent.FutureTask....

空空如也

空空如也

1 2 3 4 5 ... 20
收藏数 36,934
精华内容 14,773
关键字:

java读取hive源数据

java 订阅