hive中配置使用derby.

hive-default.xml


<property>
  <name>javax.jdo.option.ConnectionURL</name>
  <value>jdbc:derby:;databaseName=metastore_db;create=true</value> 表示使用嵌入式的derby，create为true表示自动创建数据库，数据库名为metastore_db
  <!--<value>jdbc:derby://192.168.0.3:4567/hadoopor;create=true</value>--> 表示使用客服模式的derby，hadoopor为数据库名，192.168.0.3为derby服务端的IP地址，而4567为服务端的端口号
  <description>JDBC connect string for a JDBC metastore</description>
</property>

<property>
  <name>javax.jdo.option.ConnectionDriverName</name>
  <value>org.apache.derby.jdbc.EmbeddedDriver</value> 表示使用嵌入式的derby
  <!--<value>org.apache.derby.jdbc.ClientDriver</value>--> 表示使用客服模式的derby
  <description>Driver class name for a JDBC metastore</description>
</property>


对于嵌入式的derby要求在hive的lib目录下有文件derby.jar，而对于客服模式的derby要求有derbyclient.jar文件

如果是derby坏了，就得把metastore_db删除就好了，不过以前的数据也没了，我觉得测试的时候用derby还行，如果正式上线的话就不要启动嵌入式的了，直接启动并连接线上服务器就ok了。不然metastore_db一加锁，启动了hive --service hiveserver就不能启动hive 启动了hive就不能启动hive --service hiveserver。

 

说明：

测试的时候使用嵌入式还可以，正式环境一定要用服务端模式，否则出了问题就没法恢复了。

可以选择任何你熟悉的语言类作为JDBC连接：

import java.sql.SQLException;

import java.sql.Connection;

import java.sql.ResultSet;

import java.sql.Statement;

import java.sql.DriverManager;

 

public class HiveJdbcClient {

  private static String driverName = "org.apache.hadoop.hive.jdbc.HiveDriver";

 

  /**

 * @param args

 * @throws SQLException

   */

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

      try {

      Class.forName(driverName);

    } catch (ClassNotFoundException e) {

      // TODO Auto-generated catch block

      e.printStackTrace();

      System.exit(1);

    }

    Connection con = DriverManager.getConnection("jdbc:hive://localhost:10000/default", "", "");

    Statement stmt = con.createStatement();

    String tableName = "testHiveDriverTable";

    stmt.executeQuery("drop table " + tableName);

    ResultSet res = stmt.executeQuery("create table " + tableName + " (key int, value string)");

    // show tables

    String sql = "show tables '" + tableName + "'";

    System.out.println("Running: " + sql);

    res = stmt.executeQuery(sql);

    if (res.next()) {

      System.out.println(res.getString(1));

    }

    // describe table

    sql = "describe " + tableName;

    System.out.println("Running: " + sql);

    res = stmt.executeQuery(sql);

    while (res.next()) {

      System.out.println(res.getString(1) + "\t" + res.getString(2));

    }

 

    // load data into table

    // NOTE: filepath has to be local to the hive server

    // NOTE: /tmp/a.txt is a ctrl-A separated file with two fields per line

    String filepath = "/tmp/a.txt";

    sql = "load data local inpath '" + filepath + "' into table " + tableName;

    System.out.println("Running: " + sql);

    res = stmt.executeQuery(sql);

 

    // select * query

    sql = "select * from " + tableName;

    System.out.println("Running: " + sql);

    res = stmt.executeQuery(sql);

    while (res.next()) {

      System.out.println(String.valueOf(res.getInt(1)) + "\t" + res.getString(2));

    }

 

    // regular hive query

    sql = "select count(1) from " + tableName;

    System.out.println("Running: " + sql);

    res = stmt.executeQuery(sql);

    while (res.next()) {

      System.out.println(res.getString(1));

    }

  }

}

接下来做的工作即是运行了：

# Then on the command-line

$ javac HiveJdbcClient.java

# To run the program in standalone mode, we need the following jars in the classpath

# from hive/build/dist/lib

#     hive_exec.jar

#     hive_jdbc.jar

#     hive_metastore.jar

#     hive_service.jar

#     libfb303.jar

#     log4j-1.2.15.jar

#

# from hadoop/build

#     hadoop-*-core.jar

#

# To run the program in embedded mode, we need the following additional jars in the classpath

# from hive/build/dist/lib

#     antlr-runtime-3.0.1.jar

#     derby.jar

#     jdo2-api-2.1.jar

#     jpox-core-1.2.2.jar

#     jpox-rdbms-1.2.2.jar

#

# as well as hive/build/dist/conf

$ java -cp $CLASSPATH HiveJdbcClient

# Alternatively, you can run the following bash script, which will seed the data file

# and build your classpath before invoking the client.

#!/bin/bash

HADOOP_HOME=/your/path/to/hadoop

HIVE_HOME=/your/path/to/hive

echo -e '1\x01foo' > /tmp/a.txt

echo -e '2\x01bar' >> /tmp/a.txt

HADOOP_CORE={{ls $HADOOP_HOME/hadoop-*-core.jar}}

CLASSPATH=.:$HADOOP_CORE:$HIVE_HOME/conf

for i in ${HIVE_HOME}/lib/*.jar ; do

    CLASSPATH=$CLASSPATH:$i

done

java -cp $CLASSPATH HiveJdbcClient