Command Line

本页描述了 Hive 支持的不同 Client 端。命令行 Client 端当前仅支持嵌入式服务器。 JDBC 和 Thrift-JavaClient 端支持嵌入式服务器和独立服务器。其他语言的 Client 端仅支持独立服务器。

有关独立服务器的详细信息，请参见Hive Server或HiveServer2。

仅在嵌入式模式下运行，即它需要访问 Hive 库。有关更多详细信息，请参见Getting Started和Hive CLI。

JDBC

本文档描述了原始Hive Server(有时称为 Thrift 服务器或* HiveServer1 )的 JDBCClient 端.有关 HiveServer2 JDBCClient 端的信息，请参见HiveServer2Client 端文档中的 JDBC.推荐使用 HiveServer2；原始的 HiveServer 存在多个并发问题，并且缺少 HiveServer2 中提供的一些功能.*

对于嵌入式模式，uri 只是“ jdbc：hive：//”。对于独立服务器，uri 是“ jdbc：hive：// host：port/dbname”，其中主机和端口由 Hive 服务器的运行位置确定。例如，“ jdbc：hive：// localhost：10000/default”。当前，唯一支持的 dbname 是“默认”。

JDBCClient 端示例代码

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";

  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));
    }
  }
}

运行 JDBC 示例代码

# 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

安全集群的 JDBCClient 端设置

要在安全群集上配置 Hive，请将包含 hive-site.xml 的目录添加到 JDBCClient 端的 CLASSPATH。

Python

仅在独立服务器上运行。设置(并导出)PYTHONPATH 到 build/dist/lib/py。

以下代码中导入的 python 模块是通过构建 Hive 生成的。

请注意，生成的 python 模块名称在 hive trunk 中已更改。

#!/usr/bin/env python

import sys

from hive import ThriftHive
from hive.ttypes import HiveServerException
from thrift import Thrift
from thrift.transport import TSocket
from thrift.transport import TTransport
from thrift.protocol import TBinaryProtocol

try:
    transport = TSocket.TSocket('localhost', 10000)
    transport = TTransport.TBufferedTransport(transport)
    protocol = TBinaryProtocol.TBinaryProtocol(transport)

    client = ThriftHive.Client(protocol)
    transport.open()

    client.execute("CREATE TABLE r(a STRING, b INT, c DOUBLE)")
    client.execute("LOAD TABLE LOCAL INPATH '/path' INTO TABLE r")
    client.execute("SELECT * FROM r")
    while (1):
      row = client.fetchOne()
      if (row == None):
        break
      print row
    client.execute("SELECT * FROM r")
    print client.fetchAll()

    transport.close()

except Thrift.TException, tx:
    print '%s' % (tx.message)

PHP

仅在独立服务器上运行。

<?php
// set THRIFT_ROOT to php directory of the hive distribution
$GLOBALS['THRIFT_ROOT'] = '/lib/php/';
// load the required files for connecting to Hive
require_once $GLOBALS['THRIFT_ROOT'] . 'packages/hive_service/ThriftHive.php';
require_once $GLOBALS['THRIFT_ROOT'] . 'transport/TSocket.php';
require_once $GLOBALS['THRIFT_ROOT'] . 'protocol/TBinaryProtocol.php';
// Set up the transport/protocol/client
$transport = new TSocket('localhost', 10000);
$protocol = new TBinaryProtocol($transport);
$client = new ThriftHiveClient($protocol);
$transport->open();

// run queries, metadata calls etc
$client->execute('SELECT * from src');
var_dump($client->fetchAll());
$transport->close();

ODBC

仅在独立服务器上运行。 Hive ODBCClient 端提供了一组与 C 兼容的库函数，以类似于 ODBC 规范规定的模式与 Hive Server 进行交互。参见Hive ODBC 驱动程序。

Thrift

Thrift JavaClient 端

在嵌入式模式和独立服务器上均可运行。

Thrift CClient

仅在独立服务器上运行。在作品中。

节俭节点 Client 端

Thrift NodeClient 端可在 github 上的https://github.com/wdavidw/node-thrift-hive和https://github.com/forward/node-hive上获得。

Thrift RubyClient 端

Thrift RubyClient 端可在 github 上的https://github.com/forward3d/rbhive获得。