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帮助文档（华北一、二）

1. 使用JAVA连接HiveServer2(实现创建表格、加载数据，展示数据操作)

此示例需要您先登陆托管Hadoop集群master1节点，以下操作默认在master1节点执行

org.apache.hive.jdbc.HiveDriver是hiveserver2的dirvername，hiveserver2的访问地址是"jdbc:hive2://ip:10000/default"。

● 编写示例代码

示例代码Hive2JdbcClient.java如下：

import java.sql.SQLException;

import java.sql.Connection;

import java.sql.ResultSet;

import java.sql.Statement;

import java.sql.DriverManager;

public class Hive2JdbcClient {

private static String driverName = "org.apache.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);

}

//replace "hive" here with the name of the user the queries should run as

Connection con = DriverManager.getConnection("jdbc:hive2://uhadoop-******-

master2:10000/default", "", "");

Statement stmt = con.createStatement();

String tableName = "testHive2DriverTable";

stmt.execute("drop table if exists " + tableName);

stmt.execute("create table " + tableName + " (key int, value string)");

// show tables

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

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

ResultSet 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 = "/user/hive/warehouse/b.txt";

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

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

stmt.execute(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));

}

}

}

注解：

Connection con = DriverManager.getConnection("jdbc:hive2://uhadoop-******-master2:10000/default", "", "");

uhadoop-******-master2须改成您集群master2节点的主机名称或者IP。

- 编译

javac Hive2JdbcClient.java

● 执行程序

test.sh代码如下：

#!/bin/bash

hdfs dfs -rm /user/hive/warehouse/b.txt

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

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

hdfs dfs -put /tmp/b.txt /user/hive/warehouse/

HADOOP_HOME=/home/hadoop/

CLASSPATH=.:$HIVE_HOME/conf

for i in ${HADOOP_HOME}/share/hadoop/mapreduce/lib/hadoop-*.jar ; do

CLASSPATH=$CLASSPATH:$i

done

for i in ${HADOOP_HOME}/share/hadoop/mapreduce/hadoop-*.jar ; do

CLASSPATH=$CLASSPATH:$i

Done

for i in ${HADOOP_HOME}/share/hadoop/common/lib/hadoop-*.jar ; do

CLASSPATH=$CLASSPATH:$i

done

for i in ${HADOOP_HOME}/share/hadoop/common/hadoop-*.jar ; do

CLASSPATH=$CLASSPATH:$i

done

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

CLASSPATH=$CLASSPATH:$i

done

java -cp $CLASSPATH Hive2JdbcClient

2. 使用Python连接HiveServer2(实现创建表格、加载数据，展示数据操作)

Hiveserver2使用python客户端的过程如下：

● 下载pyhs2 git clone ：

https://github.com/BradRuderman/pyhs2.git

● 安装依赖：yum install gcc-c++ cyrus-sasl-* python-devel

● 安装setuptools：

wget -q http://peak.telecommunity.com/dist/ez_setup.py ./python ez_setup.py

如果上面方式安装失败需要手动下载setuptools-0.6c11.tar.gz安装包安装

- 编译安装pyhs2

进入pyhs2目录并安装

cd pyhs2

python setup.py build

python setup.py install

编写示例代码

示例代码，即pyhs2下example.py

import pyhs2

with pyhs2.connect(host='uhadoop-******-master2',

port=10000,

authMechanism="PLAIN",

user='root',

password='test',

database='default') as conn:

with conn.cursor() as cur:

#Show databases

print cur.getDatabases()

#Execute query

cur.execute("select * from test_hive")

#Return column info from query

print cur.getSchema()

#Fetch table results

for i in cur.fetch():

print i

3. Hive外表读取HBase数据

通过在Hive中创建HBase外表，可利用简单的sql语句分析HBase的非结构化数据

打开HBase shell，创建t1表

create 't1',{NAME => 'f1',VERSIONS => 2}

put 't1','rowkey001','f1:col1','value01'

put 't1','rowkey001','f1:col2','value02'

put 't1','rowkey001','f1:colf','value03'

scan 't1'

得到的t1表结构如下：

hbase(main):013:0> scan 't1'

ROW COLUMN+CELL

rowkey001 column=f1:col1,

timestamp=1481075364575, value=value01

rowkey001 column=f1:col2,

timestamp=1481075364607, value=value02

rowkey001 column=f1:colf,

timestamp=1481075364641, value=value03

打开Hive Cli，创建外表：

hive> CREATE EXTERNAL TABLE t_hive_hbase(

> rowkey string,

> cf map<STRING,STRING>

> )

> STORED BY 'org.apache.hadoop.hive.hbase.HBaseStorageHandler'

> WITH SERDEPROPERTIES ("hbase.columns.mapping" = ":key,f1:")

> TBLPROPERTIES ("hbase.table.name" = "t1");

使用sql语句读取hbase数据，结果如下：

hive> select * from t_hive_hbase;

OK

rowkey001 {"col1":"value01","col2":"value02","colf":"value03"}