Hive環(huán)境搭建

1. hive下載：http://archive-primary.cloudera.com/cdh5/cdh/5/hive-1.1.0-cdh5.7.0.tar.gz
   wget http://archive-primary.cloudera.com/cdh5/cdh/5/hive-1.1.0-cdh5.7.0.tar.gz

2. 解壓
   tar -zxvf hive-1.1.0-cdh5.7.0.tar.gz -C ../apps/

3. 系統(tǒng)環(huán)境變量（vim ~/.bash_profile）

    export HIVE_HOME=/root/apps/hive-1.1.0-cdh5.7.0
    export PATH=$HIVE_HOME/bin:$PATH
    source ~/.bash_profile

4. 配置

    4.1 $HIVE_HOME/conf/hive-env.sh 中導(dǎo)出Hadoop_Home
    4.2 拷貝mysql 驅(qū)動架包到$HIVE_HOME/lib

4.3 vim hive-site.xml

<?xml version="1.0"?>
    <?xml-stylesheet type="text/xsl" href="configuration.xsl"?>
    <configuration>
        <property>
            <name>javax.jdo.option.ConnectionURL</name>
            <value>jdbc:mysql://spark003:3306/hive?createDatabaseIfNotExist=true</value>
        </property>
        <property>
            <name>javax.jdo.option.ConnectionDriverName</name>
            <value>com.mysql.jdbc.Driver</value>
        </property>
        <property>
            <name>javax.jdo.option.ConnectionUserName</name>
            <value>root</value>
        </property>
        <property>
            <name>javax.jdo.option.ConnectionPassword</name>
            <value>123456</value>
        </property>
    </configuration>

5. 啟動Hive： $HIVE_HOME/bin/hive

Hive的基本使用

創(chuàng)建表

create table test_table(name string);

加載本地數(shù)據(jù)到hive表【local方式】

load data local inpath '/home/hadoop/data/hello.txt' into table test_table;

查詢，統(tǒng)計，詞頻的個數(shù)：
select * from test_table;

select word, count(1) from test_table lateral view explode(split(name),'\t') wc as word group by word;

小案例

create table emp(
empno int,
ename string,
job string,
mgr int,
sal double,
comm double,
deptno int
)row format delimited fields terminated by '\t';

create table dept(
deptno int,
dname string,
location string
)row format delimited fields terminated by '\t';

load data local inpath '/home/hadoop/data/emp.txt' into table emp;
load data local inpath '/home/hadoop/data/dept.txt' into table dept;

統(tǒng)計分析：
求每個部門的人數(shù)：
select deptno,count(1) from emp group by deptno;

Spark SQL 與Hive集成（spark-shell）

1. 將hive的配置文件hive-site.xml拷貝到spark conf目錄，同時添加metastore的url配置。

<?xml version="1.0"?>
    <?xml-stylesheet type="text/xsl" href="configuration.xsl"?>
<configuration>
<property>
        <name>hive.metastore.uris</name>
        <value>thrift://spark001:9083</value>
</property>
</configuration>

2. mysql jar包到 spark 的 lib 目錄下

[root@spark001 lib]# pwd
/root/apps/spark-2.2.0-bin-2.6.0-cdh5.7.0/lib
[root@spark001 lib]# ll
total 972
-rw-r--r--. 1 root root 992805 Oct 23 23:59 mysql-connector-java-5.1.41.jar

3. 修改spark-env.sh 文件中的配置

操作： vim spark-env.sh，添加如下內(nèi)容：

export JAVA_HOME=/root/apps/jdk1.8.0_144
export SPARK_HOME=/root/apps/spark-2.2.0-bin-2.6.0-cdh5.7.0
export SCALA_HOME=/root/apps/scala-2.11.8
#新添加下面的這一條
export HADOOP_CONF_DIR=/root/apps/spark-2.2.0-bin-2.6.0-cdh5.7.0/etc/hadoop

4. 啟動服務(wù)
   啟動hadoop start-all.sh
   啟動saprk start-all.sh
   啟動mysql元數(shù)據(jù)庫 service mysqld restart
   啟動hive metastore服務(wù) hive --service metastore
   啟動hive命令行 hive
   啟動spark-shell命令行 spark-shell

5. 簡單測試
   創(chuàng)建本地文件 test.csv，內(nèi)容如下：
   0001,spark
   0002,hive
   0003,hbase
   0004,hadoop

執(zhí)行hive命令：

hive> show databases;
hive> create database databases1;
hive> create table if not exists test(userid string,username string)ROW FORMAT DELIMITED FIELDS TERMINATED BY ' ' STORED AS textfile;
hive> load data local inpath "/root/test.csv" into table test;
hive>select * from test;

執(zhí)行Spark-shell命令：

spark.sql("select * from databases1.test").show