3.hive的thriftserver服务

1.ThiftServer介绍

  1. 正常的hive仅允许使用HiveQL执行查询、更新等操作,并且该方式比较笨拙单一。幸好Hive提供了轻客户端的实现,通过HiveServer或者HiveServer2,客户端可以在不启动CLI的情况下对Hive中的数据进行操作,两者都允许远程客户端使用多种编程语言如Java、Python向Hive提交请求,取回结果 使用jdbc协议连接hive的thriftserver服务器
  2. 可以实现远程访问

  3. 可以通过命令链接多个hive

2.ThiftServer启动

  1. 启动hive的thriftserver

    #cd /soft/hive/bin/
    #./hiveserver2
    #默认启动非后台启动 需要开另外一个终端
    #端口号为10000
  2. 使用beeline连接hiveserver2服务器,client端命令行程序

    #beeline
    Beeline version 2.1.1 by Apache Hive
    #输入要链接的服务
    beeline> !connect jdbc:hive2://localhost:10000
    SLF4J: Class path contains multiple SLF4J bindings.
    SLF4J: Found binding in [jar:file:/soft/apache-hive-2.1.1-bin/lib/log4j-slf4j-impl-2.4.1.jar!/org/slf4j/impl/StaticLoggerBinder.class]
    SLF4J: Found binding in [jar:file:/soft/hadoop-2.7.3/share/hadoop/common/lib/slf4j-log4j12-1.7.10.jar!/org/slf4j/impl/StaticLoggerBinder.class]
    SLF4J: See http://www.slf4j.org/codes.html#multiple_bindings for an explanation.
    SLF4J: Actual binding is of type [org.apache.logging.slf4j.Log4jLoggerFactory]
    Connecting to jdbc:hive2://localhost:10000
    Enter username for jdbc:hive2://localhost:10000: 
    Enter password for jdbc:hive2://localhost:10000: 
    Connected to: Apache Hive (version 2.1.1)
    Driver: Hive JDBC (version 2.1.1) 
    17/07/13 10:31:00 [main]: WARN jdbc.HiveConnection: Request to set autoCommit to false; Hive does not support autoCommit=false.
    Transaction isolation: TRANSACTION_REPEATABLE_READ
    0: jdbc:hive2://localhost:10000> 

3.beeline的基本用法

  1. 查看数据库

    0: jdbc:hive2://localhost:10000> show databases;
    +----------------+--+
    | database_name  |
    +----------------+--+
    | default        |
    | liuyao         |
    +----------------+--+
    2 rows selected (1.485 seconds)
  2. 查看表

    0: jdbc:hive2://localhost:10000> use liuyao;
    No rows affected (0.123 seconds)
    0: jdbc:hive2://localhost:10000> show tables;
    +-----------+--+
    | tab_name  |
    +-----------+--+
    | test      |
    +-----------+--+
    1 row selected (0.283 seconds)
    或者使用
    0: jdbc:hive2://localhost:10000> !tables 
    +------------+--------------+-------------+-------------+----------+-----------+-------------+------------+----------------------------+-----------------+--+
    | TABLE_CAT  | TABLE_SCHEM  | TABLE_NAME  | TABLE_TYPE  | REMARKS  | TYPE_CAT  | TYPE_SCHEM  | TYPE_NAME  | SELF_REFERENCING_COL_NAME  | REF_GENERATION  |
    +------------+--------------+-------------+-------------+----------+-----------+-------------+------------+----------------------------+-----------------+--+
    |            | liuyao       | test        | TABLE       | NULL     | NULL      | NULL        | NULL       | NULL                       | NULL            |
    +------------+--------------+-------------+-------------+----------+-----------+-------------+------------+----------------------------+-----------------+--+
    0: jdbc:hive2://localhost:10000> 
  3. 创建表

    CREATE TABLE emp0
    (
    name string,
    arr ARRAY<string>,
    stru1 STRUCT<sex:string,age:int>,
    map1 MAP<string,int>,
    map2 MAP<string,ARRAY<string>>
    )
    ;
  4. 查看表结构

    0: jdbc:hive2://localhost:10000> desc emp0;
    +-----------+-----------------------------+----------+--+
    | col_name  |          data_type          | comment  |
    +-----------+-----------------------------+----------+--+
    | name      | string                      |          |
    | arr       | array<string>               |          |
    | stru1     | struct<sex:string,age:int>  |          |
    | map1      | map<string,int>             |          |
    | map2      | map<string,array<string>>   |          |
    +-----------+-----------------------------+----------+--+
    5 rows selected (0.296 seconds)
  5. 删除表

    0: jdbc:hive2://localhost:10000> use default;
    No rows affected (0.092 seconds)
    0: jdbc:hive2://localhost:10000> drop table emp0;
    No rows affected (1.823 seconds)

4. 数据导入查询等演示

  1. 生成数据

    #vim /root/hive.data
    放入以下数据
    Michael|Montreal,Toronto|Male,30|DB:80|Product:Developer^DLead
    Will|Montreal|Male,35|Perl:85|Product:Lead,Test:Lead
    Shelley|New York|Female,27|Python:80|Test:Lead,COE:Architect
    Lucy|Vancouver|Female,57|Sales:89,HR:94|Sales:Lead
  2. 创建表

    CREATE TABLE emp1
    (
    name string,
    arr ARRAY<string>,
    stru1 STRUCT<sex:string,age:int>,
    map1 MAP<string,int>,
    map2 MAP<string,ARRAY<string>>
    )
    ROW FORMAT DELIMITED
    FIELDS TERMINATED BY '|'           //字段分隔符
    COLLECTION ITEMS TERMINATED BY ','
    MAP KEYS TERMINATED BY ':'    //map的kv之间分隔符
    LINES TERMINATED BY '\n';    //集合元素分隔符
    
  3. 导入数据

    如果数据在本地用
    0: jdbc:hive2://localhost:10000> load data local inpath '/root/hive.data' into table emp0;
    No rows affected (0.956 seconds)
    0: jdbc:hive2://localhost:10000> 
  4. 查询

    0: jdbc:hive2://localhost:10000> select * from emp0;
    +------------+-------------------------+----------------------------+-----------------------+----------------------------------------+--+
    | emp0.name  |        emp0.arr         |         emp0.stru1         |       emp0.map1       |               emp0.map2                |
    +------------+-------------------------+----------------------------+-----------------------+----------------------------------------+--+
    | Michael    | ["Montreal","Toronto"]  | {"sex":"Male","age":30}    | {"DB":80}             | {"Product":["Developer^DLead"]}        |
    | Will       | ["Montreal"]            | {"sex":"Male","age":35}    | {"Perl":85}           | {"Product":["Lead"],"Test":["Lead"]}   |
    | Shelley    | ["New York"]            | {"sex":"Female","age":27}  | {"Python":80}         | {"Test":["Lead"],"COE":["Architect"]}  |
    | Lucy       | ["Vancouver"]           | {"sex":"Female","age":57}  | {"Sales":89,"HR":94}  | {"Sales":["Lead"]}                     |
    |            | NULL                    | NULL                       | NULL                  | NULL                                   |
    +------------+-------------------------+----------------------------+-----------------------+----------------------------------------+--+
    5 rows selected (1.049 seconds)   
    0: jdbc:hive2://localhost:10000> select arr[0] from emp0;
    +------------+--+ 
    |     c0     |
    +------------+--+
    | Montreal   |
    | Montreal   |
    | New York   |
    | Vancouver  |
    | NULL       |
    +------------+--+                                                                                                                       5 rows selected (0.656 seconds)
    0: jdbc:hive2://localhost:10000> select stru1 from emp0;
    +----------------------------+--+ 
    |           stru1            |
    +----------------------------+--+
    | {"sex":"Male","age":30}    |
    | {"sex":"Male","age":35}    |
    | {"sex":"Female","age":27}  |
    | {"sex":"Female","age":57}  |
    | NULL                       |
    +----------------------------+--+ 
    5 rows selected (0.193 seconds)
    0: jdbc:hive2://localhost:10000> select map1 from emp0;
    +-----------------------+--+
    |         map1          |
    +-----------------------+--+
    | {"DB":80}             |
    | {"Perl":85}           |
    | {"Python":80}         |
    | {"Sales":89,"HR":94}  |
    | NULL                  |
    +-----------------------+--+
    5 rows selected (0.216 seconds)
    0: jdbc:hive2://localhost:10000> select map1["DB"] from emp0;
    +-------+--+
    |  c0   |
    +-------+--+ 
    | 80    |
    | NULL  |
    | NULL  |
    | NULL  |
    | NULL  |
    +-------+--+
    5 rows selected (0.249 seconds)

    5.使用api编程方式连接到thriftserver服务器

public class TestCURD {

    @Test
    public void select() throws  Exception{
        String driverClass = "org.apache.hive.jdbc.HiveDriver";
        String url = "jdbc:hive2://192.168.10.145:10000/liuyao";
        Class.forName(driverClass);
        Connection connection = DriverManager.getConnection(url);
        System.out.println(connection);
        Statement statement = connection.createStatement();
        ResultSet rs = statement.executeQuery("SELECT  * FROM emp0");
        while (rs.next()){
            int id = rs.getInt(1);
            String name = rs.getString(2);
            System.out.println(id + "," + name);
        }
        rs.close();
        connection.close();

    }
}
posted @ 2017-07-15 23:07  刘耀  阅读(...)  评论(... 编辑 收藏