Hive的复杂数据类型和时间类型

一 复杂数据类型

Array：数组类型，由一系列相同类型的元素组成

Map：集合类型，包括key->value键值对，可以通过key来访问元素。

Struct：结构类型，可以包含不同类型的元素。这些元素可以通过“点语法”的方式来得到所需要的元素。

二 实战

1、数组

hive> create table student

> (sid int,

> sname string,

> grade array<float>);

类似：{1，Tom，[80,90,75]}

hive> desc student;

OK

sid int

sname string

grade array<float>

2、映射

hive> create table student1

> (sid int,

> sname string,

> grade map<string,float>);

OK

Time taken: 0.546 seconds

类似{1，Tom，<'大学语文'，85>}

hive> desc student1;

OK

sid int

sname string

grade map<string,float>

Time taken: 0.377 seconds, Fetched: 3 row(s)

3、数组加映射

hive> create table student3

> (sid int,

> sname string,

> grade array<map<string,float>>);

OK

Time taken: 0.178 seconds

类似：{1，‘Tom’，[<'大学语文'，80>，<‘大学英语’，90>]}

hive> desc student3;

OK

sid int

sname string

grade array<map<string,float>>

Time taken: 1.428 seconds, Fetched: 3 row(s)

4、结构

hive> create table student4

> (sid int,

> info struct<name:string,age:int,sex:string>);

OK

Time taken: 0.398 seconds

类似：{1，{‘Tom’，10，‘男’}}

hive> desc student4;

OK

sid int

info struct<name:string,age:int,sex:string>

Time taken: 0.682 seconds, Fetched: 2 row(s)

5、时间

hive> select unix_timestamp();

Total jobs = 1

Launching Job 1 out of 1

Number of reduce tasks is set to 0 since there's no reduce operator

Starting Job = job_201708270801_0001, Tracking URL = http://localhost:50030/jobdetails.jsp?jobid=job_201708270801_0001

Kill Command = /opt/hadoop-1.2.1/libexec/../bin/hadoop job -kill job_201708270801_0001

Hadoop job information for Stage-1: number of mappers: 1; number of reducers: 0

2017-08-27 08:05:58,184 Stage-1 map = 0%, reduce = 0%

2017-08-27 08:06:21,155 Stage-1 map = 100%, reduce = 0%, Cumulative CPU 6.28 sec

2017-08-27 08:06:30,451 Stage-1 map = 100%, reduce = 100%, Cumulative CPU 6.28 sec

MapReduce Total cumulative CPU time: 6 seconds 280 msec

Ended Job = job_201708270801_0001

MapReduce Jobs Launched:

Job 0: Map: 1 Cumulative CPU: 6.28 sec HDFS Read: 270 HDFS Write: 11 SUCCESS

Total MapReduce CPU Time Spent: 6 seconds 280 msec

OK

1503792379

Time taken: 77.649 seconds, Fetched: 1 row(s)