本篇概览

• 本文是《hive学习笔记》系列的第七篇，前文熟悉了HiveQL的常用语句，接下来把常用的内置函数简单过一遍，分为以下几部分：

1. 数学
2. 字符
3. json处理
4. 转换
5. 日期
6. 条件
7. 聚合

准备数据

1. 本次实战要准备两个表：学生表和住址表，字段都很简单，如下图所示，学生表有个住址ID字段，是住址表里的记录的唯一ID：

2. 先创建住址表：

create table address (addressid int, province string, city string) 
row format delimited 
fields terminated by ',';

3. 创建address.txt文件，内容如下：

1,guangdong,guangzhou
2,guangdong,shenzhen
3,shanxi,xian
4,shanxi,hanzhong
6,jiangshu,nanjing

4. 加载数据到address表：

load data 
local inpath '/home/hadoop/temp/202010/25/address.txt' 
into table address;

5. 创建学生表，其addressid字段关联了address表的addressid字段：

create table student (name string, age int, addressid int) 
row format delimited 
fields terminated by ',';

6. 创建student.txt文件，内容如下：

tom,11,1
jerry,12,2
mike,13,3
john,14,4
mary,15,5

7. 加载数据到student表：

load data 
local inpath '/home/hadoop/temp/202010/25/student.txt' 
into table student;

8. 至此，本次操作所需数据已准备完毕，如下所示：

hive> select * from address;
OK
1	guangdong	guangzhou
2	guangdong	shenzhen
3	shanxi	xian
4	shanxi	hanzhong
6	jiangshu	nanjing
Time taken: 0.043 seconds, Fetched: 5 row(s)
hive> select * from student;
OK
tom	11	1
jerry	12	2
mike	13	3
john	14	4
mary	15	5
Time taken: 0.068 seconds, Fetched: 5 row(s)

• 开始体验内置函数；

总览

1. 进入hive控制台；
2. 执行命令show functions;显示内置函数列表：

hive> show functions;
OK
!
!=
%
&
*
+
-
/
<
<=
<=>
<>
=
==
>
>=
^
abs
acos
add_months
and
array
array_contains
ascii
asin
assert_true
atan
avg
base64
between
bin
case
cbrt
ceil
ceiling
coalesce
collect_list
collect_set
compute_stats
concat
concat_ws
context_ngrams
conv
corr
cos
count
covar_pop
covar_samp
create_union
cume_dist
current_database
current_date
current_timestamp
current_user
date_add
date_format
date_sub
datediff
day
dayofmonth
decode
degrees
dense_rank
div
e
elt
encode
ewah_bitmap
ewah_bitmap_and
ewah_bitmap_empty
ewah_bitmap_or
exp
explode
factorial
field
find_in_set
first_value
floor
format_number
from_unixtime
from_utc_timestamp
get_json_object
greatest
hash
hex
histogram_numeric
hour
if
in
in_file
index
initcap
inline
instr
isnotnull
isnull
java_method
json_tuple
lag
last_day
last_value
lcase
lead
least
length
levenshtein
like
ln
locate
log
log10
log2
lower
lpad
ltrim
map
map_keys
map_values
matchpath
max
min
minute
month
months_between
named_struct
negative
next_day
ngrams
noop
noopstreaming
noopwithmap
noopwithmapstreaming
not
ntile
nvl
or
parse_url
parse_url_tuple
percent_rank
percentile
percentile_approx
pi
pmod
posexplode
positive
pow
power
printf
radians
rand
rank
reflect
reflect2
regexp
regexp_extract
regexp_replace
repeat
reverse
rlike
round
row_number
rpad
rtrim
second
sentences
shiftleft
shiftright
shiftrightunsigned
sign
sin
size
sort_array
soundex
space
split
sqrt
stack
std
stddev
stddev_pop
stddev_samp
str_to_map
struct
substr
substring
sum
tan
to_date
to_unix_timestamp
to_utc_timestamp
translate
trim
trunc
ucase
unbase64
unhex
unix_timestamp
upper
var_pop
var_samp
variance
weekofyear
when
windowingtablefunction
xpath
xpath_boolean
xpath_double
xpath_float
xpath_int
xpath_long
xpath_number
xpath_short
xpath_string
year
|
~
Time taken: 0.003 seconds, Fetched: 216 row(s)

3. 以lower函数为例，执行命令describe function lower;即可查看lower函数的说明：

hive> describe function lower;
OK
lower(str) - Returns str with all characters changed to lowercase
Time taken: 0.005 seconds, Fetched: 1 row(s)

• 接下来从计算函数开始，体验常用函数；
• 先执行以下命令，使查询结果中带有字段名：

set hive.cli.print.header=true;

计算函数

1. 加法+：

hive> select name, age, age+1 as add_value from student;
OK
name	age	add_value
tom	11	12
jerry	12	13
mike	13	14
john	14	15
mary	15	16
Time taken: 0.098 seconds, Fetched: 5 row(s)

2. 减法(-)、乘法(*)、除法(/)的使用与加法类似，不再赘述了；
3. 四舍五入round：

hive> select round(1.1), round(1.6);
OK
_c0	_c1
1.0	2.0
Time taken: 0.028 seconds, Fetched: 1 row(s)

4. 向上取整ceil：

hive> select ceil(1.1);
OK
_c0
2
Time taken: 0.024 seconds, Fetched: 1 row(s)

5. 向下取整floor：

hive> select floor(1.1);
OK
_c0
1
Time taken: 0.024 seconds, Fetched: 1 row(s)

6. 平方pow，例如pow(2,3)表示2的三次方，等于8：

hive> select pow(2,3);
OK
_c0
8.0
Time taken: 0.027 seconds, Fetched: 1 row(s)

7. 取模pmod：

hive> select pmod(10,3);
OK
_c0
1
Time taken: 0.059 seconds, Fetched: 1 row(s)

字符函数

1. 转小写lower，转大写upper：

hive> select lower(name), upper(name) from student;
OK
_c0	_c1
tom	TOM
jerry	JERRY
mike	MIKE
john	JOHN
mary	MARY
Time taken: 0.051 seconds, Fetched: 5 row(s)

2. 字符串长度length：

hive> select name, length(name) from student;
OK
tom	3
jerry	5
mike	4
john	4
mary	4
Time taken: 0.322 seconds, Fetched: 5 row(s)

3. 字符串拼接concat：

hive> select concat("prefix_", name) from student;
OK
prefix_tom
prefix_jerry
prefix_mike
prefix_john
prefix_mary
Time taken: 0.106 seconds, Fetched: 5 row(s)

4. 子串substr，substr(xxx,2)表示从第二位开始到右边所有，substr(xxx,2,3)表示从第二位开始取三个字符：

hive> select substr("0123456",2);
OK
123456
Time taken: 0.067 seconds, Fetched: 1 row(s)
hive> select substr("0123456",2,3);
OK
123
Time taken: 0.08 seconds, Fetched: 1 row(s)

5. 去掉前后空格trim：

hive> select trim("   123   ");
OK
123
Time taken: 0.065 seconds, Fetched: 1 row(s)

json处理(get_json_object)

为了使用json处理的函数，先准备一些数据：

1. 先创建表t15，只有一个字段用于保存字符串：

create table t15(json_raw string) 
row format delimited;

2. 创建t15.txt文件，内容如下：

{"name":"tom","age":"10"}
{"name":"jerry","age":"11"}

3. 加载数据到t15表：

load data 
local inpath '/home/hadoop/temp/202010/25/015.txt' 
into table t15;

4. 使用get_json_object函数，解析json_raw字段，分别取出指定name和age属性：

select 
get_json_object(json_raw, "$.name"), 
get_json_object(json_raw, "$.age") 
from t15;

得到结果：

hive> select 
    > get_json_object(json_raw, "$.name"), 
    > get_json_object(json_raw, "$.age") 
    > from t15;
OK
tom	10
jerry	11
Time taken: 0.081 seconds, Fetched: 2 row(s)

日期

1. 获取当前日期current_date：

hive> select current_date();
OK
2020-11-02
Time taken: 0.052 seconds, Fetched: 1 row(s)

2. 获取当前时间戳current_timestamp：

hive> select current_timestamp();
OK
2020-11-02 10:07:58.967
Time taken: 0.049 seconds, Fetched: 1 row(s)

3. 获取年份year、月份month、日期day：

hive> select year(current_date()), month(current_date()), day(current_date());
OK
2020	11	2
Time taken: 0.054 seconds, Fetched: 1 row(s)

4. 另外，year和current_timestamp也能搭配使用：

hive> select year(current_timestamp()), month(current_timestamp()), day(current_timestamp());
OK
2020	11	2
Time taken: 0.042 seconds, Fetched: 1 row(s)

5. 返回日期部分to_date：

hive> select to_date(current_timestamp());
OK
2020-11-02
Time taken: 0.051 seconds, Fetched: 1 row(s)

条件函数

• 条件函数的作用和java中的switch类似，语法是case X when XX then XXX else XXXX end；
• 示例如下，作用是判断name字段，如果等于tom就返回tom_case，如果等于jerry就返回jerry_case，其他情况都返回other_case：

select name,
case name when 'tom' then 'tom_case'
          when 'jerry' then 'jerry_case'
          else 'other_case'
end
from student;

结果如下：

hive> select name,
    > case name when 'tom' then 'tom_case'
    >           when 'jerry' then 'jerry_case'
    >           else 'other_case'
    > end
    > from student;
OK
tom	tom_case
jerry	jerry_case
mike	other_case
john	other_case
mary	other_case
Time taken: 0.08 seconds, Fetched: 5 row(s)

聚合函数

1. 返回行数count：

select count(*) from student;

触发MR，结果如下：

Total MapReduce CPU Time Spent: 2 seconds 170 msec
OK
5
Time taken: 20.823 seconds, Fetched: 1 row(s)

2. 分组后组内求和sum：

select province, sum(1) from address group by province;

触发MR，结果如下：

Total MapReduce CPU Time Spent: 1 seconds 870 msec
OK
guangdong	2
jiangshu	1
shanxi	2
Time taken: 19.524 seconds, Fetched: 3 row(s)

3. 分组后，组内最小值min，最大值max，平均值avg：

select province, min(addressid), max(addressid), avg(addressid) from address group by province;

触发MR，结果如下：

Total MapReduce CPU Time Spent: 1 seconds 650 msec
OK
guangdong	1	2	1.5
jiangshu	6	6	6.0
shanxi	3	4	3.5
Time taken: 20.106 seconds, Fetched: 3 row(s)

• 至此，hive常用到内置函数咱们都体验过一遍了，希望能给您提供一些参考，接下来的文章会体验一个常用工具：Sqoop