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hive学习笔记之七:内置函数

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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 ',';
  1. 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
  1. 加载数据到address表:
load data 
local inpath '/home/hadoop/temp/202010/25/address.txt' 
into table address;
  1. 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 ',';
  1. 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
  1. 加载数据到student表:
load data 
local inpath '/home/hadoop/temp/202010/25/student.txt' 
into table student;
  1. 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)
  1. 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)
  1. 减法(-)、乘法(*)、除法(/)的使用与加法类似,不再赘述了;
  2. 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)
  1. 向上取整ceil
hive> select ceil(1.1);
OK
_c0
2
Time taken: 0.024 seconds, Fetched: 1 row(s)
  1. 向下取整floor
hive> select floor(1.1);
OK
_c0
1
Time taken: 0.024 seconds, Fetched: 1 row(s)
  1. 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)
  1. 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)
  1. 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)
  1. 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)
  1. 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)
  1. 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;
  1. 创建t15.txt文件,内容如下:
{"name":"tom","age":"10"}
{"name":"jerry","age":"11"}
  1. 加载数据到t15表:
load data 
local inpath '/home/hadoop/temp/202010/25/015.txt' 
into table t15;
  1. 使用get_json_object函数,解析json_raw字段,分别取出指定nameage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)
  1. 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)
  1. 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)
  1. 另外,yearcurrent_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)
  1. 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)
  1. 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)
  1. 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

我是欣宸,期待与您一同畅游Java世界…

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