Hsql函数上

原文链接: https://blog.csdn.net/scgaliguodong123_/article/details/60881166

Hsql函数.上(关系/数学/逻辑/数值/日期/条件/字符串/集合统计/复杂类型)

  • 原文链接:https://blog.csdn.net/scgaliguodong123_/article/details/60881166

hive常见函数

  • 准备数据

    zhangsa	dfsadsa323	new	67.1	2
    lisi	543gfd	old	43.32	1
    wanger	65ghf	new	88.88	3
    liiu	fdsfagwe	new	66.0	1
    qibaqiu	fds	new	54.32	1
    wangshi	f332	old	77.77	2
    liwei	hfd	old	88.44	3
    wutong	543gdfsd	new	56.55	6
    lilisi	dsfgg	new	88.88	5
    qishili	fds	new	66.66	5
    
    create external table if not exists order_detail(user_id string,device_id string,user_type string, price decimal,sales int) row format delimited fields terminated by '\t' location '/hive-data/data';
    

1、关系运算

1.1、String 的比较要注意(常用的时间比较可以先 to_date 之后再比较)
## > < =
##注意: String 的比较要注意(常用的时间比较可以先 to_date 之后再比较)
select long_time>short_time, long_time<short_time,long_time=short_time, to_date(long_time)=to_date(short_time)
from 
(
    select '2017-01-11 00:00:00' as long_time, '2017-01-11' as short_time
    from 
    order_detail limit 1
)bb;

result:
true    false   false   true
1.2、空值判断
select 1 from order_detail where NULL is Null limit 1;
select 1 from order_detail where 1 is not null limit 1;
1.3、like与rlike、regexp
  • LIKE

    语法: A LIKE B
    描述: 字符串A符合表达式B的正则语法,则为TRUE;否则为FALSE. B中字符”_”表示任意单个字符,而字符”%”表示任意数量的字符。

  • RLIKE

    语法: A RLIKE B
    描述: 字符串A符合JAVA正则表达式 B 的正则语法,则为 TRUE;否则为 FALSE。

  • REGEXP

    语法: A REGEXP B
    描述: 功能与 RLIKE 相同

2、数学运算

2.1、hive的数据类型 double,只精确到小数点后16位,在做除法运算的时候要特别注意
  • 注意:
    精度在 hive 中是个很大的问题,类似这样的操作最好通过round 指定精度

    select 8.4 % 4,round(8.4 % 4 , 2) from order_detail limit 1;
    --round(xxx,2),小数点后一位
    
  • 用decimal可以表示任意精度的带符号小数;

2.2、位与& 位或| 位异或^ 位取反~(要转换成二进制运算)
select 4&6, 8&4, 4|8,6|8,4^8,6^4,~6,~3 from order_detail limit 1;

--4	0	12	14	12	2	-7	-4
--00000100(4)
--00000110(6)
--00001000(8)
--00000011(3)
2.3、逻辑与AND 逻辑或OR 逻辑非NOT
  • 注意:优先级依次为NOT AND OR,分不清的时候用括号解决一切-。-

3、数值计算函数

  • 取整: round

    • 语法: round(double a)
      说明: 遵循四舍五入
  • 指定精度取整: round

    • 语法: round(double a, int d)
  • 向下取整: floor

    • 说明: 返回等于或者小于该 double 变量的最大的整数
  • 向上取整: ceil

    • 说明: 返回等于或者大于该 double 变量的最小的整数
  • 向上取整: ceiling

    • 说明: 与ceil功能相同
  • 取随机数: rand

    • 说明: 返回一个 0 到 1 范围内的随机数。如果指定种子 seed(整数),则会得到一个稳定的随机数序列。
  • 自然指数: exp 自然对数: ln

  • 以10为底对数: log10 以2为底对数: log2

  • 对数: log

    • 语法: log(double base, double a)
    • 说明: 返回以 base 为底的 a 的对数
    select log10(100),log2(8),log(4,256) from order_detail limit 1;
    
  • 幂运算: pow, power 开平方: sqrt

    • pow(a,b)—>ab
  • 二进制: bin 十六进制: hex 反转十六进制: unhex

  • 进制转换: conv

    • 语法: conv(BIGINT num, int from_base, int to_base)
    • 说明: 将数值 num 从 from_base 进制转化到 to_base 进制
  • 绝对值:abs 正取余:pmod 正弦:sin 反正弦:asin 余弦:cos 反余弦:acos 返回A的值:positive 返回A的相反数:negative

4、日期函数

  • UNIX时间戳转日期: from_unixtime

  • 日期转UNIX时间戳,指定格式日期转UNIX 时间戳,获取当前UNIX时间戳: unix_timestamp

    • 说明: 转换格式为"yyyy-MM-dd HH:mm:ss"的日期到 UNIX 时间戳。如果转化失败,则返回 0。

      select 
          from_unixtime(1323308943),
          from_unixtime(1323308943,'yyyyMMdd'),
          unix_timestamp(),
          unix_timestamp('2017-12-07 16:01:03'),
          unix_timestamp('20171207 16-01-03','yyyyMMdd HH-mm-ss')
      from 
      order_detail limit 1;
      --2011-12-08 09:49:03     20111208        1566829811      1512633663      1512633663
      
  • 当前时间:current_timestamp()(注意:unix_timestamp(void)已经过时,用curren_timestamp替代)

--2019-08-26 22:17:32.622
  • 日期时间转日期:to_date 日期转年:year 日期转月:month 日期转天:day 日期转小时:hour 日期转分钟:minute 日期转秒:second
select
to_date('2016-12-08 10:03:01'),
year('2016-12-08 10:03:01'),
month('2016-12-08'),
day('2016-12-08 10:03:01'),
hour('2016-12-08 10:03:01'),
minute('2016-12-08 10:03:01'),
second('2016-12-08 10:03:01')
from 
order_detail limit 1;

select to_date(current_timestamp());

Hsql函数上_第1张图片

  • 日期转周:weekofyear 日期比较:datediff
select 
weekofyear('2016-12-08 10:03:01'),
datediff('2016-12-08','2016-11-27') 
from order_detail limit 1;
--49	11
  • 日期增加: date_add 日期减少: date_sub
select date_add('2016-12-08',10),date_add('2016-12-08',-10),
date_sub('2016-12-08',-10),date_sub('2016-12-08',10) from order_detail limit 1;
--2016-12-18  | 2016-11-28  | 2016-12-18  | 2016-11-28  
select 
date_add('20161208',10),
from_unixtime(unix_timestamp(date_add('2016-12-08',10)),'yyyyMMdd'),
from_unixtime(unix_timestamp(date_add('2016-12-08',10),'yyyy-MM-dd'),'yyyyMMdd') 
from order_detail limit 1;

5、条件函数

  • IF CASE COALESCE
  • 说明: COALESCE返回参数中的第一个非空值;如果所有值都为 NULL,那么返回 NULL
select user_id,device_id,user_type,sales,
if(user_type='new',user_id,'***'), 
COALESCE(null,user_id,device_id,user_type),
COALESCE(null,null,device_id,user_type),
case user_type 
	when 'new' then 'new_user' 
	when 'old' then 'old_user' 
	else 'others' end,
case 
	when user_type='new' and sales>=5 then 'gold_user' 
	when user_type='old' and sales<3 then 'bronze_user' 
	else 'silver_user' end
from order_detail;

Hsql函数上_第2张图片

6、字符串函数

  • 字符串长度:length 字符串反转:reverse 字符串连接:concat 带分隔符字符串连接:concat_ws
select 
user_id,device_id,user_type,length(user_id),
reverse(user_id),
concat(user_id,device_id,user_type),
concat_ws('_',user_id,device_id,user_type)
from order_detail;
  • 字符串截取函数: substr,substring
    • 语法: substr(string A, int start),substring(string A, int start)
      说明:返回字符串 A 从 start 位置到结尾的字符串
    • 语法: substr(string A, int start, int len),substring(string A, int start, int len)
      说明:返回字符串A从start位置开始,长度为len的字符串
  • 字符串转大写:upper,ucase 字符串转小写:lower,lcase
  • 去两边的空格:trim 左边去空格:ltrim 右边去空格:rtrim
  • 正则表达式替换: regexp_replace
    • 说明:将字符串 A 中的符合 java 正则表达式 B 的部分替换为 C。注意,在有些情况下要使用转义字符,类似 oracle 中的 regexp_replace 函数。
  • 正则表达式解析: regexp_extract
    将字符串 subject 按照 pattern 正则表达式的规则拆分,返回 index 指定的字符。
    注意,在有些情况下要使用转义字符,如等号要用双竖线转义,这是java正则表达式的规则。
select user_id,regexp_replace(user_id, 'li|ng', '**'),
regexp_extract(user_id,'li(.*?)(si)',1),
regexp_extract(user_id,'li(.*?)(si)',2),
regexp_extract(user_id,'li(.*?)(si)',0)
from order_detail;

Hsql函数上_第3张图片

  • URL解析:parse_url
    • 语法: parse_url(string urlString, string partToExtract [, string keyToExtract])
    • 说明:返回 URL 中指定的部分。
    • partToExtract 的有效值为: HOST, PATH, QUERY, REF,PROTOCOL, AUTHORITY, FILE, and USERINFO。
select 
parse_url('http://facebook.com/path1/p.php?k1=v1&k2=v2#Ref1', 'HOST'),
parse_url('http://facebook.com/path1/p.php?k1=v1&k2=v2#Ref1', 'PATH'),
parse_url('http://facebook.com/path1/p.php?k1=v1&k2=v2#Ref1', 'QUERY'),
parse_url('http://facebook.com/path1/p.php?k1=v1&k2=v2#Ref1', 'QUERY','k2'),
parse_url('http://facebook.com/path1/p.php?k1=v1&k2=v2#Ref1', 'REF'),
parse_url('http://facebook.com/path1/p.php?k1=v1&k2=v2#Ref1', 'PROTOCOL'),
parse_url('http://facebook.com/path1/p.php?k1=v1&k2=v2#Ref1', 'AUTHORITY'),
parse_url('http://facebook.com/path1/p.php?k1=v1&k2=v2#Ref1', 'FILE')
from order_detail limit 1;
  • json解析: get_json_object
    • 语法: get_json_object(string json_string, string path)
    • 说明:解析 json 的字符串 json_string,返回 path 指定的内容。如果输入的 json 字符串无效,那么返回 NULL。
select 
get_json_object(
'{"store":
{"fruit":\[{"weight":8,"type":"apple"},{"weight":9,"type":"pear"}],
"bicycle":{"price":19.95,"color":"red"}
},
"email":"amy@only_for_json_udf_test.net",
"owner":"amy"
}',
'$.owner'),
get_json_object(
'{"store":
{"fruit":\[{"weight":8,"type":"apple"},{"weight":9,"type":"pear"}],
"bicycle":{"price":19.95,"color":"red"}
},
"email":"amy@only_for_json_udf_test.net",
"owner":"amy"
}',
'$.store.fruit[0].type')
from order_detail limit 1;
  • json_tuple
    • 语法: json_tuple(string jsonStr,string k1,string k2, …)
    • 参数为一组键k1,k2……和JSON字符串,返回值的元组。该方法比 get_json_object 高效,因为可以在一次调用中输入多个键.
select a.user_id, b.*
from order_detail a 
lateral view 
json_tuple('{"store":
{"fruit":\[{"weight":8,"type":"apple"},{"weight":9,"type":"pear"}],
"bicycle":{"price":19.95,"color":"red"}
},
"email":"amy@only_for_json_udf_test.net",
"owner":"amy"
}', 'email', 'owner') b as email, owner limit 1;
  • parse_url_tuple
SELECT b.*
from (
	select 'http://facebook.com/path1/p.php?k1=v1&k2=v2#Ref1' as urlstr
	from
	order_detail 
	limit 1
	)a 
	LATERAL VIEW 
	parse_url_tuple(a.urlstr, 'HOST', 'PATH', 'QUERY', 'QUERY:k1') b 
	as host, path, query, query_k1 
	LIMIT 1;
	
--facebook.com  | /path1/p.php  | k1=v1&k2=v2  | v1        
  • 空格字符串:space 重复字符串:repeat 首字符ascii:ascii

在这里插入图片描述

  • 左补足函数:lpad 右补足函数:rpad
    • 语法: lpad(string str, int len, string pad)
    • 说明:lpad将 str 进行用 pad 进行左补足到 len 位, rpad将 str 进行用 pad 进行右补足到 len 位
    • 注意:与 GP,ORACLE 不同; pad不能默认

Hsql函数上_第4张图片

  • 分割字符串函数: split
  • 集合查找函数: find_in_set
    语法: find_in_set(string str, string strList)
    说明: 返回 str 在 strlist 第一次出现的位置, strlist 是用逗号分割的字符串。如果没有找该 str 字符,则返回 0

Hsql函数上_第5张图片

  • string转map:str_to_map

    • 语法:str_to_map(text[, delimiter1, delimiter2])
    • 说明:使用两个分隔符将文本拆分为键值对。 Delimiter1将文本分成K-V对,Delimiter2分割每个K-V对。
    • 对于delimiter1默认分隔符是’,’,对于delimiter2默认分隔符是’:’。
    select str_to_map('aaa:11&bbb:22', '&', ':')
    

在这里插入图片描述

7、集合统计函数

  • 个数统计:count 总和统计:sum
    • 语法: count(*), count(expr), count(DISTINCT expr[, expr_.])
      • 说明:
        count(*)统计检索出的行的个数,包括 NULL 值的行;
        count(expr)返回指定字段的非空值的个数;
        count(DISTINCT expr[, expr_.])返回指定字段的不同的非空值的个数
    • sum(col), sum(DISTINCT col)
      • 说明: sum(col)统计结果集中 col 的相加的结果; sum(DISTINCT col)统计结果中 col 不同值
select 
count(*),count(user_type),count(distinct user_type),
sum(sales),sum(distinct sales)
from order_detail; 
  • 平均值统计:avg 最小值统计:min 最大值统计:max
  • 标准差:stddev_samp, stddev, stddev_pop
    • stddev_pop <==> stddev
  • 方差:var_samp, var_pop
    • 当我们需要真实的标准差/方差的时候最好是使用: stddev stddev_pop var_pop
      而只是需要得到少量数据的标准差/方差的近似值可以选用: stddev_samp var_samp
  • 百分位数: percentile 近似百分位数: percentile_approx 直方图: histogram_numeric
    • 语法: percentile_approx(DOUBLE col, p [, B])
    • 返回值: double
    • 说明: 求近似的第 pth 个百分位数, p 必须介于 0 和 1 之间,返回类型为 double,但是col 字段支持浮点类型。参数 B 控制内存消耗的近似精度, B越大,结果的准确度越高。默认为 10,000。当 col 字段中的 distinct 值的个数小于 B 时,结果为准确的百分位数
    • 后面可以输入多个百分位数,返回类型也为 array,其中为对应的百分位数。

8、复杂类型访问操作及统计函数

测试数据集:
tony    1338    hello,woddd     1,2     a1,a2,a3        k1:1.0,k2:2.0,k3:3.0    s1,s2,s3,4
mark    5453    kke,ladyg       2,3     a4,a5,a6        k4:4.0,k5:5.0,k2:6.0    s4,s5,s6,6
ivyfd   4323    aa,thq,dsx      3,6     a7,a8,a9        k7:7.0,k8:8.0,k2:9.0    s7,s8,s9,9
drop table employees;
create external table if not exists employees(
name string,
salary string,
happy_word string,
happy_num array<int>,
subordinates array<string>,
deductions map<string,float>,
address struct<street:string,city:string,state:string,zip:int>
)
row format delimited fields terminated by '\t'
collection items terminated by ','
map keys terminated by ':'
lines terminated by '\n'
stored as textfile;

hdfs dfs -put /home/liguodong/data/muldata.txt /temp/lgd

load data inpath '/temp/lgd/muldata.txt' overwrite into table employees;

select * from employees;

Getting log thread is interrupted, since query is done!
+--------+---------+--------------+------------+-------------------+-------------------------------+---------------------------------------------------+--+
|  name  | salary  |  happy_word  | happy_num  |   subordinates    |          deductions           |                      address                      |
+--------+---------+--------------+------------+-------------------+-------------------------------+---------------------------------------------------+--+
| tony   | 1338    | hello,woddd  | [1,2]      | ["a1","a2","a3"]  | {"k1":1.0,"k2":2.0,"k3":3.0}  | {"street":"s1","city":"s2","state":"s3","zip":4}  |
| mark   | 5453    | kke,ladyg    | [2,3]      | ["a4","a5","a6"]  | {"k4":4.0,"k5":5.0,"k2":6.0}  | {"street":"s4","city":"s5","state":"s6","zip":6}  |
| ivyfd  | 4323    | aa,thq,dsx   | [3,6]      | ["a7","a8","a9"]  | {"k7":7.0,"k8":8.0,"k2":9.0}  | {"street":"s7","city":"s8","state":"s9","zip":9}  |
+--------+---------+--------------+------------+-------------------+-------------------------------+---------------------------------------------------+--+
## 访问数组 Map 结构体

select 
name,salary,
subordinates[1],deductions['k2'],deductions['k3'],address.city 
from employees;
+--------+---------+------+------+-------+-------+--+
|  name  | salary  | _c2  | _c3  |  _c4  | city  |
+--------+---------+------+------+-------+-------+--+
| tony   | 1338    | a2   | 2.0  | 3.0   | s2    |
| mark   | 5453    | a5   | 6.0  | NULL  | s5    |
| ivyfd  | 4323    | a8   | 9.0  | NULL  | s8    |
+--------+---------+------+------+-------+-------+--+

## Map类型长度  Array类型长度

select size(deductions),size(subordinates) from employees limit 1;

+------+------+--+
| _c0  | _c1  |
+------+------+--+
| 3    | 3    |
+------+------+--+

## 类型转换: cast

select cast(salary as int),cast(deductions['k2'] as bigint) from employees;

+---------+------+--+
| salary  | _c1  |
+---------+------+--+
| 1338    | 2    |
| 5453    | 6    |
| 4323    | 9    |
+---------+------+--+

### LATERAL VIEW 行转列
SELECT 
name, ad_subordinate
FROM employees 
LATERAL VIEW explode(subordinates) addTable AS ad_subordinate;
+--------+-----------------+--+
|  name  | ad_subordinate  |
+--------+-----------------+--+
| tony   | a1              |
| tony   | a2              |
| tony   | a3              |
| mark   | a4              |
| mark   | a5              |
| mark   | a6              |
| ivyfd  | a7              |
| ivyfd  | a8              |
| ivyfd  | a9              |
+--------+-----------------+--+

SELECT 
name, count(1)
FROM employees 
LATERAL VIEW explode(subordinates) addTable AS ad_subordinate
group by name;
+--------+------+--+
|  name  | _c1  |
+--------+------+--+
| ivyfd  | 3    |
| mark   | 3    |
| tony   | 3    |
+--------+------+--+

SELECT ad_subordinate, ad_num 
FROM employees
LATERAL VIEW explode(subordinates) addTable AS ad_subordinate
LATERAL VIEW explode(happy_num) addTable2 AS ad_num;
+-----------------+---------+--+
| ad_subordinate  | ad_num  |
+-----------------+---------+--+
| a1              | 1       |
| a1              | 2       |
| a2              | 1       |
| a2              | 2       |
| a3              | 1       |
| a3              | 2       |
| a4              | 2       |
| a4              | 3       |
| a5              | 2       |
| a5              | 3       |
| a6              | 2       |
| a6              | 3       |
| a7              | 3       |
| a7              | 6       |
| a8              | 3       |
| a8              | 6       |
| a9              | 3       |
| a9              | 6       |
+-----------------+---------+--+

### 多个LATERAL VIEW
SELECT 
name, count(1) 
FROM employees
LATERAL VIEW explode(subordinates) addTable AS ad_subordinate
LATERAL VIEW explode(happy_num) addTable2 AS ad_num
group by name;

+--------+------+--+
|  name  | _c1  |
+--------+------+--+
| ivyfd  | 6    |
| mark   | 6    |
| tony   | 6    |
+--------+------+--+

### 不满足条件产生空行
SELECT AA.name, BB.* FROM employees AA
LATERAL VIEW 
explode(array()) BB AS a limit 10;
+-------+----+--+
| name  | a  |
+-------+----+--+
+-------+----+--+

### OUTER 避免永远不产生结果,无满足条件的行,在该列会产生NULL值。
SELECT AA.name, BB.* FROM employees AA
LATERAL VIEW 
OUTER explode(array()) BB AS a limit 10;
+--------+-------+--+
|  name  |   a   |
+--------+-------+--+
| tony   | NULL  |
| mark   | NULL  |
| ivyfd  | NULL  |
+--------+-------+--+

### 字符串切分成多列
SELECT 
name, word
FROM employees
LATERAL VIEW explode(split(happy_word,',')) addTable AS word;

+--------+--------+--+
|  name  |  word  |
+--------+--------+--+
| tony   | hello  |
| tony   | woddd  |
| mark   | kke    |
| mark   | ladyg  |
| ivyfd  | aa     |
| ivyfd  | thq    |
| ivyfd  | dsx    |
+--------+--------+--+


### OUTER 避免永远不产生结果,无满足条件的行,在该列会产生NULL值。
SELECT AA.name, BB.* FROM employees AA
LATERAL VIEW 
OUTER explode(array()) BB AS a limit 10;
+--------+-------+--+
|  name  |   a   |
+--------+-------+--+
| tony   | NULL  |
| mark   | NULL  |
| ivyfd  | NULL  |
+--------+-------+--+

### 字符串切分成多列
SELECT 
name, word
FROM employees
LATERAL VIEW explode(split(happy_word,',')) addTable AS word;

+--------+--------+--+
|  name  |  word  |
+--------+--------+--+
| tony   | hello  |
| tony   | woddd  |
| mark   | kke    |
| mark   | ladyg  |
| ivyfd  | aa     |
| ivyfd  | thq    |
| ivyfd  | dsx    |
+--------+--------+--+

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