Hive語法及其進階(二)

1、使用JDBC連接Hive

 1 import java.sql.Connection;
 2 import java.sql.DriverManager;
 3 import java.sql.PreparedStatement;
 4 import java.sql.ResultSet;
 5 
 6 public class HiveDemo {
 7     public static void main(String[] args) throws Exception {
 8         Class.forName("org.apache.hive.jdbc.HiveDriver");
 9         //"jdbc:hive2://master:10000/test3"
10         Connection connection = DriverManager.getConnection("jdbc:hive2://master:10000/myhive");
11         String sql="select * from students";
12         PreparedStatement ps = connection.prepareStatement(sql);
13         ResultSet rs = ps.executeQuery();
14         while (rs.next()){
15             int id = rs.getInt(1);
16             String name = rs.getString(2);
17             int age = rs.getInt(3);
18             String gender = rs.getString(4);
19             String clazz = rs.getString(5);
20             System.out.println(id + "," + name + "," + age + "," + gender + "," + clazz);
21         }
22         rs.close();
23         ps.close();
24         connection.close();
25     }
26 }

2、Hive常用函式

1.關系運算

// 等值比較 = == <=>
// 不等值比較 != <>
// 區間比較： select * from default.students where id between 1500100001 and 1500100010;
// 空值/非空值判斷：is null、is not null、nvl()、isnull()

2 .數值計算

取整函式(四舍五入)：round
向上取整：ceil
向下取整：floor

 like、rlike、

（1）查找名字以A開頭的員工資訊

hive (default)> select * from emp where ename LIKE 'A%';

（2）查找名字中第二個字母為A的員工資訊

hive (default)> select * from emp where ename LIKE '_A%';

（3）查找名字中帶有A的員工資訊

hive (default)> select * from emp where ename  RLIKE '[A]';

.

 3.日期函式

1 select from_unixtime(1610611142,'YYYY/MM/dd HH:mm:ss');
2unix_timestamp(),獲取當前時間的時間戳

3 select from_unixtime(unix_timestamp(),'YYYY/MM/dd HH:mm:ss'); 

4 // '2021年01月14日' -> '2021-01-14' 
6 select from_unixtime(unix_timestamp('2021年01月14日','yyyy年MM月dd日'),'yyyy-MM-dd');
8 select from_unixtime(unix_timestamp("04-2021-16","MM-yyyy-dd"),"yyyy/MM/dd");

4.字串函式

1）cancat（）字串拼接 當有空值則為NULL

2）cancat_ws()指定可以指定分隔符，并且會自動忽略NULL

 3)substring字串的截取

 4)split字串的切分

 5）explode列轉行

 決議json格式的資料

select get_json_object
('{"name":"zhangsan",
"age":18,
"score":[{"course_name":"math","score":100},{"course_name":"english","score":60}]}',
"$.score[0].score");

 6) Hive中的wordcount

create table words(
    words string
)row format delimited fields terminated by '|';

// 資料
hello,java,hello,java,scala,python
hbase,hadoop,hadoop,hdfs,hive,hive
hbase,hadoop,hadoop,hdfs,hive,hive

select word,count(*) from (select explode(split(words,',')) word from words) a group by a.word;

4.開窗函式

##### row_number：無并列排名

分組求TOPN

select * from (select  *, row_number() over(partition by clazz order by score desc)as s from new_score)tt where tt.s<=3;

用法： select xxxx, row_number() over(partition by 分組欄位 order by 排序欄位 desc) as rn from tb group by xxxx

##### dense_rank：有并列排名，并且依次遞增

hive> select  *, row_number() over(partition by clazz order by score desc)as s,
    > dense_rank()  over(partition by clazz order by score desc)as s from new_score;

##### rank：有并列排名，不依次遞增

hive> select  *, row_number() over(partition by clazz order by score desc)as s,
    > dense_rank()  over(partition by clazz order by score desc),
    > rank() over(partition by clazz order by score desc)from new_score;

##### percent_rank：(rank的結果-1)/(磁區內資料的個數-1)

select *, row_number() over(partition by clazz order by score desc)as s,
> rank() over(partition by clazz order by score desc),
> percent_rank() over(partition by clazz order by score desc)from new_score;

##### cume_dist：計算某個視窗或磁區中某個值的累積分布，

select *, row_number() over(partition by clazz order by score desc)as s,
> rank() over(partition by clazz order by score desc),
> percent_rank() over(partition by clazz order by score desc),
> cume_dist() over(partition by clazz order by score desc) from new_score;

> 假定升序排序，則使用以下公式確定累積分布： 小于等于當前值x的行數 / 視窗或partition磁區內的總行數，其中，x 等于 order by 子句中指定的列的當前行中的值，

##### NTILE(n)：對磁區內資料再分成n組，然后打上組號

##### max、min、avg、count、sum：基于每個partition磁區內的資料做對應的計算

5.視窗幀格式
　　格式1:按照行的記錄取值

　　　　　　ROWS BETWEEN (UNBOUNDED | [num]) PRECEDING AND ([num] PRECEDING | CURRENT ROW | (UNBOUNDED | [num]) FOLLOWING)

　　格式2:當前所指定值的范圍取值

　　　　　　RANGE BETWEEN (UNBOUNDED | [num]) PRECEDING AND ([num] PRECEDING | CURRENT ROW | (UNBOUNDED | [num]) FOLLOWING)
注意:
　　　　UNBOUNDED:無界限

　　　　CURRENT ROW:當前行

rows格式1:前2行+當前行+后兩行

　　　　sum(score) over (partition by clazz order by score desc rows between 2 PRECEDING and 2 FOLLOWING)

rows格式2:前記錄到最末尾的總和

　　　　sum(score) over (partition by clazz order by score desc rows between CURRENT ROW and UNBOUNDED FOLLOWING)

range格式1: 如果當前值在80,取值就會落在范圍在80-2=78和80+2=82組件之內的行

　　　　max(score) over (partition by clazz order by score desc range between 2 PRECEDING and 2 FOLLOWING)

標籤：大數據

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