hive查询语句

一. 为什么hive是数据仓库

1. hive局限于hdfs, 不能进行记录级别的增删改
2. hive底层的mapreduce启动耗时很长, 无法做到传统数据库的秒查, 只适合离线分析
3. hive不支持事务, 无法完成OLTP的要求, OLTP选择hbase或cassandera

二. hive安装

1. 每个hive客户端, 都需要有一个元数据服务来存储元信息(表模式,分区信息), 通常用传统数据库的一个表来存储元信息
2. hive内部默认用derby存储元信息, 由于derby是单进程存储, 使得不允许两个以上的hive cli执行操作

三.HQL数据操作

1. 文本文件导入表中

   LOAD DATA [LOCAL] INPATH 'filepath' [OVERWRITE] INTO TABLE tablename [PARTITION (partcol1=val1, partcol2=val2 ...)]
   

2. 动态分区插入 :

    insert  OVERWRITE  TABLE  employees  PARTITION (country, state)  SELECT  *  FROM  staged_employees  se ;
    CREATE  TABLE  ca_employees  AS  SELECT  name,slary  FROM  employee  WHERE  se.state='CA'
   

3. 一次查询多次插入
   这种from 后跟多个insert into的语句, 可以只扫描表一次. 而多次插入表, 效率最高

   FROM from_statement  
   INSERT INTO TABLE tablename1 [PARTITION (partcol1=val1, partcol2=val2 ...)] select_statement1  
   [INSERT INTO TABLE tablename2 [PARTITION ...] select_statement2]
   

   --1. 建立桶表, 分区表  
   CREATE TABLE TESTA  
      (person_name string, person_org_name string, level2_org_name string)  
   PARTITIONED BY (import_time   string)  
   CLUSTERED BY (person_name) INTO 8 BUCKETS  
   ROW FORMAT DELIMITED FIELDS TERMINATED BY '\t'  
   STORED AS textfile  
   

   --2.  插入分区数据  
   from (select person_name, person_org_name, level2_org_name from iap_app_log_import_minute where import_time in ('2015-01-16-0000', '2015-01-200000')) applog 
   insert into table testa partition(import_time = '2015-01')
   select applog.person_name,
          applog.person_org_name,
          applog.level2_org_name
   

四. 查询语句

1. sort by + distribute by 与 order by + group by
   (1) order by: 查询语句全局有序
   (2) sort by : 每个reducer内的数据有序, 当reducer的个数为1, sort by的数据据才全局有序 (效率高)
   (3) distribute by : mapreduce会把map输入的键计算哈希值, 把相同哈希值的键值对发往一个reducer.
   (4) cluster by : 先distribute by 再order by , 达到全局有序

2. 查看partition

   show partitions employees;
   

   SHOW PARTITIONS employees PARTITION(country='US');
   

3. 桶表的抽样查询tablesample

   select * from testa tablesample(bucket 3 out of 10 on  person_name)
   

4. laterview

   pageid	contact_page
   contact_page	[3, 4, 5]
   front_page	[1, 2, 3]

   SELECT pageid, adid
       FROM pageAds LATERAL VIEW explode(adid_list) adTable AS adid;
   

   pageid	adid
   contact_page	3
   contact_page	4
   contact_page	5
   front_page	1
   front_page	2
   front_page	3

五. 其他形式

1. 视图 : CRETAE VIEW 视图名 AS SLECTSTATEMENT
2. 索引 :

```sql
CREATE INDEX index_name ON TABLE base_table_name (col_name, ...) AS 'index.handler.class.name' [WITH DEFERRED REBUILD] 
--当表的数据发生变化, 自动更新分区内的全部索引
[IDXPROPERTIES (property_name=property_value, ...)]
[IN TABLE index_table_name]
[PARTITIONED BY (col_name, ...)]
[
  [ ROW FORMAT ...] STORED AS ...
  | STORED BY ...
]
[LOCATION hdfs_path]
[TBLPROPERTIES (...)]
[COMMENT "index comment"]
```