Hive 基本使用

CREATE TABLE emp(
empno int,
ename string,
job string,
mgr int,
hiredate string,
sal double,
comm double,
deptno int
) ROW FORMAT DELIMITED FIELDS TERMINATED BY ‘\t‘;

LOAD DATA LOCAL INPATH ‘/home/hadoop/data/emp.txt‘ OVERWRITE INTO TABLE emp;

MANAGED_TABLE:内部表
删除表：HDFS上的数据被删除 & Meta也被删除

CREATE EXTERNAL TABLE emp_external(    # 加入EXTERNAL创建的表就是
empno int,
ename string,
job string,
mgr int,
hiredate string,
sal double,
comm double,
deptno int
) ROW FORMAT DELIMITED FIELDS TERMINATED BY ‘\t‘
location ‘/external/emp/‘;

LOAD DATA LOCAL INPATH ‘/home/hadoop/data/emp.txt‘ OVERWRITE INTO TABLE emp_external;


EXTERNAL_TABLE
	HDFS上的数据不被删除 & Meta被删除

create external table track_info(
ip string,
country string,
province string,
city string,
url string,
time string,
page string
) partitioned by (day string)   # partitioned by 分区表  根据day进行分区
ROW FORMAT DELIMITED FIELDS TERMINATED BY ‘\t‘
location ‘/project/trackinfo/‘;

crontab表达式进行调度
Azkaban调度：ETLApp==>其他的统计分析
	PySpark及调度系统
		https://coding.imooc.com/class/chapter/249.html#Anchor

LOAD DATA INPATH ‘hdfs://192.168.107.216:8020/project/input/raw/train_data.txt‘ OVERWRITE INTO TABLE track_info partition(day=‘2013-07-21‘);  # partition(day=‘2013-07-21‘) 前面建表时候 制定的分区

select count(*) from track_info where day=‘2013-07-21‘;

select province,count(*) as cnt from track_info where day=‘2013-07-21‘ group by province ;



省份统计表
create table track_info_province_stat(
province string,
cnt bigint
) partitioned by (day string)
ROW FORMAT DELIMITED FIELDS TERMINATED BY ‘\t‘;

insert overwrite table track_info_province_stat partition(day=‘2013-07-21‘)
select province,count(*) as cnt from track_info where day=‘2013-07-21‘ group by province ;

到现在为止，我们统计的数据已经在Hive表track_info_province_stat
而且这个表是一个分区表，后续统计报表的数据可以直接从这个表中查询
也可以将hive表的数据导出到RDBMS（sqoop）