Hive 基本指令

1、show databases;

查看都有哪些數據庫

hive> show databases;
OK
default
Time taken: 0.141 seconds, Fetched: 2 row(s)
hive>

2、create database park;

創建park數據庫

hive> create database park;
OK
Time taken: 0.376 seconds
hive> show databases;
OK
default
park
Time taken: 0.027 seconds, Fetched: 2 row(s)
hive>

3、use park;

進入park數據庫

hive> use  park;
OK
Time taken: 0.057 seconds
hive>

4、show tables;

查看當前數據庫下所有表

hive> show tables;
OK
Time taken: 0.046 seconds
hive>

5、create table stu(id int,name string);

創建stu表，以及相關的兩個字段

hive> create table stu(id int,name string);
OK
Time taken: 0.482 seconds
hive> show tables;
OK
stu
Time taken: 0.055 seconds, Fetched: 1 row(s)
hive>

6、insert into stu values(1,‘zhang’);

向stu表插入數據

hive> insert into stu values(1,'zhang');
Query ID = root_20200528154450_bee5a3e2-dc10-4016-9d78-28f1bfea2406
Total jobs = 3
Launching Job 1 out of 3
Number of reduce tasks is set to 0 since there's no reduce operator
Starting Job = job_1590626315637_0002, Tracking URL = http://node1:8088/proxy/application_1590626315637_0002/
Kill Command = /usr/local/src/hadoop-2.9.2/bin/hadoop job  -kill job_1590626315637_0002
Hadoop job information for Stage-1: number of mappers: 1; number of reducers: 0
2020-05-28 15:45:48,732 Stage-1 map = 0%,  reduce = 0%
2020-05-28 15:46:13,543 Stage-1 map = 100%,  reduce = 0%, Cumulative CPU 3.03 sec
MapReduce Total cumulative CPU time: 3 seconds 30 msec
Ended Job = job_1590626315637_0002
Stage-4 is selected by condition resolver.
Stage-3 is filtered out by condition resolver.
Stage-5 is filtered out by condition resolver.
Moving data to: hdfs://node1:9000/user/hive/warehouse/park.db/stu/.hive-staging_hive_2020-05-28_15-44-50_434_1338240324720857993-1/-ext-10000
Loading data to table park.stu
Table park.stu stats: [numFiles=1, numRows=1, totalSize=8, rawDataSize=7]
MapReduce Jobs Launched:
Stage-Stage-1: Map: 1   Cumulative CPU: 3.3 sec   HDFS Read: 3478 HDFS Write: 72 SUCCESS
Total MapReduce CPU Time Spent: 3 seconds 300 msec
OK
Time taken: 116.87 seconds
hive>

7、select * from stu;

查看錶數據

hive> select * from stu;
OK
1       zhang
Time taken: 1.273 seconds, Fetched: 1 row(s)
hive>

8、load data local inpath ‘2.txt’ into table stu;

通過加載文件數據到指定的表裏( 默認當前目錄爲 root/ )
也可以通過其它方法直接上傳到hdfs hive 數據庫中

[root@node1 ~]# vi 2.txt
[root@node1 ~]# cat 2.txt
2 mei
[root@node1 ~]#

hive> select * from stu;
OK
1       zhang
NULL    NULL
Time taken: 0.691 seconds, Fetched: 2 row(s)
hive>

加載文件數據到stu表，出現空字符

即第一列和第二列是以空格爲分隔符的。 但是把數據導入到hive之後，hive並不知道分隔符是什麼，所以就不能正確的切分數
據。所以顯示null。 解決辦法：在hive創建表的時候，要指定分割符，並且這個分割符要和外部文件裏的 分割符一致。

9、create table stu1(idint,name string) row format delimited fields terminated by ’ ';

創建stu1表，並指定分割符空格。

hive> create table stu1(id int,name string) row format delimited fields terminated by ' ';
OK
Time taken: 0.567 seconds
hive> show tables;
OK
stu
stu1
Time taken: 0.078 seconds, Fetched: 3 row(s)
hive>

此時，把外部數據導入hive，就可以正確查出數據了。

hive> select * from stu1;
OK
1       zhang
2       wang
3       li
4       zhao
5       chen
6       liu
7       huang
8       yang
9       bai
Time taken: 0.188 seconds, Fetched: 9 row(s)
hive>

10、desc stu;

查看stu表結構

hive> desc  stu;
OK
id                      int
name                    string
Time taken: 0.287 seconds, Fetched: 2 row(s)
hive>

11、create table stu2 like stu;

創建一張stu2表，表結構和stu表結構相同

hive> show tables;
OK
stu
stu1
stu2
values__tmp__table__2
Time taken: 0.027 seconds, Fetched: 4 row(s)
hive> desc stu2;
OK
id                      int
name                    string
Time taken: 0.219 seconds, Fetched: 2 row(s)
hive>

12、alter table stu rename to stu3;

爲表stu重命名爲stu1

hive> alter table  stu rename to stu3;
OK
Time taken: 0.365 seconds
hive> show tables;
OK
stu1
stu2
stu3
values__tmp__table__2
Time taken: 0.116 seconds, Fetched: 4 row(s)
hive>

13、alter table stu3 add columns (age int);

爲表stu1增加一個列字段age，類型爲int

hive> alter table stu3 add columns (age int);
OK
Time taken: 0.292 seconds
hive> desc stu3;
OK
id                      int
name                    string
age                     int
Time taken: 0.193 seconds, Fetched: 3 row(s)
hive>

14、 insert overwrite table stu1 select * from stu2;

把stu2表數據插入到stu1表中(只有兩個表屬性相同才能插入)

hive> desc stu2;
OK
id                      int
name                    string
Time taken: 0.124 seconds, Fetched: 2 row(s)
hive> desc stu1;
OK
id                      int
name                    string
Time taken: 0.115 seconds, Fetched: 2 row(s)
hive> insert overwrite table stu1 select * from stu2;
Query ID = root_20200528161455_dce43421-aafd-481f-a3d8-1a6f45e8fdfd
Total jobs = 3
Launching Job 1 out of 3
Number of reduce tasks is set to 0 since there's no reduce operator
Starting Job = job_1590626315637_0003, Tracking URL = http://node1:8088/proxy/application_1590626315637_0003/
Kill Command = /usr/local/src/hadoop-2.9.2/bin/hadoop job  -kill job_1590626315637_0003
Hadoop job information for Stage-1: number of mappers: 1; number of reducers: 0
2020-05-28 16:15:23,968 Stage-1 map = 0%,  reduce = 0%
2020-05-28 16:15:37,798 Stage-1 map = 100%,  reduce = 0%, Cumulative CPU 1.38 sec
MapReduce Total cumulative CPU time: 1 seconds 380 msec
Ended Job = job_1590626315637_0003
Stage-4 is selected by condition resolver.
Stage-3 is filtered out by condition resolver.
Stage-5 is filtered out by condition resolver.
Moving data to: hdfs://node1:9000/user/hive/warehouse/park.db/stu1/.hive-staging_hive_2020-05-28_16-14-55_929_8015397837048918811-1/-ext-10000
Loading data to table park.stu1
Table park.stu1 stats: [numFiles=1, numRows=0, totalSize=0, rawDataSize=0]
MapReduce Jobs Launched:
Stage-Stage-1: Map: 1   Cumulative CPU: 1.38 sec   HDFS Read: 3223 HDFS Write: 35 SUCCESS
Total MapReduce CPU Time Spent: 1 seconds 380 msec
OK
Time taken: 47.245 seconds
hive>

15、insert overwrite local directory ‘/stu’ row format delimited fields terminated by ’ ’ select * from stu3;

將查詢到的數據保存到本地(不加local 保存到HDFS)

16、insert overwrite directory ‘/stu6’ row format delimited fields terminated by ’ ’ select * from stu3;

保存查詢數據到HDFS

hive> insert overwrite  directory '/stu6' row format delimited fields terminated by ' ' select * from stu3;
Query ID = root_20200528162300_48d95d4f-c2c3-46c2-a522-6c2a71b9c8ca
Total jobs = 3
Launching Job 1 out of 3
Number of reduce tasks is set to 0 since there's no reduce operator
Starting Job = job_1590626315637_0005, Tracking URL = http://node1:8088/proxy/application_1590626315637_0005/
Kill Command = /usr/local/src/hadoop-2.9.2/bin/hadoop job  -kill job_1590626315637_0005
Hadoop job information for Stage-1: number of mappers: 1; number of reducers: 0
2020-05-28 16:23:21,807 Stage-1 map = 0%,  reduce = 0%
2020-05-28 16:23:34,654 Stage-1 map = 100%,  reduce = 0%, Cumulative CPU 2.48 sec
MapReduce Total cumulative CPU time: 2 seconds 480 msec
Ended Job = job_1590626315637_0005
Stage-3 is selected by condition resolver.
Stage-2 is filtered out by condition resolver.
Stage-4 is filtered out by condition resolver.
Moving data to: hdfs://node1:9000/stu6/.hive-staging_hive_2020-05-28_16-23-00_136_8301333514132090063-1/-ext-10000
Moving data to: /stu6
MapReduce Jobs Launched:
Stage-Stage-1: Map: 1   Cumulative CPU: 2.48 sec   HDFS Read: 3051 HDFS Write: 20 SUCCESS
Total MapReduce CPU Time Spent: 2 seconds 480 msec
OK
Time taken: 38.871 seconds
hive>