Hive作为大数据环境下的数据仓库工具,支持基于hadoop以sql的方式执行mapreduce的任务,非常适合对大量的数据进行全量的查询分析。
本文主要讲述下hive载cli中如何导入导出数据:
导入数据
第一种方式,直接从本地文件系统导入数据
我的本机有一个test1.txt文件,这个文件中有三列数据,并且每列都是以'\t'为分隔
[root@localhost conf]# cat /usr/tmp/test1.txt
1 a1 b1
2 a2 b2
3 a3 b3
4 a4 b
创建数据表:
>create table test1(a string,b string,c string)
>row format delimited
>fields terminated by '\t'
>stored as textfile;
导入数据:
load data local inpath '/usr/tmp/test1.txt' overwrite into table test1;
其中local inpath,表明路径为本机路径
overwrite表示加载的数据会覆盖原来的内容
第二种,从hdfs文件中导入数据
首先上传数据到hdfs中
hadoop fs -put /usr/tmp/test1.txt /test1.txt
在hive中查看test1.txt文件
hive> dfs -cat /test1.txt;
1 a1 b1
2 a2 b2
3 a3 b3
4 a4 b4
创建数据表,与前面一样。导入数据的命令有些差异:
load data inpath '/test1.txt' overwrite into table test2;
第三种,基于查询insert into导入
首先定义数据表,这里直接创建带有分区的表
hive> create table test3(a string,b string,c string) partitioned by (d string) row format delimited fields terminated by '\t' stored as textfile;
OK
Time taken: 0.109 seconds
hive> describe test3;
OK
a string
b string
c string
d string
# Partition Information
# col_name data_type comment
d string
Time taken: 0.071 seconds, Fetched: 9 row(s)
通过查询直接导入数据到固定的分区表中:
hive> insert into table test3 partition(d='aaaaaa') select * from test2;
WARNING: Hive-on-MR is deprecated in Hive 2 and may not be available in the future versions. Consider using a different execution engine (i.e. spark, tez) or using Hive 1.X releases.
Query ID = root_20160823212718_9cfdbea4-42fa-4267-ac46-9ac2c357f944
Total jobs = 3
Launching Job 1 out of 3
Number of reduce tasks is set to 0 since there's no reduce operator
Job running in-process (local Hadoop)
2016-08-23 21:27:21,621 Stage-1 map = 100%, reduce = 0%
Ended Job = job_local1550375778_0001
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 directory hdfs://localhost:8020/user/hive/warehouse/test.db/test3/d=aaaaaa/.hive-staging_hive_2016-08-23_21-27-18_739_4058721562930266873-1/-ext-10000
Loading data to table test.test3 partition (d=aaaaaa)
MapReduce Jobs Launched:
Stage-Stage-1: HDFS Read: 248 HDFS Write: 175 SUCCESS
Total MapReduce CPU Time Spent: 0 msec
OK
Time taken: 3.647 seconds
通过查询观察结果
hive> select * from test3;
OK
1 a1 b1 aaaaaa
2 a2 b2 aaaaaa
3 a3 b3 aaaaaa
4 a4 b4 aaaaaa
Time taken: 0.264 seconds, Fetched: 4 row(s)
PS:也可以直接通过动态分区插入数据:
insert into table test4 partition(c) select * from test2;
分区会以文件夹命名的方式存储:
hive> dfs -ls /user/hive/warehouse/test.db/test4/;
Found 4 items
drwxr-xr-x - root supergroup 0 2016-08-23 21:33 /user/hive/warehouse/test.db/test4/c=b1
drwxr-xr-x - root supergroup 0 2016-08-23 21:33 /user/hive/warehouse/test.db/test4/c=b2
drwxr-xr-x - root supergroup 0 2016-08-23 21:33 /user/hive/warehouse/test.db/test4/c=b3
drwxr-xr-x - root supergroup 0 2016-08-23 21:33 /user/hive/warehouse/test.db/test4/c=b4
第四种,直接基于查询创建数据表
直接通过查询创建数据表:
hive> create table test5 as select * from test4;
WARNING: Hive-on-MR is deprecated in Hive 2 and may not be available in the future versions. Consider using a different execution engine (i.e. spark, tez) or using Hive 1.X releases.
Query ID = root_20160823213944_03672168-bc56-43d7-aefb-cac03a6558bf
Total jobs = 3
Launching Job 1 out of 3
Number of reduce tasks is set to 0 since there's no reduce operator
Job running in-process (local Hadoop)
2016-08-23 21:39:46,030 Stage-1 map = 100%, reduce = 0%
Ended Job = job_local855333165_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 directory hdfs://localhost:8020/user/hive/warehouse/test.db/.hive-staging_hive_2016-08-23_21-39-44_259_5484795730585321098-1/-ext-10002
Moving data to directory hdfs://localhost:8020/user/hive/warehouse/test.db/test5
MapReduce Jobs Launched:
Stage-Stage-1: HDFS Read: 600 HDFS Write: 466 SUCCESS
Total MapReduce CPU Time Spent: 0 msec
OK
Time taken: 2.184 seconds
查看结果
hive> select * from test5;
OK
1 a1 b1
2 a2 b2
3 a3 b3
4 a4 b4
Time taken: 0.147 seconds, Fetched: 4 row(s)
导出数据
导出到本地文件
执行导出本地文件命令:
hive> insert overwrite local directory '/usr/tmp/export' select * from test1;
WARNING: Hive-on-MR is deprecated in Hive 2 and may not be available in the future versions. Consider using a different execution engine (i.e. spark, tez) or using Hive 1.X releases.
Query ID = root_20160823221655_05b05863-6273-4bdd-aad2-e80d4982425d
Total jobs = 1
Launching Job 1 out of 1
Number of reduce tasks is set to 0 since there's no reduce operator
Job running in-process (local Hadoop)
2016-08-23 22:16:57,028 Stage-1 map = 100%, reduce = 0%
Ended Job = job_local8632460_0005
Moving data to local directory /usr/tmp/export
MapReduce Jobs Launched:
Stage-Stage-1: HDFS Read: 794 HDFS Write: 498 SUCCESS
Total MapReduce CPU Time Spent: 0 msec
OK
Time taken: 1.569 seconds
hive>
在本地文件查看内容:
[root@localhost export]# ll
total 4
-rw-r--r--. 1 root root 32 Aug 23 22:16 000000_0
[root@localhost export]# cat 000000_0
1a1b1
2a2b2
3a3b3
4a4b4
[root@localhost export]# pwd
/usr/tmp/export
[root@localhost export]#
导出到hdfs
hive> insert overwrite directory '/usr/tmp/test' select * from test1;
WARNING: Hive-on-MR is deprecated in Hive 2 and may not be available in the future versions. Consider using a different execution engine (i.e. spark, tez) or using Hive 1.X releases.
Query ID = root_20160823214217_e8c71bb9-a147-4518-8353-81f9adc54183
Total jobs = 3
Launching Job 1 out of 3
Number of reduce tasks is set to 0 since there's no reduce operator
Job running in-process (local Hadoop)
2016-08-23 21:42:19,257 Stage-1 map = 100%, reduce = 0%
Ended Job = job_local628523792_0004
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 directory hdfs://localhost:8020/usr/tmp/test/.hive-staging_hive_2016-08-23_21-42-17_778_6818164305996247644-1/-ext-10000
Moving data to directory /usr/tmp/test
MapReduce Jobs Launched:
Stage-Stage-1: HDFS Read: 730 HDFS Write: 498 SUCCESS
Total MapReduce CPU Time Spent: 0 msec
OK
Time taken: 1.594 seconds
导出成功,查看导出的hdfs文件
hive> dfs -cat /usr/tmp/test;
cat: `/usr/tmp/test': Is a directory
Command failed with exit code = 1
Query returned non-zero code: 1, cause: null
hive> dfs -ls /usr/tmp/test;
Found 1 items
-rwxr-xr-x 3 root supergroup 32 2016-08-23 21:42 /usr/tmp/test/000000_0
hive> dfs -cat /usr/tmp/test/000000_0;
1a1b1
2a2b2
3a3b3
4a4b4
hive>
导出到另一个表
样例可以参考前面数据导入的部分:
insert into table test3 select * from test1;
本文转自博客园xingoo的博客,原文链接:[Hadoop大数据]——Hive数据的导入导出,如需转载请自行联系原博主。
时间: 2024-12-08 12:20:44