可以通過多種方式將資料匯入hive表，.通過外部表匯入，使用者在hive上建external表，建表的同時指定hdfs路徑，在資料拷貝到指定hdf
可以通過多種方式將資料匯入hive表
1.通過外部表匯入使用者在hive上建external表，建表的同時指定hdfs路徑，在資料拷貝到指定hdfs路徑的同時，也同時完成資料插入external表。
例如：編輯檔案test.txt
$ cat test.txt
1 hello
2 world
3 test
4 case
字段之間以'\t'分割
啟動hive：
$ hive
建external表：
hive>create external table mytest(num int, name string)
> comment 'this is a test'
> row format delimited fields terminated by '\t'
> stored as textfile
> location '/data/test';
oktime taken: 0.714 seconds
hive> show tables;
okmytest
partition_test
partition_test_input
test
time taken: 0.07 seconds
hive> desc mytest ;
oknum int
name string
time taken: 0.121 seconds|
資料拷貝到hdfs：
$ hadoop fs -put test.txt /data/test
檢視hive表資料：
hive> select * from mytest;
ok1 hello
2 world
3 test
4 case
time taken: 0.375 seconds
hive>select num from mytest;
total mapreduce jobs = 1
launching job 1 out of 1
total mapreduce cpu time spent: 510 msec
oktime taken: 27.157 seconds
這種方式常常用於當hdfs上有一些歷史資料，而我們需要在這些資料上做一些hive的操作時使用。這種方式避免了資料拷貝開銷
2.從本地匯入資料不在hdfs上，直接從本地匯入hive表
檔案/home/work/test.txt內容同上
建表：hive> create table mytest2(num int, name string)
> comment 'this is a test2'
> row format delimited fields terminated by '\t'
> stored as textfile;
oktime taken: 0.077 seconds
導資料入錶：
hive>load data local inpath '/home/work/test.txt' into table mytest2;
copying data from file:/home/work/test.txt
copying file: file:/home/work/test.txt
loading data to table default.mytest2
oktime taken: 0.24 seconds
檢視資料：
hive> select * from mytest2;
ok1 hello
2 world
3 test
4 case
time taken: 0.11 seconds
這種方式匯入的本地資料可以是乙個檔案，，乙個資料夾或者萬用字元，需要注意的是，如果是資料夾，資料夾內不能包含子目錄，同樣，萬用字元只能通配檔案。
3.從hdfs匯入上述test.txt檔案已經匯入/data/test
則可以使用下述命令直接將資料匯入hive表：
hive> create table mytest3(num int, name string)
> comment "this is a test3"
> row format delimited fields terminated by '\t'
> stored as textfile;
oktime taken: 4.735 seconds
hive>load data inpath '/data/test/test.txt' into table mytest3;
loading data to table default.mytest3
oktime taken: 0.337 seconds
hive>select * from mytest3 ;
ok1 hello
2 world
3 test
4 case
time taken: 0.227 seconds
4. 從其它表匯入資料：hive> create external table mytest4(num int) ;
oktime taken: 0.091 seconds
hive> from mytest3 test3
> insert overwrite table mytest4
> select test3.num where;
total mapreduce jobs = 2
launching job 1 out of 2
number of reduce tasks is set to 0 since there's no reduce operator
starting job = job_201207230024_0002, tracking url = :50030/jobdetails.jsp?jobid=job_201207230024_0002
kill command = /home/work/hadoop/hadoop-1.0.3/libexec/../bin/hadoop job -dmapred.job.tracker=localhost:9001 -kill job_201207230024_0002
2012-07-23 18:59:02,365 stage-1 map = 0%, reduce = 0%
2012-07-23 18:59:08,417 stage-1 map = 100%, reduce = 0%, cumulative cpu 0.62 sec
2012-07-23 18:59:09,435 stage-1 map = 100%, reduce = 0%, cumulative cpu 0.62 sec
2012-07-23 18:59:10,445 stage-1 map = 100%, reduce = 0%, cumulative cpu 0.62 sec
2012-07-23 18:59:11,455 stage-1 map = 100%, reduce = 0%, cumulative cpu 0.62 sec
2012-07-23 18:59:12,470 stage-1 map = 100%, reduce = 0%, cumulative cpu 0.62 sec
2012-07-23 18:59:13,489 stage-1 map = 100%, reduce = 0%, cumulative cpu 0.62 sec
2012-07-23 18:59:14,508 stage-1 map = 100%, reduce = 100%, cumulative cpu 0.62 sec
mapreduce total cumulative cpu time: 620 msec
ended job = job_201207230024_0002
ended job = -174856900, job is filtered out (removed at runtime).
moving data to: hdfs://localhost:9000/tmp/hive-work/hive_2012-07-23_18-58-44_166_189728317691010041/-ext-10000
loading data to table default.mytest4
deleted hdfs://localhost:9000/user/hive/warehouse/mytest4
table default.mytest4 stats: [num_partitions: 0, num_files: 1, num_rows: 0, total_size: 2, raw_data_size: 0]
1 rows loaded to mytest4
mapreduce jobs launched:
job 0: map: 1 accumulative cpu: 0.62 sec hdfs read: 242 hdfs write: 2 sucess
total mapreduce cpu time spent: 620 msec
oktime taken: 30.663 seconds
hive> select * from mytest4;
oktime taken: 0.103 seconds
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