Hbase通过命令将数据批量导入的方法
抛砖引玉：
hbase建表：
hbase(main):003:0> create 'people','0'
将提前准备好的数据上传到hdfs：
[hadoop@h71 ~]$ vi people.txt
1,jimmy,25,jiujinshan
2,tina,25,hunan
[hadoop@h71 ~]$ hadoop fs -mkdir /bulkload
[hadoop@h71 ~]$ hadoop fs -put people.txt /bulkload
将刚上传到hdfs上的数据通过hbase bulkload导入到hbase：
importtsv:
HADOOP_CLASSPATH=`/home/hadoop/hbase-1.0.0-cdh5.5.2/bin/hbase classpath` /home/hadoop/hadoop-2.6.0-cdh5.5.2/bin/hadoop jar /home/hadoop/hbase-1.0.0-cdh5.5.2/lib/hbase-server-1.0.0-cdh5.5.2.jar importtsv -Dimporttsv.separator=, -Dimporttsv.columns=HBASE_ROW_KEY,0:name,0:age,0:province -Dimporttsv.bulk.output=hdfs:///bulkload/output people hdfs:///bulkload/people.txt
（importtsv工具只从HDFS中读取数据，所以就需要将数据从Linux本地导入到HDFS中）
[hadoop@h71 ~]$ hadoop fs -lsr /bulkload
drwxr-xr-x - hadoop supergroup 0 2017-03-20 02:16 /bulkload/output
drwxr-xr-x - hadoop supergroup 0 2017-03-20 02:15 /bulkload/output/0
-rw-r--r-- 2 hadoop supergroup 1247 2017-03-20 02:16 /bulkload/output/0/e9124651e9e04ab29794572e67b87736
-rw-r--r-- 2 hadoop supergroup 0 2017-03-20 02:16 /bulkload/output/_SUCCESS
-rw-r--r-- 2 hadoop supergroup 38 2017-03-20 01:50 /bulkload/people.txt
completebulkload:
HADOOP_CLASSPATH=`/home/hadoop/hbase-1.0.0-cdh5.5.2/bin/hbase classpath` /home/hadoop/hadoop-2.6.0-cdh5.5.2/bin/hadoop jar /home/hadoop/hbase-1.0.0-cdh5.5.2/lib/hbase-server-1.0.0-cdh5.5.2.jar completebulkload hdfs:///bulkload/output people
hbase(main):004:0> scan 'people'
ROW COLUMN+CELL
1 column=0:age, timestamp=1489947175529, value=25
1 column=0:name, timestamp=1489947175529, value=jimmy
1 column=0:province, timestamp=1489947175529, value=jiujinshan
2 column=0:age, timestamp=1489947175529, value=25
2 column=0:name, timestamp=1489947175529, value=tina
2 column=0:province, timestamp=1489947175529, value=hunan目前总结了四种方法：
(1)利用ImportTsv将文件导入到Hbase中
可直接将CSV文件导入到hbase表中，不过得先在hbase中建立相应的表
hbase(main):012:0> create 'hbase-tb1-001','cf'
[hadoop@h71 ~]$ vi simple.csv
1,"tom"
2,"sam"
3,"jerry"
4,"marry"
5,"john"
[hadoop@h71 ~]$ hadoop fs -put simple.csv /
再执行：
HADOOP_CLASSPATH=`/home/hadoop/hbase-1.0.0-cdh5.5.2/bin/hbase classpath` /home/hadoop/hadoop-2.6.0-cdh5.5.2/bin/hadoop jar /home/hadoop/hbase-1.0.0-cdh5.5.2/lib/hbase-server-1.0.0-cdh5.5.2.jar importtsv -Dimporttsv.separator=, -Dimporttsv.columns=HBASE_ROW_KEY,cf hbase-tb1-001 /simple.csv
(2)利用completebulkload将数据导入到hbase中
和最上面那种导入people的方法一样，只不过上面的方法先在hbase中建立相应的表，而这个方法不用先建表，在指令里就可以在hbase中自动建表了
HADOOP_CLASSPATH=`/home/hadoop/hbase-1.0.0-cdh5.5.2/bin/hbase classpath` /home/hadoop/hadoop-2.6.0-cdh5.5.2/bin/hadoop jar /home/hadoop/hbase-1.0.0-cdh5.5.2/lib/hbase-server-1.0.0-cdh5.5.2.jar importtsv -Dimporttsv.separator=, -Dimporttsv.bulk.output=/output -Dimporttsv.columns=HBASE_ROW_KEY,cf hbase-tb1-002 /simple.csv
（在指定路径生成了HFile文件并且在hbase中建立了hbase-tb1-002空表）
HADOOP_CLASSPATH=`/home/hadoop/hbase-1.0.0-cdh5.5.2/bin/hbase classpath` /home/hadoop/hadoop-2.6.0-cdh5.5.2/bin/hadoop jar /home/hadoop/hbase-1.0.0-cdh5.5.2/lib/hbase-server-1.0.0-cdh5.5.2.jar completebulkload /output hbase-tb1-002
或者这条命令
hadoop jar /home/hadoop/hbase-1.0.0-cdh5.5.2/lib/hbase-server-1.0.0-cdh5.5.2.jar completebulkload /output hbase-tb1-002
hbase(main):014:0> scan 'hbase-tb1-002'
ROW COLUMN+CELL
1 column=cf:, timestamp=1489846700133, value="tom"
2 column=cf:, timestamp=1489846700133, value="sam"
3 column=cf:, timestamp=1489846700133, value="jerry"
4 column=cf:, timestamp=1489846700133, value="marry"
5 column=cf:, timestamp=1489846700133, value="john"(3)利用improt将数据导入到hbase中
首先hbase中存在hbase-tb1-002表并且其中有数据：
hbase(main):014:0> scan 'hbase-tb1-002'
ROW COLUMN+CELL
1 column=cf:, timestamp=1489846700133, value="tom"
2 column=cf:, timestamp=1489846700133, value="sam"
3 column=cf:, timestamp=1489846700133, value="jerry"
4 column=cf:, timestamp=1489846700133, value="marry"
5 column=cf:, timestamp=1489846700133, value="john"（在hbase0.96中用的命令是bin/hbase org.apache.hadoop.hbase.mapreduce.Export hbase-tb1-002 /test-output）
[hadoop@h71 hbase-1.0.0-cdh5.5.2]$ hadoop fs -lsr /test-output
-rw-r--r-- 2 hadoop supergroup 0 2017-03-19 00:16 /test-output/_SUCCESS
-rw-r--r-- 2 hadoop supergroup 344 2017-03-19 00:16 /test-output/part-m-00000
(生成的是sequence file格式的数据文件，用hadoop fs -cat命令查看乱码)
hbase(main):025:0> create 'hbase-tb1-003','cf'
hadoop jar /home/hadoop/hbase-1.0.0-cdh5.5.2/lib/hbase-server-1.0.0-cdh5.5.2.jar import hbase-tb1-003 /test-output
（并且/test-output/part-m-00000不会像用completebulkload时消失）
hbase(main):026:0> scan 'hbase-tb1-003'
ROW COLUMN+CELL
1 column=cf:, timestamp=1489853023886, value="tom"
2 column=cf:, timestamp=1489853023886, value="sam"
3 column=cf:, timestamp=1489853023886, value="jerry"
4 column=cf:, timestamp=1489853023886, value="marry"
5 column=cf:, timestamp=1489853023886, value="john"参考地址：http://blog.csdn.net/maomaosi2009/article/details/45623821 （这个博客中说在导入数据的时候写file:///指定为本地文件路径虽然报错但可以导入数据，我做的结果是报错并且不会导入数据，在Phoenix中查询该表为空）
http://blog.csdn.net/d6619309/article/details/51334126
（做这个实验我在装有Apache版的hbase和Phoenix中成功了，但是在cdh版中却失败了，并且报这个错：
Error: java.lang.ClassNotFoundException: org.apache.commons.csv.CSVFormat
at java.net.URLClassLoader$1.run(URLClassLoader.java:366)
at java.net.URLClassLoader$1.run(URLClassLoader.java:355)
at java.security.AccessController.doPrivileged(Native Method)
at java.net.URLClassLoader.findClass(URLClassLoader.java:354)
at java.lang.ClassLoader.loadClass(ClassLoader.java:424)
at sun.misc.Launcher$AppClassLoader.loadClass(Launcher.java:308)
at java.lang.ClassLoader.loadClass(ClassLoader.java:357)
at org.apache.phoenix.mapreduce.CsvToKeyValueMapper$CsvLineParser.(CsvToKeyValueMapper.java:282)
at org.apache.phoenix.mapreduce.CsvToKeyValueMapper.setup(CsvToKeyValueMapper.java:142)
at org.apache.hadoop.mapreduce.Mapper.run(Mapper.java:142)
at org.apache.hadoop.mapred.MapTask.runNewMapper(MapTask.java:787)
at org.apache.hadoop.mapred.MapTask.run(MapTask.java:341)
at org.apache.hadoop.mapred.YarnChild$2.run(YarnChild.java:163)
at java.security.AccessController.doPrivileged(Native Method)
at javax.security.auth.Subject.doAs(Subject.java:415)
at org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1671)
at org.apache.hadoop.mapred.YarnChild.main(YarnChild.java:158) 解决：后来我试探性的将phoenix-4.6.0-cdh5.5.2-client.jar复制到了主节点/home/hadoop/hbase-1.0.0-cdh5.5.2/lib再执行以上命令就好使了
在phoenix的CLI界面创建user表：
0: jdbc:phoenix:h40,h41,h42:2181> create table user (id varchar primary key,account varchar ,passwd varchar);
在【PHOENIX_HOME】目录下创建data_import.txt，内容如下：
[hadoop@h40 ~]$ vi data_import.txt
001,google,AM
002,baidu,BJ
003,alibaba,HZ
执行MapReduce
[hadoop@h40 phoenix-4.6.0-HBase-1.0-bin]$ hadoop jar phoenix-4.6.0-HBase-1.0-client.jar org.apache.phoenix.mapreduce.CsvBulkLoadTool --table USER --input /data_import.txt
0: jdbc:phoenix:h40,h41,h42:2181> select * from user;
+------------------------------------------+------------------------------------------+------------------------------------------+
| ID | ACCOUNT | PASSWD |
+------------------------------------------+------------------------------------------+------------------------------------------+
| 001 | google | AM |
| 002 | baidu | BJ |
| 003 | alibaba | HZ |
+------------------------------------------+------------------------------------------+------------------------------------------+
hbase(main):004:0> scan 'USER'
ROW COLUMN+CELL
001 column=0:ACCOUNT, timestamp=1492424759793, value=google
001 column=0:PASSWD, timestamp=1492424759793, value=AM
001 column=0:_0, timestamp=1492424759793, value=
002 column=0:ACCOUNT, timestamp=1492424759793, value=baidu
002 column=0:PASSWD, timestamp=1492424759793, value=BJ
002 column=0:_0, timestamp=1492424759793, value=
003 column=0:ACCOUNT, timestamp=1492424759793, value=alibaba
003 column=0:PASSWD, timestamp=1492424759793, value=HZ
003 column=0:_0, timestamp=1492424759793, value=