Hbase通過命令將資料批量匯入的方法
拋磚引玉：
hbase建表：
hbase(main):003:0> create 'people','0'
將提前準備好的資料上傳到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
將剛上傳到hdfs上的資料通過hbase bulkload匯入到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工具只從HDFS中讀取資料，所以就需要將資料從Linux本地匯入到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
其實hbase本身就已經提供了直接通過命令列模式來將資料直接批量匯入到hbase中去（第4個不是自帶的，是第三方外掛），但我感覺這種命令列只適合那種比較簡單的場景，需求複雜的話還得自己編寫程式碼吧。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
目前總結了四種方法：
(1)利用ImportTsv將檔案匯入到Hbase中
可直接將CSV檔案匯入到hbase表中，不過得先在hbase中建立相應的表
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 /
再執行：
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將資料匯入到hbase中
和最上面那種匯入people的方法一樣，只不過上面的方法先在hbase中建立相應的表，而這個方法不用先建表，在指令裡就可以在hbase中自動建表了
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
（在指定路徑生成了HFile檔案並且在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
或者這條命令
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將資料匯入到hbase中
首先hbase中存在hbase-tb1-002表並且其中有資料：
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格式的資料檔案，用hadoop fs -cat命令檢視亂碼)
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
（並且/test-output/part-m-00000不會像用completebulkload時消失）
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"參考地址：http://blog.csdn.net/maomaosi2009/article/details/45623821 （這個部落格中說在匯入資料的時候寫file:///指定為本地檔案路徑雖然報錯但可以匯入資料，我做的結果是報錯並且不會匯入資料，在Phoenix中查詢該表為空）
http://blog.csdn.net/d6619309/article/details/51334126
（做這個實驗我在裝有Apache版的hbase和Phoenix中成功了，但是在cdh版中卻失敗了，並且報這個錯：
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.<init>(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$2.run(YarnChild.java:163)
at java.security.AccessController.doPrivileged(Native Method)
at javax.security.auth.Subject.doAs(Subject.java:415)
at org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1671)
at org.apache.hadoop.mapred.YarnChild.main(YarnChild.java:158)解決：後來我試探性的將phoenix-4.6.0-cdh5.5.2-client.jar複製到了主節點/home/hadoop/hbase-1.0.0-cdh5.5.2/lib再執行以上命令就好使了
在phoenix的CLI介面建立user表：
0: jdbc:phoenix:h40,h41,h42:2181> create table user (id varchar primary key,account varchar ,passwd varchar);
在【PHOENIX_HOME】目錄下建立data_import.txt，內容如下：
[hadoop@h40 ~]$ vi data_import.txt
001,google,AM
002,baidu,BJ
003,alibaba,HZ
執行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=