ImportTsv 工具是通過map reduce 完成的。所以要啓動yarn. 工具要使用jar包，所以注意配置classpath。ImportTsv默認是通過hbase api 插入數據的
[hadoop-user@rhel work]$ cat /home/hadoop-user/.bash_profile
# .bash_profile
# Get the aliases and functions
if [ -f ~/.bashrc ]; then
. ~/.bashrc
fi
# User specific environment and startup programs
PATH=$PATH:$HOME/bin
export PATH
JAVA_HOME=/usr/java/jdk1.8.0_171-amd64
PATH=$PATH:$JAVA_HOME/bin
CLASSPATH=$CLASSPATH:$JAVA_HOME/lib
HADOOP_HOME=/home/hadoop-user/hadoop-2.8.0
PATH=$PATH:$HADOOP_HOME/bin:$HADOOP_HOME/sbin
CLASSPATH=$CLASSPATH:$HADOOP_HOME/lib
HBASE_HOME=/home/hadoop-user/hbase-2.0.0
PATH=$PATH:$HBASE_HOME/bin
CLASSPATH=$CLASSPATH:$HBASE_HOME/lib
ZOOKEEPER_HOME=/home/hadoop-user/zookeeper-3.4.12
PATH=$PATH:$ZOOKEEPER_HOME/bin
PHOENIX_HOME=/home/hadoop-user/apache-phoenix-5.0.0-alpha-HBase-2.0-bin
PATH=$PATH:$PHOENIX_HOME/bin
export PATH
創建表
hbase(main):033:0> create 'test','cf'
創建要導入的文件
[hadoop-user@rhel work]$ cat /home/hadoop-user/work/sample1.csv
row10,"mjj10"
row11,"mjj11"
row12,"mjj12"
row14,"mjj13"
將文件放入hdfs
[hadoop-user@rhel work]$ hdfs dfs -put /home/hadoop-user/work/sample1.csv /sample1.csv
ImportTsv導入命令
hbase org.apache.hadoop.hbase.mapreduce.ImportTsv -Dimporttsv.separator="," -Dimporttsv.columns=HBASE_ROW_KEY,cf:a test /sample1.csv
注: HBASE_ROW_KEY表示文件rowid的位置，後面是列的定義。這裏意思是導入的列爲列族爲cf,列名爲a。要導入的文件是hdfs中/sample1.csv
幫助中的解釋
Usage: importtsv -Dimporttsv.columns=a,b,c <tablename> <inputdir>
Imports the given input directory of TSV data into the specified table.
The column names of the TSV data must be specified using the -Dimporttsv.columns
option. This option takes the form of comma-separated column names, where each
column name is either a simple column family, or a columnfamily:qualifier. The special
column name HBASE_ROW_KEY is used to designate that this column should be used
as the row key for each imported record. You must specify exactly one column
to be the row key, and you must specify a column name for every column that exists in the
input data. Another special columnHBASE_TS_KEY designates that this column should be
used as timestamp for each record. Unlike HBASE_ROW_KEY, HBASE_TS_KEY is optional.
You must specify at most one column as timestamp key for each imported record.
Record with invalid timestamps (blank, non-numeric) will be treated as bad record.
Note: if you use this option, then 'importtsv.timestamp' option will be ignored.
注意: ImportTsv導入的內容，phoenix看不到。事實上，hbase創建的表，Phoenix看不到。phoenix創建的表，hbase能看到，但是內容是編碼後的內容。
importtsv 工具默認使用hbase put api導數據.當使用選項 -Dimporttsv.bulk.output時，將會先生成HFILE文件的內部格式的文件。
The importtsv tool, by default, uses the HBase Put API to insert data into the HBase
table using TableOutputFormat in its map phase. But when the -Dimporttsv.bulk.output option is specified, it instead generates HBase internal format (HFile) files on HDFS
by using HFileOutputFormat. Therefore, we can then use the completebulkload tool to load the generated files into a running cluster. The following steps are to use the bulk output and load tools:
生成HFILE格式的文件命令
hbase org.apache.hadoop.hbase.mapreduce.ImportTsv -Dimporttsv.separator="," -Dimporttsv.bulk.output=/hfiles_tsv -Dimporttsv.columns=HBASE_ROW_KEY,cf:a test /sample1.csv
注: 生成hfile格式的文件，存放於hdfs中的/hfile_tsv目錄中，目錄會由命令自己創建。
[hadoop-user@rhel work]$ hdfs dfs -ls /hfiles_tsv/cf
18/06/28 10:49:21 WARN util.NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
Found 1 items
-rw-r--r-- 1 hadoop-user supergroup 5125 2018-06-28 10:40 /hfiles_tsv/cf/0e466616d42a4a128fb60caa7dbe075a
注: 0e466616d42a4a128fb60caa7dbe075a的命名格式跟WEB中region的命名格式很像
通過
hadoop jar hbase-server-2.0.0.jar completebulkload /hfiles_tsv 'test'
出現異常； Exception in thread "main" java.lang.ClassNotFoundException: completebulkload
HBASE文檔中兩種導入方式:
There are two ways to invoke this utility, with explicit classname and via the driver:
Explicit Classname
$ bin/hbase org.apache.hadoop.hbase.tool.LoadIncrementalHFiles <hdfs://storefileoutput> <tablename>
Driver
HADOOP_CLASSPATH=`${HBASE_HOME}/bin/hbase classpath` ${HADOOP_HOME}/bin/hadoop jar ${HBASE_HOME}/hbase-server-VERSION.jar completebulkload <hdfs://storefileoutput> <tablename>