Hbase - 迁移数据--导出,导入

https://www.jianshu.com/p/045026a13bf8

有没有这样一样情况，把一个集群中的某个表导到另一个群集中，或者hbase的表结构发生了更改，但是数据还要，比如预分区没做，导致某台RegionServer很吃紧，Hbase的导出导出都可以很快的完成这些操作。

现在环境上面有一张表logTable，有一个ext列簇
但是没有做预分区，虽然可以强制拆分表，但是split的start,end范围无法精确控制。

方式一 (先导出再导出)

hadoop fs -mkdir /tmp/hbase-export

hadoop fs -ls /tmp/hbase-export

备份表数据
使用hbase内置的mr命令,会默认导出到hdfs中: 换行符去掉生效

hbase org.apache.hadoop.hbase.mapreduce.Export \
 -D hbase.mapreduce.scan.column.family=f1 \ 
icc:test hdfs:///tmp/hbase-export/test

删除表

disable 'logTable'
drop 'logTable'

创建表
数据3天过期，可以根据RegionServer的个数做预分区，假设有8台，则使用下面的方式。
由于我们是使用MD5("uid")前两位作为打散,范围为00~ff 256个分片,可以使用如下方式。

# scala shell 创建方式
(0 until 256 by 256/8).map(Integer.toHexString).map(i=>s"0$i".takeRight(2))

hbase创表

create 'logTable',{ \
  NAME => 'ext',TTL => '3 DAYS', \
  CONFIGURATION => {
  'SPLIT_POLICY' => 'org.apache.hadoop.hbase.regionserver.KeyPrefixRegionSplitPolicy', \
  'KeyPrefixRegionSplitPolicy.prefix_length' => '2' 
  }, \
  COMPRESSION => 'SNAPPY' \
}, \ 
SPLITS => ['20', '40', '60', '80', 'a0', 'c0', 'e0']

导入备份数据

hbase org.apache.hadoop.hbase.mapreduce.Import logTable hdfs:///tmp/hbase-export/logTable

注意事项

默认导出所有列簇，可通过指定-D hbase.mapreduce.scan.column.family=ext,info参数导出。
如果另一张表没有源表对应的列簇将会出错。

1.export

1> 执行导出命令

可使用-D命令自定义参数，此处限定表名、列族、开始结束RowKey、以及导出到HDFS的目录

hbase org.apache.hadoop.hbase.mapreduce.Export \
-D hbase.mapreduce.scan.column.family=0 \
-D hbase.mapreduce.scan.row.start=aaaaaaaaaaaaaaaaaaa00010078 \
-D hbase.mapreduce.scan.row.stop=jjjjjjjjjjjjjjjjjjj00010078 TESTA /tmp/hbase_export

可选的-D参数配置项

Usage: Export [-D <property=value>]* <tablename> <outputdir> [<versions> [<starttime> [<endtime>]] [^[regex pattern] or [Prefix] to filter]]

  Note: -D properties will be applied to the conf used. 
  For example: 
   -D mapred.output.compress=true
   -D mapred.output.compression.codec=org.apache.hadoop.io.compress.GzipCodec
   -D mapred.output.compression.type=BLOCK
  Additionally, the following SCAN properties can be specified
  to control/limit what is exported..
   -D hbase.mapreduce.scan.column.family=<familyName>
   -D hbase.mapreduce.include.deleted.rows=true
For performance consider the following properties:
   -Dhbase.client.scanner.caching=100
   -Dmapred.map.tasks.speculative.execution=false
   -Dmapred.reduce.tasks.speculative.execution=false
For tables with very wide rows consider setting the batch size as below:
   -Dhbase.export.scanner.batch=10

2> MR执行导出

3> 查看HDFS

2.import

1> 预先建表

在hbase中预先建立一个名称为TESTX的表，其包含一个名称为0的列族。若表事先不存在将报错

create 'TESTX','0'

2> 运行导入命令

可使用-D命令自定义参数，此处不多做限制

hbase org.apache.hadoop.hbase.mapreduce.Import TESTX hdfs://cdh01/tmp/hbase_export/

可选的-D参数配置项

Usage: Import [options] <tablename> <inputdir>

By default Import will load data directly into HBase. To instead generate
HFiles of data to prepare for a bulk data load, pass the option:
  -Dimport.bulk.output=/path/for/output
 To apply a generic org.apache.hadoop.hbase.filter.Filter to the input, use
  -Dimport.filter.class=<name of filter class>
  -Dimport.filter.args=<comma separated list of args for filter
 NOTE: The filter will be applied BEFORE doing key renames via the HBASE_IMPORTER_RENAME_CFS property. Futher, filters will only use the Filter#filterRowKey(byte[] buffer, int offset, int length) method to identify  whether the current row needs to be ignored completely for processing and  Filter#filterKeyValue(KeyValue) method to determine if the KeyValue should be added; Filter.ReturnCode#INCLUDE and #INCLUDE_AND_NEXT_COL will be considered as including the KeyValue.
For performance consider the following options:
  -Dmapred.map.tasks.speculative.execution=false
  -Dmapred.reduce.tasks.speculative.execution=false
  -Dimport.wal.durability=<Used while writing data to hbase. Allowed values are the supported durability values like SKIP_WAL/ASYNC_WAL/SYNC_WAL/...>

3> MR执行导入

4> HBase查看导入数据

三、hbase批量提数，数据需要脱敏，将hbase1的数据导入hbase2

1、建立关联hbase1的hive1外表.

hive> 
CREATE EXTERNAL TABLE china_mainland_acturl(
rowkey string,
act_url STRING
) STORED BY 'org.apache.hadoop.hive.hbase.HBaseStorageHandler'
WITH SERDEPROPERTIES ("hbase.columns.mapping" = ":key,act:url")
TBLPROPERTIES ("hbase.table.name" = "users:china_mainland")
;

2、hive -e "select * from hive1 where ***" >>data.csv

3、建立hive2的临时表table_temp ，并将data.csv上传至hsfs，hadoop fs -put localpath table_temp_hdfspath

4、建立关联hbase1的hive1外表.

5、将tabletemp表的数据插入hive2

insert into hive2 as select * from table_temp