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420 lines
14 KiB
Markdown
420 lines
14 KiB
Markdown
# Hbase094XReader & Hbase11XReader 插件文档
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___
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## 1 快速介绍
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HbaseReader 插件实现了从 Hbase中读取数据。在底层实现上，HbaseReader 通过 HBase 的 Java 客户端连接远程 HBase 服务，并通过 Scan 方式读取你指定 rowkey 范围内的数据，并将读取的数据使用 DataX 自定义的数据类型拼装为抽象的数据集，并传递给下游 Writer 处理。
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### 1.1支持的功能
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1、目前HbaseReader支持的Hbase版本有：Hbase0.94.x和Hbase1.1.x。
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* 若您的hbase版本为Hbase0.94.x，reader端的插件请选择：hbase094xreader，即：
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```
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"reader": {
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"name": "hbase094xreader"
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}
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```
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* 若您的hbase版本为Hbase1.1.x，reader端的插件请选择：hbase11xreader,即：
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```
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"reader": {
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"name": "hbase11xreader"
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}
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```
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2、目前HbaseReader支持两模式读取：normal 模式、multiVersionFixedColumn模式；
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* normal 模式：把HBase中的表，当成普通二维表（横表）进行读取,读取最新版本数据。如：
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```
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hbase(main):017:0> scan 'users'
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ROW COLUMN+CELL
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lisi column=address:city, timestamp=1457101972764, value=beijing
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lisi column=address:contry, timestamp=1457102773908, value=china
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lisi column=address:province, timestamp=1457101972736, value=beijing
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lisi column=info:age, timestamp=1457101972548, value=27
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lisi column=info:birthday, timestamp=1457101972604, value=1987-06-17
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lisi column=info:company, timestamp=1457101972653, value=baidu
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xiaoming column=address:city, timestamp=1457082196082, value=hangzhou
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xiaoming column=address:contry, timestamp=1457082195729, value=china
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xiaoming column=address:province, timestamp=1457082195773, value=zhejiang
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xiaoming column=info:age, timestamp=1457082218735, value=29
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xiaoming column=info:birthday, timestamp=1457082186830, value=1987-06-17
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xiaoming column=info:company, timestamp=1457082189826, value=alibaba
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2 row(s) in 0.0580 seconds
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```
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读取后数据
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| rowKey | addres:city | address:contry | address:province | info:age| info:birthday | info:company |
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| --------| ---------------- |----- |----- |--------| ---------------- |----- |
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| lisi | beijing| china| beijing |27 | 1987-06-17 | baidu|
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| xiaoming | hangzhou| china | zhejiang|29 | 1987-06-17 | alibaba|
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* multiVersionFixedColumn模式：把HBase中的表，当成竖表进行读取。读出的每条记录一定是四列形式，依次为：rowKey，family:qualifier，timestamp，value。读取时需要明确指定要读取的列，把每一个 cell 中的值，作为一条记录（record），若有多个版本就有多条记录（record）。如：
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```
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hbase(main):018:0> scan 'users',{VERSIONS=>5}
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ROW COLUMN+CELL
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lisi column=address:city, timestamp=1457101972764, value=beijing
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lisi column=address:contry, timestamp=1457102773908, value=china
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lisi column=address:province, timestamp=1457101972736, value=beijing
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lisi column=info:age, timestamp=1457101972548, value=27
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lisi column=info:birthday, timestamp=1457101972604, value=1987-06-17
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lisi column=info:company, timestamp=1457101972653, value=baidu
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xiaoming column=address:city, timestamp=1457082196082, value=hangzhou
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xiaoming column=address:contry, timestamp=1457082195729, value=china
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xiaoming column=address:province, timestamp=1457082195773, value=zhejiang
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xiaoming column=info:age, timestamp=1457082218735, value=29
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xiaoming column=info:age, timestamp=1457082178630, value=24
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xiaoming column=info:birthday, timestamp=1457082186830, value=1987-06-17
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xiaoming column=info:company, timestamp=1457082189826, value=alibaba
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2 row(s) in 0.0260 seconds
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```
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读取后数据(4列)
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| rowKey | column:qualifier| timestamp | value |
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| --------| ---------------- |----- |----- |
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| lisi | address:city| 1457101972764 | beijing |
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| lisi | address:contry| 1457102773908 | china |
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| lisi | address:province| 1457101972736 | beijing |
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| lisi | info:age| 1457101972548 | 27 |
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| lisi | info:birthday| 1457101972604 | 1987-06-17 |
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| lisi | info:company| 1457101972653 | beijing |
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| xiaoming | address:city| 1457082196082 | hangzhou |
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| xiaoming | address:contry| 1457082195729 | china |
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| xiaoming | address:province| 1457082195773 | zhejiang |
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| xiaoming | info:age| 1457082218735 | 29 |
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| xiaoming | info:age| 1457082178630 | 24 |
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| xiaoming | info:birthday| 1457082186830 | 1987-06-17 |
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| xiaoming | info:company| 1457082189826 | alibaba |
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### 1.2 限制
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1、目前不支持动态列的读取。考虑网络传输流量（支持动态列，需要先将hbase所有列的数据读取出来，再按规则进行过滤），现支持的两种读取模式中需要用户明确指定要读取的列。
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2、关于同步作业的切分：目前的切分方式是根据用户hbase表数据的region分布进行切分。即：在用户填写的［startrowkey，endrowkey］范围内，一个region会切分成一个task，单个region不进行切分。
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3、multiVersionFixedColumn模式下不支持增加常量列
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## 2 实现原理
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简而言之，HbaseReader 通过 HBase 的 Java 客户端，通过 HTable, Scan, ResultScanner 等 API，读取你指定 rowkey 范围内的数据，并将读取的数据使用 DataX 自定义的数据类型拼装为抽象的数据集，并传递给下游 Writer 处理。hbase11xreader与hbase094xreader的主要不同在于API的调用不同，Hbase1.1.x废弃了很多Hbase0.94.x的api。
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## 3 功能说明
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### 3.1 配置样例
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* 配置一个从 HBase 抽取数据到本地的作业:（normal 模式）
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```
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{
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"job": {
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"setting": {
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"speed": {
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"channel": 1
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}
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},
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"content": [
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{
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"reader": {
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"name": "hbase11xreader",
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"parameter": {
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"hbaseConfig": {
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"hbase.zookeeper.quorum": "xxxf"
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},
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"table": "users",
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"encoding": "utf-8",
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"mode": "normal",
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"column": [
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{
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"name": "rowkey",
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"type": "string"
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},
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{
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"name": "info: age",
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"type": "string"
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},
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{
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"name": "info: birthday",
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"type": "date",
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"format":"yyyy-MM-dd"
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},
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{
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"name": "info: company",
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"type": "string"
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},
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{
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"name": "address: contry",
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"type": "string"
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},
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{
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"name": "address: province",
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"type": "string"
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},
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{
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"name": "address: city",
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"type": "string"
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}
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],
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"range": {
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"startRowkey": "",
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"endRowkey": "",
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"isBinaryRowkey": true
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}
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}
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},
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"writer": {
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"name": "txtfilewriter",
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"parameter": {
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"path": "/Users/shf/workplace/datax_test/hbase11xreader/result",
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"fileName": "qiran",
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"writeMode": "truncate"
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}
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}
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}
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]
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}
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}
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```
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* 配置一个从 HBase 抽取数据到本地的作业:（ multiVersionFixedColumn 模式）
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```
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{
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"job": {
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"setting": {
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"speed": {
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"channel": 1
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}
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},
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"content": [
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{
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"reader": {
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"name": "hbase11xreader",
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"parameter": {
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"hbaseConfig": {
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"hbase.zookeeper.quorum": "xxx"
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},
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"table": "users",
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"encoding": "utf-8",
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"mode": "multiVersionFixedColumn",
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"maxVersion": "-1",
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"column": [
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{
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"name": "rowkey",
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"type": "string"
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},
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{
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"name": "info: age",
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"type": "string"
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},
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{
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"name": "info: birthday",
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"type": "date",
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"format":"yyyy-MM-dd"
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},
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{
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"name": "info: company",
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"type": "string"
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},
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{
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"name": "address: contry",
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"type": "string"
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},
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{
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"name": "address: province",
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"type": "string"
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},
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{
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"name": "address: city",
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"type": "string"
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}
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],
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"range": {
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"startRowkey": "",
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"endRowkey": ""
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}
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}
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},
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"writer": {
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"name": "txtfilewriter",
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"parameter": {
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"path": "/Users/shf/workplace/datax_test/hbase11xreader/result",
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"fileName": "qiran",
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"writeMode": "truncate"
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}
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}
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}
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]
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}
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}
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```
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### 3.2 参数说明
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* **hbaseConfig**
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* 描述：连接HBase集群需要的配置信息，JSON格式。必填的项是hbase.zookeeper.quorum，表示HBase的ZK链接地址。同时可以补充更多HBase client的配置，如：设置scan的cache、batch来优化与服务器的交互。
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* 必选：是 <br />
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* 默认值：无 <br />
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* **mode**
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* 描述：读取hbase的模式，支持normal 模式、multiVersionFixedColumn模式，即：normal/multiVersionFixedColumn <br />
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* 必选：是 <br />
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* 默认值：无 <br />
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* **table**
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* 描述：要读取的 hbase 表名（大小写敏感） <br />
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* 必选：是 <br />
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* 默认值：无 <br />
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* **encoding**
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* 描述：编码方式，UTF-8 或是 GBK，用于对二进制存储的 HBase byte[] 转为 String 时的编码 <br />
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* 必选：否 <br />
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* 默认值：UTF-8 <br />
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* **column**
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* 描述：要读取的hbase字段，normal 模式与multiVersionFixedColumn 模式下必填项。
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(1)、normal 模式下：name指定读取的hbase列，除了rowkey外，必须为 列族:列名 的格式，type指定源数据的类型，format指定日期类型的格式，value指定当前类型为常量，不从hbase读取数据，而是根据value值自动生成对应的列。配置格式如下：
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```
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"column":
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[
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{
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"name": "rowkey",
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"type": "string"
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},
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{
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"value": "test",
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"type": "string"
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}
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]
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```
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normal 模式下，对于用户指定Column信息，type必须填写，name/value必须选择其一。
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(2)、multiVersionFixedColumn 模式下：name指定读取的hbase列，除了rowkey外，必须为 列族:列名 的格式，type指定源数据的类型，format指定日期类型的格式 。multiVersionFixedColumn模式下不支持常量列。配置格式如下：
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```
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"column":
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[
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{
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"name": "rowkey",
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"type": "string"
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},
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{
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"name": "info: age",
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"type": "string"
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}
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]
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```
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* 必选：是<br />
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* 默认值：无 <br />
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* **maxVersion**
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* 描述：指定在多版本模式下的hbasereader读取的版本数，取值只能为－1或者大于1的数字，－1表示读取所有版本 <br />
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* 必选：multiVersionFixedColumn 模式下必填项<br />
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* 默认值：无<br />
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* **range**
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* 描述：指定hbasereader读取的rowkey范围。<br />
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startRowkey：指定开始rowkey；<br />
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endRowkey指定结束rowkey；<br />
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isBinaryRowkey：指定配置的startRowkey和endRowkey转换为byte[]时的方式，默认值为false,若为true，则调用Bytes.toBytesBinary(rowkey)方法进行转换;若为false：则调用Bytes.toBytes(rowkey)<br />
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配置格式如下：
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```
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"range": {
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"startRowkey": "aaa",
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"endRowkey": "ccc",
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"isBinaryRowkey":false
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}
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```
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<br />
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* 必选：否 <br />
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* 默认值：无 <br />
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* **scanCacheSize**
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* 描述：Hbase client每次rpc从服务器端读取的行数 <br />
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* 必选：否<br />
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* 默认值：256<br />
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* **scanBatchSize**
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* 描述：Hbase client每次rpc从服务器端读取的列数 <br />
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* 必选：否<br />
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* 默认值：100<br />
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### 3.3 类型转换
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下面列出支持的读取HBase数据类型，HbaseReader 针对 HBase 类型转换列表:
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| DataX 内部类型| HBase 数据类型 |
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| -------- | ----- |
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| Long |int, short ,long|
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| Double |float, double|
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| String |string,binarystring |
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| Date |date |
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| Boolean |boolean |
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请注意:
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* `除上述罗列字段类型外，其他类型均不支持`。
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## 4 性能报告
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略
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## 5 约束限制
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略
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## 6 FAQ
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***
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