HBASE架构
HBASEshell
不做概述
HBASE的JavaAPI操作
hbase的api操作总结下来就是一句话，就是
需要对表做一些操作，就使用getAdmin()（修改表结构什么的）
需要对数据做一些操作，就使用getTable()
配置连接并尝试创建一个表：
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.hbase.HBaseConfiguration;
import org.apache.hadoop.hbase.HColumnDescriptor;
import org.apache.hadoop.hbase.HTableDescriptor;
import org.apache.hadoop.hbase.TableName;
import org.apache.hadoop.hbase.client.Admin;
import org.apache.hadoop.hbase.client.Connection;
import org.apache.hadoop.hbase.client.ConnectionFactory;
import java.io.IOException;
public class Demo01Test {
public static void main(String[] args) throws IOException {
//创建配置，指定zk的集群地址
Configuration conf = HBaseConfiguration.create();
conf.set("hbase.zookeeper.quorum","master,node1,node2");
//创建连接
Connection conn = ConnectionFactory.createConnection(conf);
//创建Admin对象
Admin admin = conn.getAdmin();
//创建test_01表
HTableDescriptor test_01 = new HTableDescriptor(TableName.valueOf("test_01"));
//创建一个列簇
HColumnDescriptor cf1 = new HColumnDescriptor("cf1");
//配置列簇
cf1.setTimeToLive(10000);//设置过期时间
cf1.setMaxVersions(3);//设置最大版本数
//增加一个列簇
test_01.addFamily(cf1);
admin.createTable(test_01);
//关闭连接
conn.close();
}
}
实现各类不同的操作：
import javafx.scene.control.Tab;
import org.apache.hadoop.hbase.*;
import org.apache.hadoop.hbase.client.*;
import org.apache.hadoop.hbase.util.Bytes;
import org.junit.After;
import org.junit.Before;
import org.junit.Test;
import java.io.BufferedReader;
import java.io.FileReader;
import java.io.IOException;
import java.util.ArrayList;
import java.util.Scanner;
public class Demo02API {
Connection conn;
@Before
public void init() throws IOException {
HBaseConfiguration conf = new HBaseConfiguration();
conf.set("hbase.zookeeper.quorum","master,node1,node2");
conn = ConnectionFactory.createConnection(conf);
}
//创建表
@Test
public void create() throws IOException {
Admin admin = conn.getAdmin();
if(!admin.tableExists(TableName.valueOf("test03"))){
HTableDescriptor test_03 = new HTableDescriptor(TableName.valueOf("test_03"));
HColumnDescriptor cf3 = new HColumnDescriptor("cf3");
cf3.setTimeToLive(1000);//设置过期时间
cf3.setMaxVersions(3);//设置版本数
test_03.addFamily(cf3);
admin.createTable(test_03);
}else {
System.out.println("表已存在");
}
}
//删除表
@Test
public void delete() throws IOException {
Admin admin = conn.getAdmin();
// Scanner sc = new Scanner(System.in);
// System.out.println("请输入要删除的表名");
// String name = sc.next();
if (admin.tableExists(TableName.valueOf("test_02"))){
admin.disableTable(TableName.valueOf("test_02"));
admin.deleteTable(TableName.valueOf("test_02"));
}else {
System.out.println("表不存在");
}
}
//修改表
@Test
public void alter() throws IOException {
Admin admin = conn.getAdmin();
TableName tableName = TableName.valueOf("test_01");
//获取表
HTableDescriptor hTableDescriptor = admin.getTableDescriptor(tableName);
//获取表的列簇数组
HColumnDescriptor[] columnFamilies = hTableDescriptor.getColumnFamilies();
//遍历所有的列簇
for (HColumnDescriptor columnFamily : columnFamilies) {
//获取所有的列簇名称
String cfname = columnFamily.getNameAsString();
if ("cf1".equals(cfname)){
columnFamily.setMaxVersions(5);//修改版本数为5
columnFamily.setTimeToLive(20000);//修改版本数为20000
}
}
admin.modifyTable(tableName,hTableDescriptor);
}
//插入数据
@Test
public void Put() throws IOException{
Table test_01 = conn.getTable(TableName.valueOf("test_01"));
Put put = new Put("001".getBytes());
// put.addColumn("cf1".getBytes(),"name".getBytes(),"张三".getBytes());
put.addColumn("cf1".getBytes(),"name".getBytes(),Bytes.toBytes("张三"));
test_01.put(put);
}
//get获取数据
@Test
public void Get() throws IOException{
Table test_01 = conn.getTable(TableName.valueOf("test_01"));
Get get = new Get("001".getBytes());
Result result = test_01.get(get);
byte[] value = result.getValue("cf1".getBytes(), "name".getBytes());
// System.out.println(value.toString());//[B@1dac5ef
System.out.println(Bytes.toString(value));
}
//scan获取数据的第一种方式
@Test
public void Scan() throws IOException{
Table test_01 = conn.getTable(TableName.valueOf("test_01"));
Scan scan = new Scan();
scan.setLimit(5);//最多只显示五条数据
scan.withStartRow("0".getBytes());//从这个行键开始读取数据
scan.withStopRow("1500".getBytes());//到这个行键结束读取数据
ResultScanner scanner = test_01.getScanner(scan);
//获取了一条条数据
for (Result result : scanner) {
String id = Bytes.toString(result.getRow());
String name = Bytes.toString(result.getValue("info".getBytes(), "name".getBytes()));
String age = Bytes.toString(result.getValue("info".getBytes(), "age".getBytes()));
String gender = Bytes.toString(result.getValue("info".getBytes(), "gender".getBytes()));
String clazz = Bytes.toString(result.getValue("info".getBytes(), "clazz".getBytes()));
System.out.println(id+","+name+","+age+","+gender+","+clazz);
}
}
//scan获取数据的第二种方式
//适用于每条数据结构不唯一的情况下，直接遍历每条数据包含的所有的cell
@Test
public void scanWithUtil() throws IOException{
Table test_01 = conn.getTable(TableName.valueOf("test_01"));
Scan scan = new Scan();
scan.setLimit(5);//最多只显示5条数据
scan.withStartRow("0".getBytes());
scan.withStopRow("150".getBytes());
ResultScanner scanner = test_01.getScanner(scan);
for (Result result : scanner) {
String rowkey = Bytes.toString(result.getRow());
System.out.println(rowkey+" ");
for (Cell cell:result.listCells()){
//列名
String column = Bytes.toString(CellUtil.cloneQualifier(cell));
//列簇名
String cf = Bytes.toString(CellUtil.cloneFamily(cell));
}
}
}
//putall读取students.txt的数据，并写入hbase
//批量插入
@Test
public void PutAll() throws IOException{
//创建students表
Admin admin = conn.getAdmin();
if(!admin.tableExists(TableName.valueOf("students"))){
HTableDescriptor students = new HTableDescriptor(TableName.valueOf("students"));
HColumnDescriptor info = new HColumnDescriptor("info");
students.addFamily(info);
admin.createTable(students);
}
Table students = conn.getTable(TableName.valueOf("students"));
BufferedReader br = new BufferedReader(new FileReader("D:\\BigDaTa\\JAVA项目\\ShuJia01\\data\\students.txt"));
String line = null;
ArrayList<Put> puts = new ArrayList<Put>();
int size=10;
while ((line=br.readLine())!=null){
//读取每一行数据
String[] split = line.split(",");
String id = split[0];
String name = split[1];
String age = split[2];
String gender = split[3];
String clazz = split[4];
Put put = new Put(id.getBytes());
put.addColumn("info".getBytes(),"name".getBytes(),name.getBytes());
put.addColumn("info".getBytes(),"age".getBytes(),age.getBytes());
put.addColumn("info".getBytes(),"gender".getBytes(),gender.getBytes());
put.addColumn("info".getBytes(),"clazz".getBytes(),clazz.getBytes());
puts.add(put);
if (puts.size()==size){
students.put(puts);
puts=new ArrayList<Put>();
}
}
if (puts.size()!=0){
students.put(puts);
}
}
//putall读取students.txt的数据，并写入hbase
//逐个插入
@Test
public void PutAllAgain() throws IOException{
Admin admin = conn.getAdmin();
if(!admin.tableExists(TableName.valueOf("students"))){
HTableDescriptor test_01 = new HTableDescriptor(TableName.valueOf("students"));
HColumnDescriptor info = new HColumnDescriptor("info");
test_01.addFamily(info);
admin.createTable(test_01);
}
Table test_01 = conn.getTable(TableName.valueOf("students"));
BufferedReader br = new BufferedReader(new FileReader("D:\\BigDaTa\\JAVA项目\\ShuJia01\\data\\students.txt"));
String line=null;
while ((line=br.readLine())!=null){
String[] split = line.split(",");
String id = split[0];
String name = split[1];
String age = split[2];
String gender = split[3];
String clazz = split[4];
Put put = new Put(id.getBytes());
put.addColumn("info".getBytes(),"name".getBytes(),name.getBytes());
put.addColumn("info".getBytes(),"age".getBytes(),age.getBytes());
put.addColumn("info".getBytes(),"gender".getBytes(),gender.getBytes());
put.addColumn("info".getBytes(),"clazz".getBytes(),clazz.getBytes());
test_01.put(put);
}
}
@After
public void close() throws IOException {
conn.close();
}
}
HBASE连接Hive
将hbase中如下图的数据样式导入到hive中，在hive中创建一个外部表（主要用hive的外部表来接收不同数据源的数据），hbase表中是一个行键（id），一个列簇下面对应四个列（name,age,gender,clazz），在hive中创建对应的表即可
hive中创建相应的表：
create external table students_hbase
(
id string,
name string,
age string,
gender string,
clazz string
)
stored by 'org.apache.hadoop.hive.hbase.HBaseStorageHandler'
with serdeproperties ("hbase.columns.mapping" = "
:key,
info:name,
info:age,
info:gender,
info:clazz
")
tblproperties("hbase.table.name" = "default:students");
数据已导入
HBASE过滤器
我们会遇到一些这样的操作：比如过滤出“文科一班”的学生，在hive里面，直接一条sql就解决了问题，但相同的问题放到hbase里面，就需要用到过滤器来做操作
我理解的过滤器，其实不过如此（过滤器一般来说会和比较器一起使用）：
简单来说，就是找到自己的需求，比如是对列进行操作，对列簇进行操作，还是对某一列的值操作，或者又是对所有列的值进行操作；在这基础上，在加上一个比较器，比如是正则比较器、二进制比较器，或者又是前缀比较器，二者合在一起，就是比较过滤器
比较器
比较运算符
- LESS <
- LESS_OR_EQUAL <=
- EQUAL =
- NOT_EQUAL <>
- GREATER_OR_EQUAL >=
- GREATER >
- NO_OP 排除所有
常见的比较器
- BinaryComparator
按照字节索引排序比较指定字节数据 - BinaryPrefixComparator
只是比较左端前缀的数据是否相同 - NullComparator
判断给定的值是否为空 - BitComparator
按位比较 - RegexStringComparator
提供一个正则的比较器，仅支持EQUAL和非EQUAL - SubstringComparator
判断提供的子串是否出现在原有的字符串中
过滤器
常见的过滤器
- rowKey过滤器：RowFilter
- 列簇过滤器：FamilyFilter
- 列过滤器：QualifierFilter
- 列值过滤器：ValueFilter
- 单列值过滤器：SingleColumnValueFilter
- 列值排除过滤器：SingleColumnValueExcludeFilter
- rowkey前缀过滤器：PrefixFilter
- 分页过滤器PageFilter
过滤器举例
使用列值过滤器和单列值过滤器分别过滤出“文科一班”的所有学生
搭好架构：
Connection conn;
Admin admin;
Table students;
TableName studentsT = TableName.valueOf("students");
public void printScannerWithFilter() throws IOException {
Scan scan = new Scan();
ResultScanner scanner = students.getScanner(scan);
for (Result result : scanner) { //一个resule就代表一行数据
List<Cell> cells = result.listCells();
String id = Bytes.toString(result.getRow());
System.out.print(id + "\t");
for (Cell cell : cells) {
// String id = Bytes.toString(CellUtil.cloneRow(cell));
String value = Bytes.toString(CellUtil.cloneValue(cell));
System.out.print(value + "\t");
}
System.out.println();
}
}
@Before
public void init() throws IOException{
Configuration conf = HBaseConfiguration.create();
conf.set("hbase.zookeeper.quorum","master,node1,node2");
conn = ConnectionFactory.createConnection(conf);
admin = conn.getAdmin();
students = conn.getTable(studentsT);
}
@After
public void close() throws IOException{
conn.close();
}
使用列值过滤器过滤出“文科一班”的学生：
//这个过滤，过滤的是所有的列，只要前面的任何一列是过滤符合标准的，就会对其进行过滤
//使用正则比较器+列值过滤器->过滤出 文科一班 的学生
//RegexStringComparator+ValueFilter
//ValueFilter 会将比较器作用到所有的列值上，也就相当于作用在每一个cell上面，
//把符合比较器规则的cell过滤出来，不符合的直接丢弃
@Test
public void RegexStringComparatorValueFilter() throws IOException {
//过滤说到底也就是一种查询，查询有两种，一个get，一个scan，过滤是scan
Scan scan = new Scan();
//第一个填的是比较运算符（大于、小于、等于，什么的）
//第二个填的是比较器，这里用的是正则表达式的比较器 ^文科.*班
RegexStringComparator regexStringComparator = new RegexStringComparator(".*班");//文科开头，班结尾的班级
ValueFilter valueFilter = new ValueFilter(
CompareFilter.CompareOp.EQUAL,
regexStringComparator
);
scan.setFilter(valueFilter);
ResultScanner scanner = students.getScanner(scan);
for (Result result : scanner) {
List<Cell> cells = result.listCells();
// for (Cell cell:cells){
// String value = Bytes.toString(CellUtil.cloneValue(cell));
// System.out.println(value);
// }
// for (Cell cell : cells) {
// String column = Bytes.toString(cell.getFamilyArray());
// String value = Bytes.toString(cell.getQualifierArray());
// System.out.println(value);
// }
String name = Bytes.toString(result.getValue("info".getBytes(), "name".getBytes()));
String age = Bytes.toString(result.getValue("info".getBytes(), "age".getBytes()));
String gender = Bytes.toString(result.getValue("info".getBytes(), "gender".getBytes()));
String clazz = Bytes.toString(result.getValue("info".getBytes(), "clazz".getBytes()));
System.out.println(name+","+age+","+gender+","+clazz);
}
}
最后发现结果是这样的，也就是说，这个过滤，过滤的是所有的列，只要前面的任何一列是过滤符合标准的，就会对其进行过滤
使用单列值过滤器过滤出“文科一班”的学生：
//SingleColumnValueFilter 这个最后会输出这一列
//SingleColumnValueExcludeFilter 这个最后会排除这一列
//单列值过滤器
@Test
public void RegexStringComparatorSingleColumnValueFilter() throws IOException {
Scan scan = new Scan();
// SingleColumnValueFilter singleColumnValueFilter = new SingleColumnValueFilter(
// "info".getBytes(),
// "clazz".getBytes(),
// CompareFilter.CompareOp.EQUAL,
// "文科一班".getBytes() //这里既可以传入字符数组，也可以传入一个比较器
// );
SingleColumnValueFilter singleColumnValueFilter = new SingleColumnValueFilter(
"info".getBytes(),
"clazz".getBytes(),
CompareFilter.CompareOp.EQUAL,
new RegexStringComparator("^文科.*班$")
);
scan.setFilter(singleColumnValueFilter);
ResultScanner scanner = students.getScanner(scan);
for (Result result : scanner) { //一个resule就代表一行数据
List<Cell> cells = result.listCells();
String id = Bytes.toString(result.getRow());
System.out.print(id+"\t");
for (Cell cell : cells) {
// String id = Bytes.toString(CellUtil.cloneRow(cell));
String value = Bytes.toString(CellUtil.cloneValue(cell));
System.out.print(value+"\t");
}
System.out.println();
// String name = Bytes.toString(result.getValue("info".getBytes(), "name".getBytes()));
// String age = Bytes.toString(result.getValue("info".getBytes(), "age".getBytes()));
// String gender = Bytes.toString(result.getValue("info".getBytes(), "gender".getBytes()));
// String clazz = Bytes.toString(result.getValue("info".getBytes(), "clazz".getBytes()));
// System.out.println(name+","+age+","+gender+","+clazz);
}
}
过滤出了文科一班的所有学生
过滤器举例的所有代码
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.hbase.Cell;
import org.apache.hadoop.hbase.CellUtil;
import org.apache.hadoop.hbase.HBaseConfiguration;
import org.apache.hadoop.hbase.TableName;
import org.apache.hadoop.hbase.client.*;
import org.apache.hadoop.hbase.filter.*;
import org.apache.hadoop.hbase.util.Bytes;
import org.junit.After;
import org.junit.Before;
import org.junit.Test;
import java.io.IOException;
import java.util.List;
public class Demo4Filter {
Connection conn;
Admin admin;
Table students;
TableName studentsT = TableName.valueOf("students");
public void printScannerWithFilter() throws IOException {
Scan scan = new Scan();
ResultScanner scanner = students.getScanner(scan);
for (Result result : scanner) { //一个resule就代表一行数据
List<Cell> cells = result.listCells();
String id = Bytes.toString(result.getRow());
System.out.print(id + "\t");
for (Cell cell : cells) {
// String id = Bytes.toString(CellUtil.cloneRow(cell));
String value = Bytes.toString(CellUtil.cloneValue(cell));
System.out.print(value + "\t");
}
System.out.println();
}
}
@Before
public void init() throws IOException{
Configuration conf = HBaseConfiguration.create();
conf.set("hbase.zookeeper.quorum","master,node1,node2");
conn = ConnectionFactory.createConnection(conf);
admin = conn.getAdmin();
students = conn.getTable(studentsT);
}
//这个过滤，过滤的是所有的列，只要前面的任何一列是过滤符合标准的，就会对其进行过滤
//使用正则比较器+列值过滤器->过滤出 文科一班 的学生
//RegexStringComparator+ValueFilter
//ValueFilter 会将比较器作用到所有的列值上，也就相当于作用在每一个cell上面，
//把符合比较器规则的cell过滤出来，不符合的直接丢弃
@Test
public void RegexStringComparatorValueFilter() throws IOException {
//过滤说到底也就是一种查询，查询有两种，一个get，一个scan，过滤是scan
Scan scan = new Scan();
//第一个填的是比较运算符（大于、小于、等于，什么的）
//第二个填的是比较器，这里用的是正则表达式的比较器 ^文科.*班
RegexStringComparator regexStringComparator = new RegexStringComparator(".*班");//文科开头，班结尾的班级
ValueFilter valueFilter = new ValueFilter(
CompareFilter.CompareOp.EQUAL,
regexStringComparator
);
scan.setFilter(valueFilter);
printScannerWithFilter();
// ResultScanner scanner = students.getScanner(scan);
// for (Result result : scanner) {
// List<Cell> cells = result.listCells();
//// for (Cell cell:cells){
//// String value = Bytes.toString(CellUtil.cloneValue(cell));
//// System.out.println(value);
//// }
//// for (Cell cell : cells) {
//// String column = Bytes.toString(cell.getFamilyArray());
//// String value = Bytes.toString(cell.getQualifierArray());
//// System.out.println(value);
//// }
// String name = Bytes.toString(result.getValue("info".getBytes(), "name".getBytes()));
// String age = Bytes.toString(result.getValue("info".getBytes(), "age".getBytes()));
// String gender = Bytes.toString(result.getValue("info".getBytes(), "gender".getBytes()));
// String clazz = Bytes.toString(result.getValue("info".getBytes(), "clazz".getBytes()));
// System.out.println(name+","+age+","+gender+","+clazz);
// }
}
/*
过滤条件是这样的：^文科.*班
//null,null,null,文科五班
//null,null,null,文科六班
//null,null,null,文科六班
//null,null,null,文科一班
//null,null,null,文科一班
//null,null,null,文科四班
//null,null,null,文科六班
//null,null,null,文科三班
//null,null,null,文科五班
最后输出的结果格式是这样的
如果修改了一下最后一条数据
过滤条件是这样的 .*班
null,null,null,理科五班
null,null,null,文科三班
null,null,null,理科六班
null,null,null,理科四班
null,null,null,文科五班
班班班,null,null,理科六班
最后的输出结构就这样了
*/
//SingleColumnValueFilter 这个最后会输出这一列
//SingleColumnValueExcludeFilter 这个最后会排除这一列
//单列值过滤器
@Test
public void RegexStringComparatorSingleColumnValueFilter() throws IOException {
Scan scan = new Scan();
// SingleColumnValueFilter singleColumnValueFilter = new SingleColumnValueFilter(
// "info".getBytes(),
// "clazz".getBytes(),
// CompareFilter.CompareOp.EQUAL,
// "文科一班".getBytes() //这里既可以传入字符数组，也可以传入一个比较器
// );
SingleColumnValueFilter singleColumnValueFilter = new SingleColumnValueFilter(
"info".getBytes(),
"clazz".getBytes(),
CompareFilter.CompareOp.EQUAL,
new RegexStringComparator("^文科.*班$")
);
scan.setFilter(singleColumnValueFilter);
printScannerWithFilter();
// ResultScanner scanner = students.getScanner(scan);
// for (Result result : scanner) { //一个resule就代表一行数据
// List<Cell> cells = result.listCells();
//
// String id = Bytes.toString(result.getRow());
// System.out.print(id+"\t");
// for (Cell cell : cells) {
//// String id = Bytes.toString(CellUtil.cloneRow(cell));
// String value = Bytes.toString(CellUtil.cloneValue(cell));
// System.out.print(value+"\t");
// }
// System.out.println();
//
//// String name = Bytes.toString(result.getValue("info".getBytes(), "name".getBytes()));
//// String age = Bytes.toString(result.getValue("info".getBytes(), "age".getBytes()));
//// String gender = Bytes.toString(result.getValue("info".getBytes(), "gender".getBytes()));
//// String clazz = Bytes.toString(result.getValue("info".getBytes(), "clazz".getBytes()));
//// System.out.println(name+","+age+","+gender+","+clazz);
// }
//
}
//过滤出列里面包含字母a的所有列的数据
@org.junit.Test
public void SubstringComparatorSingleColumnValueFilter() throws IOException {
Table students = conn.getTable(TableName.valueOf("students"));
SubstringComparator a = new SubstringComparator("a");
QualifierFilter qualifierFilter = new QualifierFilter(
CompareFilter.CompareOp.EQUAL,
a
);
Scan scan = new Scan();
scan.setFilter(qualifierFilter);
ResultScanner scanner = students.getScanner(scan);
for (Result result : scanner) {
List<Cell> cells = result.listCells();
for (Cell cell : cells) {
String s = Bytes.toString(cell.getValue());
System.out.print(s+"\t");
}
System.out.println();
}
students.getScanner(scan);
}
@org.junit.Test
//过滤出rowkey比1500100010小的所有值来
public void BinaryPrefixComparatorRowFilter() throws IOException {
Table students = conn.getTable(TableName.valueOf("students"));
Scan scan = new Scan();
BinaryComparator binaryComparator = new BinaryComparator("1500100010".getBytes());
RowFilter rowFilter = new RowFilter(
CompareFilter.CompareOp.LESS,
binaryComparator
);
scan.setFilter(rowFilter);
ResultScanner scanner = students.getScanner(scan);
for (Result result : scanner) {
String id = Bytes.toString(result.getRow());
List<Cell> cells = result.listCells();
System.out.print(id+"\t");
for (Cell cell : cells) {
String value = Bytes.toString(CellUtil.cloneValue(cell));
System.out.print(value+"\t");
}
System.out.println();
}
}
@org.junit.Test
//查询列簇名包含in的所有列簇下面的数据
public void SubstringFamilyFilter() throws IOException {
Table students = conn.getTable(TableName.valueOf("students"));
SubstringComparator substringComparator = new SubstringComparator("in");
FamilyFilter familyFilter = new FamilyFilter(
CompareFilter.CompareOp.EQUAL,
substringComparator
);
Scan scan = new Scan();
scan.setFilter(familyFilter);
ResultScanner scanner = students.getScanner(scan);
for (Result result : scanner) {
String id = Bytes.toString(result.getRow());
System.out.print(id);
List<Cell> cells = result.listCells();
for (Cell cell : cells) {
String value = Bytes.toString(CellUtil.cloneValue(cell));
System.out.print(value+"\t");
}
System.out.println();
}
}
@org.junit.Test
//查询列簇以info开头的列簇下面的数据
public void BinaryPrefixComparatorFamilyFilter() throws IOException {
Table students = conn.getTable(TableName.valueOf("students"));
BinaryPrefixComparator binaryPrefixComparator = new BinaryPrefixComparator("info".getBytes());
FamilyFilter familyFilter = new FamilyFilter(
CompareFilter.CompareOp.EQUAL,
binaryPrefixComparator
);
Scan scan = new Scan();
ResultScanner scanner = students.getScanner(scan);
String id;
for (Result result : scanner) {
id = Bytes.toString(result.getRow());
List<Cell> cells = result.listCells();
System.out.print(id+"\t");
for (Cell cell : cells) {
String value = Bytes.toString(CellUtil.cloneValue(cell));
System.out.print(value+"\t");
}
System.out.println();
}
}
@After
public void close() throws IOException{
conn.close();
}
}
感谢阅读，我是啊帅和和，一位大数据专业大四学生，祝你快乐。
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