Hbase入门之六JAVA链接hbase

1、需要的jar包：

commons-codec-1.4.jar

commons-logging-1.0.4.jar

hadoop-0.20.2-core.jar

hbase-0.20.6.jar

log4j-1.2.15.jar

zookeeper-3.2.2.jar

 

2、已有表结构：

1、表名：scores

2、列族：

course:art

course:math

grade:

 

3、scan 'scores'的内容：

ROW COLUMN+CELL
Jerry column=course:art, timestamp=1301294630194, value=80
Jerry column=course:math, timestamp=1301294630132, value=100
Jerry column=grade:, timestamp=1301294630073, value=2
Jim column=course:art, timestamp=1301294630363, value=97
Jim column=course:math, timestamp=1301294630305, value=100
Jim column=grade:, timestamp=1301294630247, value=3
Tom column=course:art, timestamp=1301294630015, value=97
Tom column=course:math, timestamp=1301294629987, value=87
Tom column=grade:, timestamp=1301294629931, value=1

 

 

package org.myhbase;

import java.io.IOException;

import java.util.ArrayList;

import java.util.List;

import org.apache.hadoop.conf.Configuration;

import org.apache.hadoop.hbase.HBaseConfiguration;

import org.apache.hadoop.hbase.KeyValue;

import org.apache.hadoop.hbase.client.Get;

import org.apache.hadoop.hbase.client.HTable;

import org.apache.hadoop.hbase.client.Result;

import org.apache.hadoop.hbase.client.ResultScanner;

import org.apache.hadoop.hbase.client.Scan;

import org.apache.hadoop.hbase.filter.FilterList;

import org.apache.hadoop.hbase.filter.SingleColumnValueFilter;

import org.apache.hadoop.hbase.filter.CompareFilter.CompareOp;

import org.apache.hadoop.hbase.io.Cell;

import org.apache.hadoop.hbase.util.Bytes;

public class HBaseBasic03 {

private static HBaseConfiguration hbaseConfig=null;

static{

Configuration config=new Configuration();

config.set("hbase.zookeeper.quorum","192.168.10.149,192.168.10.44,192.168.10.49");

config.set("hbase.zookeeper.property.clientPort", "2181");

hbaseConfig=new HBaseConfiguration(config);

}

public static void selectByRowKey(String tablename,String rowKey) throws IOException{

HTable table=new HTable(hbaseConfig,tablename);

Get g = new Get(Bytes.toBytes(rowKey));

Result r=table.get(g);

for(KeyValue kv:r.raw()){

System.out.println("column: "+new String(kv.getColumn()));

System.out.println("value: "+new String(kv.getValue()));

}

}

public static void selectByRowKeyColumn(String tablename,String rowKey,String column) throws IOException{

HTable table=new HTable(hbaseConfig,tablename);

Get g = new Get(Bytes.toBytes(rowKey));

g.addColumn(Bytes.toBytes(column));

Result r=table.get(g);

for(KeyValue kv:r.raw()){

System.out.println("column: "+new String(kv.getColumn()));

System.out.println("value: "+new String(kv.getValue()));

}

}

public static void selectByFilter(String tablename,List arr) throws IOException{

HTable table=new HTable(hbaseConfig,tablename);

FilterList filterList = new FilterList();

Scan s1 = new Scan();

for(String v:arr){ // 各个条件之间是“与”的关系

String [] s=v.split(",");

filterList.addFilter(new SingleColumnValueFilter(Bytes.toBytes(s[0]),

Bytes.toBytes(s[1]),

CompareOp.EQUAL,Bytes.toBytes(s[2])

)

);

// 添加下面这一行后，则只返回指定的cell，同一行中的其他cell不返回

// s1.addColumn(Bytes.toBytes(s[0]), Bytes.toBytes(s[1]));

}

s1.setFilter(filterList);

ResultScanner ResultScannerFilterList = table.getScanner(s1);

for(Result rr=ResultScannerFilterList.next();rr!=null;rr=ResultScannerFilterList.next()){

for(KeyValue kv:rr.list()){

System.out.println("row : "+new String(kv.getRow()));

System.out.println("column : "+new String(kv.getColumn()));

System.out.println("value : "+new String(kv.getValue()));

}

}

}

public static void main(String [] args) throws IOException{

// 按rowkey查询，查询Tom行的所有cell

HBaseBasic03.selectByRowKey("scores","Tom");

// 按rokey 和 column 来查询，查询Tom行course列族的所有列值

HBaseBasic03.selectByRowKeyColumn("scores","Tom","course");

// Filter多条件查询，条件：查询 course列族中art列值为97 ，且 course列族中math列值为100的行

List arr=new ArrayList();

arr.add("course,art,97");

arr.add("course,math,100");

HBaseBasic03.selectByFilter("scores",arr);

}

}

1.连接HBase中的表testtable,用户名：root,密码：root

public void ConnectHBaseTable()
{
Configuration conf = new Configuration();
conf.set("hadoop.job.ugi", "root,root");
HBaseConfiguration config = new HBaseConfiguration();
try
{
table = new HTable(config, "testtable");
}catch(Exception e){e.printStackTrace();}
}

2.根据行名name获得一行数据，存入Result.注意HBase中的表数据是字节存储的。

下面的例子表示获得行名为name的行的famA列族col1列的数据。

String rowId = "name";
Get get = new Get(rowId);
Result result = hTable.get(get);
byte[] value = result.getValue(famA, col1);
System.out.println(Bytes.toString(value));

3.向表中存数据

下面的例子表示写入一行。行名为abcd，famA列族col1列的数据为"hello world!"。

byte[] rowId = Bytes.toBytes("abcd");
byte[] famA = Bytes.toBytes("famA");
byte[] col1 = Bytes.toBytes("col1");
Put put = new Put(rowId).
add(famA, col1, Bytes.toBytes("hello world!"));
hTable.put(put);

4.扫描的用法（scan）：便于获得自己需要的数据，相当于SQL查询。

byte[] famA = Bytes.toBytes("famA");
byte[] col1 = Bytes.toBytes("col1");

HTable hTable = new HTable("test");

//表示要查询的行名是从a开始，到z结束。
Scan scan = new Scan(Bytes.toBytes("a"), Bytes.toBytes("z"));

//用scan.setStartRow(Bytes.toBytes(""));设置起始行

//用scan.setStopRow(Bytes.toBytes(""));设置终止行

 

//表示查询famA族col1列

scan.addColumn(famA, col1);

//注意，下面是filter的写法。相当于SQL的where子句

//表示famA族col1列的数据等于"hello world!"
SingleColumnValueFilter singleColumnValueFilterA = new SingleColumnValueFilter(
famA, col1, CompareOp.EQUAL, Bytes.toBytes("hello world!"));
singleColumnValueFilterA.setFilterIfMissing(true);

//表示famA族col1列的数据等于"hello hbase!"
SingleColumnValueFilter singleColumnValueFilterB = new SingleColumnValueFilter(
famA, col1, CompareOp.EQUAL, Bytes.toBytes("hello hbase!"));
singleColumnValueFilterB.setFilterIfMissing(true);

//表示famA族col1列的数据是两者中的一个
FilterList filter = new FilterList(Operator.MUST_PASS_ONE, Arrays
.asList((Filter) singleColumnValueFilterA,
singleColumnValueFilterB));

scan.setFilter(filter);

ResultScanner scanner = hTable.getScanner(scan);
//遍历每个数据
for (Result result : scanner) {
System.out.println(Bytes.toString(result.getValue(famA, col1)));
}

5.上面的代码容易出错的地方在于，需要导入HBase的类所在的包。导入时需要选择包，由于类可能出现在HBase的各个子包中，所以要选择好，下面列出常用的包。尽量用HBase的包

import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.hbase.HBaseConfiguration;
import org.apache.hadoop.hbase.client.Get;
import org.apache.hadoop.hbase.client.HTable;
import org.apache.hadoop.hbase.client.Put;
import org.apache.hadoop.hbase.client.Result;
import org.apache.hadoop.hbase.client.ResultScanner;
import org.apache.hadoop.hbase.client.Scan;
import org.apache.hadoop.hbase.filter.Filter;
import org.apache.hadoop.hbase.filter.FilterList;
import org.apache.hadoop.hbase.filter.SingleColumnValueFilter;
import org.apache.hadoop.hbase.filter.CompareFilter.CompareOp;
import org.apache.hadoop.hbase.filter.FilterList.Operator;
import org.apache.hadoop.hbase.util.Bytes;

import java.io.IOException;
import java.text.SimpleDateFormat;
import java.util.Arrays;
import java.util.Date;

 

6.下面列出HBase常用的操作

（1）时间戳到时间的转换.单一的时间戳无法给出直观的解释。

public String GetTimeByStamp(String timestamp)
{

long datatime= Long.parseLong(timestamp);
Date date=new Date(datatime);
SimpleDateFormat format=new SimpleDateFormat("yyyy-MM-dd HH:MM:ss");
String timeresult=format.format(date);
System.out.println("Time : "+timeresult);
return timeresult;
}

（2）时间到时间戳的转换。注意时间是字符串格式。字符串与时间的相互转换，此不赘述。

public String GetStampByTime(String time)
{
String Stamp="";
SimpleDateFormat sdf=new SimpleDateFormat("yyyy-MM-dd HH:mm:ss");
Date date;
try
{
date=sdf.parse(time);
Stamp=date.getTime()+"000";
System.out.println(Stamp);
}catch(Exception e){e.printStackTrace();}
return Stamp;

}