您好,登录后才能下订单哦!
下面说说JAVA API 提供的这些类的功能和他们之间有什么样的联系。
1.HBaseConfiguration
关系:org.apache.hadoop.hbase.HBaseConfiguration
作用:通过此类可以对HBase进行配置
用法实例: Configuration config = HBaseConfiguration.create();
说明: HBaseConfiguration.create() 默认会从classpath 中查找 hbase-site.xml 中的配置信息,初始化 Configuration。
2.HBaseAdmin 类
关系:org.apache.hadoop.hbase.client.HBaseAdmin
作用:提供接口关系HBase 数据库中的表信息
用法:HBaseAdmin admin = new HBaseAdmin(config);
3.Descriptor类
关系:org.apache.hadoop.hbase.HTableDescriptor
作用:HTableDescriptor 类包含了表的名字以及表的列族信息
用法:HTableDescriptor htd =new HTableDescriptor(tablename);
构造一个表描述符指定TableName对象。
Htd.addFamily(new HColumnDescriptor(“myFamily”));
将列家族给定的描述符
4.HTable
关系:org.apache.hadoop.hbase.client.HTable
作用:HTable 和 HBase 的表通信
用法:HTable tab = new HTable(config,Bytes.toBytes(tablename));
ResultScanner sc = tab.getScanner(Bytes.toBytes(“familyName”));
说明:获取表内列族 familyNme 的所有数据。
5.Put
关系:org.apache.hadoop.hbase.client.Put
作用:获取单个行的数据
用法:HTable table = new HTable(config,Bytes.toBytes(tablename));
Put put = new Put(row);
p.add(family,qualifier,value);
说明:向表 tablename 添加 “family,qualifier,value”指定的值。
6.Get
关系:org.apache.hadoop.hbase.client.Get
作用:获取单个行的数据
用法:HTable table = new HTable(config,Bytes.toBytes(tablename));
Get get = new Get(Bytes.toBytes(row));
Result result = table.get(get);
说明:获取 tablename 表中 row 行的对应数据
7.ResultScanner
关系:Interface
作用:获取值的接口
用法:ResultScanner scanner = table.getScanner(Bytes.toBytes(family));
For(Result rowResult : scanner){
Bytes[] str = rowResult.getValue(family,column);
}
说明:循环获取行中列值。
例1 HBase之读取HDFS数据写入HBase
package org.hadoop.hbase; import java.io.IOException; import java.util.StringTokenizer; import org.apache.hadoop.conf.Configuration; import org.apache.hadoop.fs.Path; import org.apache.hadoop.hbase.HBaseConfiguration; import org.apache.hadoop.hbase.HColumnDescriptor; import org.apache.hadoop.hbase.HTableDescriptor; import org.apache.hadoop.hbase.client.HBaseAdmin; import org.apache.hadoop.hbase.client.Put; import org.apache.hadoop.hbase.io.ImmutableBytesWritable; import org.apache.hadoop.hbase.mapreduce.TableMapReduceUtil; import org.apache.hadoop.hbase.mapreduce.TableReducer; import org.apache.hadoop.hbase.util.Bytes; import org.apache.hadoop.io.IntWritable; import org.apache.hadoop.io.Text; import org.apache.hadoop.mapreduce.Job; import org.apache.hadoop.mapreduce.Mapper; import org.apache.hadoop.mapreduce.lib.input.FileInputFormat; import org.apache.hadoop.util.GenericOptionsParser; public class WordCountHbaseWriter { public static class WordCountHbaseMapper extends Mapper<Object, Text, Text, IntWritable> { private final static IntWritable one = new IntWritable(1); private Text word = new Text(); public void map(Object key, Text value, Context context) throws IOException, InterruptedException { StringTokenizer itr = new StringTokenizer(value.toString()); while (itr.hasMoreTokens()) { word.set(itr.nextToken()); context.write(word, one);// 输出<key,value>为<word,one> } } } public static class WordCountHbaseReducer extends TableReducer<Text, IntWritable, ImmutableBytesWritable> { public void reduce(Text key, Iterable<IntWritable> values, Context context) throws IOException, InterruptedException { int sum = 0; for (IntWritable val : values) {// 遍历求和 sum += val.get(); } Put put = new Put(key.getBytes());//put实例化,每一个词存一行 //列族为content,列修饰符为count,列值为数目 put.add(Bytes.toBytes("content"), Bytes.toBytes("count"), Bytes.toBytes(String.valueOf(sum))); context.write(new ImmutableBytesWritable(key.getBytes()), put);// 输出求和后的<key,value> } } public static void main(String[] args){ String tablename = "wordcount"; Configuration conf = HBaseConfiguration.create(); conf.set("hbase.zookeeper.quorum", "192.168.1.139"); conf.set("hbase.zookeeper.property.clientPort", "2191"); HBaseAdmin admin = null; try { admin = new HBaseAdmin(conf); if(admin.tableExists(tablename)){ System.out.println("table exists!recreating......."); admin.disableTable(tablename); admin.deleteTable(tablename); } HTableDescriptor htd = new HTableDescriptor(tablename); HColumnDescriptor tcd = new HColumnDescriptor("content"); htd.addFamily(tcd);//创建列族 admin.createTable(htd);//创建表 String[] otherArgs = new GenericOptionsParser(conf, args).getRemainingArgs(); if (otherArgs.length != 1) { System.err.println("Usage: WordCountHbaseWriter <in>"); System.exit(2); } Job job = new Job(conf, "WordCountHbaseWriter"); job.setNumReduceTasks(2); job.setJarByClass(WordCountHbaseWriter.class); //使用WordCountHbaseMapper类完成Map过程; job.setMapperClass(WordCountHbaseMapper.class); TableMapReduceUtil.initTableReducerJob(tablename, WordCountHbaseReducer.class, job); //设置任务数据的输入路径; FileInputFormat.addInputPath(job, new Path(otherArgs[0])); //设置了Map过程的输出类型,其中设置key的输出类型为Text; job.setOutputKeyClass(Text.class); //设置了Map过程的输出类型,其中设置value的输出类型为IntWritable; job.setOutputValueClass(IntWritable.class); //调用job.waitForCompletion(true) 执行任务,执行成功后退出; System.exit(job.waitForCompletion(true) ? 0 : 1); } catch (Exception e) { e.printStackTrace(); } finally{ if(admin!=null) try { admin.close(); } catch (IOException e) { e.printStackTrace(); } } } }
例2 HBase之读取HBase数据写入HDFS
package org.hadoop.hbase; import java.io.IOException; import java.util.Map.Entry; import org.apache.hadoop.conf.Configuration; import org.apache.hadoop.fs.Path; import org.apache.hadoop.hbase.HBaseConfiguration; import org.apache.hadoop.hbase.client.Result; import org.apache.hadoop.hbase.client.Scan; import org.apache.hadoop.hbase.io.ImmutableBytesWritable; import org.apache.hadoop.hbase.mapreduce.TableMapReduceUtil; import org.apache.hadoop.hbase.mapreduce.TableMapper; import org.apache.hadoop.io.Text; import org.apache.hadoop.mapreduce.Job; import org.apache.hadoop.mapreduce.Reducer; import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat; import org.apache.hadoop.util.GenericOptionsParser; public class WordCountHbaseReader { public static class WordCountHbaseReaderMapper extends TableMapper<Text,Text>{ @Override protected void map(ImmutableBytesWritable key,Result value,Context context) throws IOException, InterruptedException { StringBuffer sb = new StringBuffer(""); for(Entry<byte[],byte[]> entry:value.getFamilyMap("content".getBytes()).entrySet()){ String str = new String(entry.getValue()); //将字节数组转换为String类型 if(str != null){ sb.append(new String(entry.getKey())); sb.append(":"); sb.append(str); } context.write(new Text(key.get()), new Text(new String(sb))); } } } public static class WordCountHbaseReaderReduce extends Reducer<Text,Text,Text,Text>{ private Text result = new Text(); @Override protected void reduce(Text key, Iterable<Text> values,Context context) throws IOException, InterruptedException { for(Text val:values){ result.set(val); context.write(key, result); } } } public static void main(String[] args) throws Exception { String tablename = "wordcount"; Configuration conf = HBaseConfiguration.create(); conf.set("hbase.zookeeper.quorum", "192.168.1.139"); conf.set("hbase.zookeeper.property.clientPort", "2191"); String[] otherArgs = new GenericOptionsParser(conf, args).getRemainingArgs(); if (otherArgs.length != 1) { System.err.println("Usage: WordCountHbaseReader <out>"); System.exit(2); } Job job = new Job(conf, "WordCountHbaseReader"); job.setJarByClass(WordCountHbaseReader.class); //设置任务数据的输出路径; FileOutputFormat.setOutputPath(job, new Path(otherArgs[0])); job.setReducerClass(WordCountHbaseReaderReduce.class); Scan scan = new Scan(); TableMapReduceUtil.initTableMapperJob(tablename,scan,WordCountHbaseReaderMapper.class, Text.class, Text.class, job); //调用job.waitForCompletion(true) 执行任务,执行成功后退出; System.exit(job.waitForCompletion(true) ? 0 : 1); } }
程序中用到hadoop的相关JAR包(如下图)及hbase所有jar包
如果上面的API还不能满足你的要求,可以到下面这个网站里面Hbase全部API介绍
http://www.yiibai.com/hbase/
免责声明:本站发布的内容(图片、视频和文字)以原创、转载和分享为主,文章观点不代表本网站立场,如果涉及侵权请联系站长邮箱:is@yisu.com进行举报,并提供相关证据,一经查实,将立刻删除涉嫌侵权内容。