org.apache.hadoop.hbase.MasterNotRunningException解决策略

运行HBase时常会遇到个错误，我就有这样的经历。 

ERROR: org.apache.hadoop.hbase.MasterNotRunningException: Retried 7 times

检查日志：org.apache.hadoop.ipc.RPC$VersionMismatch: Protocol org.apache.hadoop.hdfs.protocol.ClientProtocol version mismatch. (client = 42, server = 41)

如果是这个错误，说明RPC协议不一致所造成的，解决方法：将hbase/lib目录下的hadoop-core的jar文件删除，将hadoop目录下的hadoop-0.20.2-core.jar拷贝到hbase/lib下面，然后重新启动hbase即可。第二种错误是：没有启动hadoop，先启用hadoop，再启用hbase。

在Eclipse开发中，需要加入hadoop所有的jar包以及HBase二个jar包（hbase，zooKooper）。

1. 建表，通过HBaseAdmin类中的create静态方法来创建表。
2. HTable类是操作表，例如，静态方法put可以插入数据，该类初始化时可以传递一个行键，静态方法getScanner()可以获得某一列上的所有数据，返回Result类,Result类中有个静态方法getFamilyMap（）可以获得以列名为key，值为value，这刚好与hadoop中map结果是一样的。
3. 

   package test;import java.io.IOException;import java.util.Map;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.client.HBaseAdmin;import org.apache.hadoop.hbase.client.HTable;import org.apache.hadoop.hbase.client.Put;import org.apache.hadoop.hbase.client.Result;public class Htable {    /**     * @param args     */    public static void main(String[] args) throws IOException {        // TODO Auto-generated method stub        Configuration hbaseConf = HBaseConfiguration.create();        HBaseAdmin admin = new HBaseAdmin(hbaseConf);        HTableDescriptor htableDescriptor = new HTableDescriptor("table"                .getBytes());  //set the name of table        htableDescriptor.addFamily(new HColumnDescriptor("fam1")); //set the name of column clusters        admin.createTable(htableDescriptor); //create a table         HTable table = new HTable(hbaseConf, "table"); //get instance of table.        for (int i = 0; i < 3; i++) {   //for is number of rows            Put putRow = new Put(("row" + i).getBytes()); //the ith row            putRow.add("fam1".getBytes(), "col1".getBytes(), "vaule1"                    .getBytes());  //set the name of column and value.            putRow.add("fam1".getBytes(), "col2".getBytes(), "vaule2"                    .getBytes());            putRow.add("fam1".getBytes(), "col3".getBytes(), "vaule3"                    .getBytes());            table.put(putRow);        }        for(Result result: table.getScanner("fam1".getBytes())){//get data of column clusters             for(Map.Entry<byte[], byte[]> entry : result.getFamilyMap("fam1".getBytes()).entrySet()){//get collection of result                String column = new String(entry.getKey());                String value = new String(entry.getValue());                System.out.println(column+","+value);            }        }        admin.disableTable("table".getBytes()); //disable the table        admin.deleteTable("table".getBytes());  //drop the tbale    }}

    

   
   以上代码不难看懂。

下面介绍一下，用mapreduce怎样操作HBase，主要对HBase中的数据进行读取。

现在有一些大的文件，需要存入HBase中，其思想是先把文件传到HDFS上，利用map阶段读取<key,value>对，可在reduce把这些键值对上传到HBase中。

 

package test;import java.io.IOException;import org.apache.hadoop.io.LongWritable;import org.apache.hadoop.io.Text;import org.apache.hadoop.mapreduce.Mapper;public class MapperClass extends Mapper<LongWritable,Text,Text,Text>{        public void map(LongWritable key,Text value,Context context)thorws IOException{            String[] items = value.toString().split(" ");            String k = items[0];            String v = items[1];                     context.write(new Text(k), new Text(v));    }}

Reduce类,主要是将键值传到HBase表中

 

package test;import java.io.IOException;import org.apache.hadoop.hbase.client.Put;import org.apache.hadoop.hbase.io.ImmutableBytesWritable;import org.apache.hadoop.hbase.mapreduce.TableReducer;import org.apache.hadoop.io.Text;public class ReducerClass extends TableReducer<Text,Text,ImmutableBytesWritable>{    public void reduce(Text key,Iterable<Text> values,Context context){        String k = key.toString();        StringBuffer str=null;        for(Text value: values){            str.append(value.toString());        }        String v = new String(str);         Put putrow = new Put(k.getBytes());        putrow.add("fam1".getBytes(), "name".getBytes(), v.getBytes());         }}

 

由上面可知ReducerClass继承TableReduce，在hadoop里面ReducerClass继承Reducer类。它的原型为：TableReducer<KeyIn,Values,KeyOut>可以看出，HBase里面是读出的Key类型是ImmutableBytesWritable。

Map，Reduce，以及Job的配置分离，比较清晰,mahout也是采用这种构架。

 

package test;import org.apache.hadoop.conf.Configuration;import org.apache.hadoop.conf.Configured;import org.apache.hadoop.fs.Path;import org.apache.hadoop.hbase.HBaseConfiguration;import org.apache.hadoop.hbase.mapreduce.TableMapReduceUtil;import org.apache.hadoop.io.Text;import org.apache.hadoop.mapreduce.Job;import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;import org.apache.hadoop.mapreduce.lib.input.TextInputFormat;import org.apache.hadoop.util.Tool;public class Driver extends Configured implements Tool{    @Override    public static void run(String[] arg0) throws Exception {        // TODO Auto-generated method stub        Configuration conf = HBaseConfiguration.create();        conf.set("hbase.zookeeper.quorum.", "localhost");                  Job job = new Job(conf,"Hbase");        job.setJarByClass(TxtHbase.class);                Path in = new Path(arg0[0]);                job.setInputFormatClass(TextInputFormat.class);        FileInputFormat.addInputPath(job, in);                job.setMapperClass(MapperClass.class);        job.setMapOutputKeyClass(Text.class);        job.setMapOutputValueClass(Text.class);                TableMapReduceUtil.initTableReducerJob("table", ReducerClass.class, job);               job.waitForCompletion(true);    }    }

 

Driver中job配置的时候没有设置 job.setReduceClass(); 而是用 TableMapReduceUtil.initTableReducerJob("tab1", THReducer.class, job); 来执行reduce类。

主函数

 

package test;import org.apache.hadoop.conf.Configuration;import org.apache.hadoop.util.ToolRunner;public class TxtHbase {    public static void main(String [] args) throws Exception{        Driver.run(new Configuration(),new THDriver(),args);     } }

 

 

读取数据时比较简单，编写Mapper函数，读取<key,value>值就行了。

 

package test;import java.io.IOException;import org.apache.hadoop.conf.Configuration;import org.apache.hadoop.hbase.client.Result;import org.apache.hadoop.hbase.io.ImmutableBytesWritable;import org.apache.hadoop.hbase.mapred.TableMap;import org.apache.hadoop.io.Text;import org.apache.hadoop.mapred.MapReduceBase;import org.apache.hadoop.mapred.OutputCollector;import org.apache.hadoop.mapred.Reporter;public class MapperClass extends MapReduceBase implements        TableMap<Text, Text> {    static final String NAME = "GetDataFromHbaseTest";    private Configuration conf;    public void map(ImmutableBytesWritable row, Result values,            OutputCollector<Text, Text> output, Reporter reporter)            throws IOException {        StringBuilder sb = new StringBuilder();        for (Entry<byte[], byte[]> value : values.getFamilyMap(                "fam1".getBytes()).entrySet()) {            String cell = value.getValue().toString();            if (cell != null) {                sb.append(new String(value.getKey())).append(new String(cell));            }        }        output.collect(new Text(row.get()), new Text(sb.toString()));    }

 

要实现这个方法 initTableMapJob(String table, String columns, Class<? extends TableMap> mapper, Class<? extends org.apache.hadoop.io.WritableComparable> outputKeyClass, Class<? extends org.apache.hadoop.io.Writable> outputValueClass, org.apache.hadoop.mapred.JobConf job, boolean addDependencyJars)。

 

package test;import org.apache.hadoop.conf.Configuration;import org.apache.hadoop.conf.Configured;import org.apache.hadoop.fs.Path;import org.apache.hadoop.hbase.HBaseConfiguration;import org.apache.hadoop.hbase.mapreduce.TableMapReduceUtil;import org.apache.hadoop.io.Text;import org.apache.hadoop.mapreduce.Job;import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;import org.apache.hadoop.mapreduce.lib.input.TextInputFormat;import org.apache.hadoop.util.Tool;public class Driver extends Configured implements Tool{    @Override    public static void run(String[] arg0) throws Exception {        // TODO Auto-generated method stub        Configuration conf = HBaseConfiguration.create();        conf.set("hbase.zookeeper.quorum.", "localhost");          Job job = new Job(conf,"Hbase");        job.setJarByClass(TxtHbase.class);        job.setInputFormatClass(TextInputFormat.class);        job.setMapOutputKeyClass(Text.class);        job.setMapOutputValueClass(Text.class);        TableMapReduceUtilinitTableMapperJob("table", args0[0],MapperClass.class, job);         job.waitForCompletion(true); } }

 

主函数

 

package test;import org.apache.hadoop.conf.Configuration;import org.apache.hadoop.util.ToolRunner;public class TxtHbase {    public static void main(String [] args) throws Exception{        Driver.run(new Configuration(),new THDriver(),args);     } }