如何从Map器中访问cassandra柱族？具体来说，如何将map（）方法的参数转换回我期望的java类型？
键{logtype}->{列名：timeuuid，列值：csv log line，ttl:1year}

感谢@chris&@rs\u atl

我成功运行了hadoop作业，下面是完整的代码：

package com.xxx.hadoop;

import java.io.IOException;
import java.nio.ByteBuffer;
import java.util.Iterator;
import java.util.SortedMap;

import org.apache.cassandra.db.IColumn;
import org.apache.cassandra.hadoop.ColumnFamilyInputFormat;
import org.apache.cassandra.hadoop.ConfigHelper;
import org.apache.cassandra.thrift.SlicePredicate;
import org.apache.cassandra.thrift.SliceRange;
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.conf.Configured;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.LongWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Job;
import org.apache.hadoop.mapreduce.Mapper;
import org.apache.hadoop.mapreduce.Reducer;
import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;
import org.apache.hadoop.util.Tool;
import org.apache.hadoop.util.ToolRunner;
import org.apache.thrift.TBaseHelper;

import com.xxx.parser.LogParser;
import com.netflix.astyanax.serializers.StringSerializer;

public class LogTypeCounterByDate extends Configured implements Tool {
    private static final String KEYSPACE = "LogKS";
    private static final String COLUMN_FAMILY = "LogBlock";
    private static final String JOB_NAME = "LOG_LINE_COUNT";
    private static final String INPUT_PARTITIONER = "org.apache.cassandra.dht.RandomPartitioner";
    private static final String INPUT_RPC_PORT = "9160";
    private static final String INPUT_INITIAL_ADDRESS = "192.168.1.21";
    private static final String OUTPUT_PATH = "/logOutput/results";

    @Override
    public int run(String[] args) throws Exception {

        //Configuration conf = new Configuration();

        Job job = new Job(getConf(), JOB_NAME);
        job.setJarByClass(LogTypeCounterByDate.class);
        job.setMapperClass(LogTypeCounterByDateMapper.class);       
        job.setReducerClass(LogTypeCounterByDateReducer.class);

        job.setInputFormatClass(ColumnFamilyInputFormat.class);

        job.setMapOutputKeyClass(Text.class);
        job.setMapOutputValueClass(LongWritable.class);
        job.setNumReduceTasks(1);
        ConfigHelper.setRangeBatchSize(getConf(), 1000);

        /*SlicePredicate predicate = new SlicePredicate().setSlice_range(new SliceRange(ByteBuffer.wrap(new byte[0]), 
                ByteBuffer.wrap(new byte[0]), true, 1));*/
        SliceRange sliceRange = new SliceRange(ByteBuffer.wrap(new byte[0]), 
                ByteBuffer.wrap(new byte[0]), true, 1000);

        SlicePredicate slicePredicate = new SlicePredicate();
        slicePredicate.setSlice_range(sliceRange);

        ConfigHelper.setInputColumnFamily(job.getConfiguration(), KEYSPACE, COLUMN_FAMILY);
        ConfigHelper.setInputRpcPort(job.getConfiguration(), INPUT_RPC_PORT);
        ConfigHelper.setInputInitialAddress(job.getConfiguration(), INPUT_INITIAL_ADDRESS);
        ConfigHelper.setInputPartitioner(job.getConfiguration(), INPUT_PARTITIONER);
        ConfigHelper.setInputSlicePredicate(job.getConfiguration(), slicePredicate);

        FileOutputFormat.setOutputPath(job, new Path(OUTPUT_PATH));

        job.waitForCompletion(true);
        return job.isSuccessful() ? 0 : 1;
    }

    public static void main(String[] args) throws Exception{
        ToolRunner.run(new Configuration(), new LogTypeCounterByDate(), args);
        System.exit(0);
    }

    public static class LogTypeCounterByDateMapper extends Mapper<ByteBuffer, SortedMap<ByteBuffer, IColumn>, Text, LongWritable>
    {

        @SuppressWarnings("rawtypes")
        @Override
        protected void setup(Mapper.Context context){

        }

        @SuppressWarnings({ })
        public void map(ByteBuffer key, SortedMap<ByteBuffer, IColumn> columns, Context context) throws IOException, InterruptedException{
            //String[] lines = columns.;
            String rowkey = StringSerializer.get().fromByteBuffer(TBaseHelper.rightSize(key));  
            Iterator<ByteBuffer> iter = columns.keySet().iterator();
            IColumn column;
            String line;
            LogParser lp = null;

            while(iter.hasNext()){
                column = columns.get(iter.next());
                line = StringSerializer.get().fromByteBuffer(TBaseHelper.rightSize(column.value()));
                lp = new LogParser(line);               
                context.write(new Text(rowkey + "\t" + "LineCount"), new LongWritable(1L));
                context.write(new Text(rowkey + "\t" + "Minutes"), new LongWritable(lp.getTotalDuration()));
            }
        }
    }

    public static class LogTypeCounterByDateReducer extends Reducer<Text, LongWritable, Text, LongWritable>
    {           

        public void reduce(Text key, Iterable<LongWritable> values, Context context) throws IOException, InterruptedException{
            long total = 0;
            for(LongWritable val : values){
                total += val.get();
            }
            context.write(key, new LongWritable(total));
        }
    }               
}

ConfigHelper.setRangeBatchSize(getConf(), 1000);

        /*SlicePredicate predicate = new   SlicePredicate().setSlice_range(new SliceRange(ByteBuffer.wrap(new byte[0]), 
                ByteBuffer.wrap(new byte[0]), true, 1));*/
        SliceRange sliceRange = new SliceRange(ByteBuffer.wrap(new byte[0]), 
                ByteBuffer.wrap(new byte[0]), true, 1000);

        SlicePredicate slicePredicate = new SlicePredicate();
        slicePredicate.setSlice_range(sliceRange);

上面的代码只为每一行向mapper提供1000列，因为我希望为每一行提供所有列，每次1000列。
请有人帮我一下。