Apache Hadoop中的Combiner函数可以在MapReduce作业的Map阶段之后，Reduce阶段之前对Map输出进行本地合并，以减少数据传输量。Gora是一个开源的数据存储、查询和处理框架，用于在Apache Hadoop生态系统中处理大规模数据。

下面是一个使用Combiner函数和Gora的代码示例：

import java.io.IOException;
import java.util.Iterator;

import org.apache.hadoop.io.IntWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Mapper;
import org.apache.hadoop.mapreduce.Reducer;

import org.apache.gora.mapreduce.GoraMapper;
import org.apache.gora.mapreduce.GoraReducer;
import org.apache.gora.store.DataStoreFactory;
import org.apache.gora.store.DataStore;
import org.apache.gora.util.GoraException;

public class WordCount {

    public static class WordCountMapper extends GoraMapper {

        private final static IntWritable one = new IntWritable(1);
        private Text word = new Text();

        @Override
        public void map(Long key, Text value, Context context) throws IOException, InterruptedException {
            String line = value.toString();
            String[] words = line.split(" ");

            for (String w : words) {
                word.set(w);
                context.write(word, one);
            }
        }
    }

    public static class WordCountReducer extends GoraReducer {

        private IntWritable result = new IntWritable();

        @Override
        protected void reduce(Text key, Iterable values, Context context) throws IOException, InterruptedException {
            int sum = 0;

            for (IntWritable val : values) {
                sum += val.get();
            }

            result.set(sum);
            context.write(key, result);
        }
    }

    public static void main(String[] args) throws IOException, ClassNotFoundException, InterruptedException, GoraException {
        DataStore dataStore = DataStoreFactory.getDataStore(Long.class, MyCustomObject.class, new Configuration());

        Job job = Job.getInstance(new Configuration());
        job.setJarByClass(WordCount.class);
        job.setMapperClass(WordCountMapper.class);
        job.setCombinerClass(WordCountReducer.class);
        job.setReducerClass(WordCountReducer.class);
        job.setOutputKeyClass(Text.class);
        job.setOutputValueClass(IntWritable.class);

        GoraMapper.initMapperJob(job, dataStore, Long.class, MyCustomObject.class, WordCountMapper.class, true);
        GoraReducer.initReducerJob(job, dataStore, WordCountReducer.class);

        job.waitForCompletion(true);
    }
}

上述示例中，使用了Apache Gora中的GoraMapper和GoraReducer类来处理数据存储和查询。在main方法中，我们首先初始化了一个Gora DataStore实例来连接到数据存储中。

然后，我们创建一个MapReduce作业，并设置了Mapper和Reducer的类。我们还设置了Combiner函数，即WordCountReducer类，以进行本地合并。最后，我们通过调用GoraMapper和GoraReducer类的initMapperJob和initReducerJob方法来初始化Mapper和Reducer作业。

请注意，上述代码示例中的MyCustomObject类是一个自定义的数据对象，你可以根据自己的需求进行修改。另外，你还需要根据实际情况进行相关的配置和依赖项设置。

希望这个示例能够帮助你理解如何在Apache Hadoop中使用Combiner函数和Gora。