稍微扩展ben tse的回答，以允许可变的选择量：

import java.util.Random;

import org.apache.accumulo.core.data.Key;
import org.apache.accumulo.core.data.Value;
import org.apache.accumulo.core.iterators.Filter;

public class RandomAcceptFilter extends Filter {
    private Random rand = new Random();
    private double percentToAllow;
    public static final String RATIO = "ratio";
    public static final String DEFAULT = "0.05";        

    @Override
    public void init(SortedKeyValueIterator<Key, Value> source, Map<String, String> options, IteratorEnvironment env) throws IOException {
        super.init(source, options, env);
        String option = options.containsKey(RATIO) ? options.get(RATIO) : DEFAULT;
        this.percentToAllow = Double.parseDouble(option);
    }

    @Override
    public boolean accept(Key k, Value v) {
        return rand.nextDouble() < this.percentToAllow;
    }
}

当您从代码中调用迭代器时

IteratorSetting itr = new IteratorSetting(15, "myIterator", RandomAcceptFilter.class);
itr.addOption(RandomAcceptFilter.RATIO, "0.20");
myScanner.addScanIterator(itr);

显然，你需要增加边界检查等，但你得到的想法。

您可以扩展org.apache.accumulo.core.iterators.filter并随机接受x%的条目。下面的迭代器将随机返回5%的条目。

import java.util.Random;

import org.apache.accumulo.core.data.Key;
import org.apache.accumulo.core.data.Value;
import org.apache.accumulo.core.iterators.Filter;

public class RandomAcceptFilter extends Filter {
    private Random rand = new Random();

    @Override
    public boolean accept(Key k, Value v) {
        return rand.nextDouble() < .05;
    }
}