Hadoop:我怎么能在键值对中有一个双精度数组作为值?

时间:2012-02-18 14:56:07

标签: java hadoop key-value

我有一个问题,我需要聚合一些向量,以便找到一些统计数据。例如,我有双打的向量,我需要总结它们。我的矢量看起来像这样:

      1,0,3,4,5
      2,3,4,5,6
      3,4,5,5,6

到目前为止我的键值对是(String,String)。但每次我需要添加这些向量时,我首先必须将它们转换为双数组,添加它们,最后将聚合向量转换为字符串。我认为如果我只能在表单中使用键值对(String,double array)会快得多。没有必要来回转换它们。我的问题是我找不到将双数组作为值的方法。有没有简单的方法而不是创建新的自定义类型?

1 个答案:

答案 0 :(得分:3)

你的意思是这样的吗?

Map<String, List<Double>> arrays = new HashMap<String, List<Double>>();

double[] array;
arrays.put("ArrayKey", Arrays.asList(array));

然后你可以调用你的地图方法:

map(String key, String arrayKey) {
    List<Double> value = arrays.get(arrayKey);
}

此外,您可以序列化双数组,然后将其反序列化:

package test;

import org.apache.commons.codec.binary.Base64InputStream;
import org.apache.commons.codec.binary.Base64OutputStream;

import java.io.*;
import java.util.Arrays;

public class Test {

    public static void main(String[] args) throws IOException, ClassNotFoundException {
        double[] array = {0.0, 1.1, 2.2, 3.3};
        String stringValue = serialize(array);
        map("Key", stringValue);
    }

    public static void map(String key, String value) throws ClassNotFoundException, IOException {
        double[] array = deserialize(value);
        System.out.println("Key=" + key + "; Value=" + Arrays.toString(array));
    }

    public static String serialize(double[] array) throws IOException {
        ByteArrayOutputStream byteArrayOutputStream = new ByteArrayOutputStream();
        Base64OutputStream base64OutputStream = new Base64OutputStream(byteArrayOutputStream);
        ObjectOutputStream oos = new ObjectOutputStream(base64OutputStream);
        oos.writeObject(array);
        oos.flush();
        oos.close();
        return byteArrayOutputStream.toString();
    }

    public static double[] deserialize(String stringArray) throws IOException, ClassNotFoundException {
        ByteArrayInputStream byteArrayInputStream = new ByteArrayInputStream(stringArray.getBytes());
        Base64InputStream base64InputStream = new Base64InputStream(byteArrayInputStream);
        ObjectInputStream iis = new ObjectInputStream(base64InputStream);
        return (double[]) iis.readObject();
    }
}

输出:

Key=Key; Value=[0.0, 1.1, 2.2, 3.3]

映射速度更快,但如果您使用节点和集群(如果需要将数组传递到另一个JVM),序列化将更有用:

 private static class SpeedTest {
        private static final Map<String, List> arrays = new HashMap<String, List>();

        public static void test(final double[] array) throws IOException, ClassNotFoundException {
            final String str = serialize(array);
            final int amount = 10 * 1000;

            long timeStamp = System.currentTimeMillis();
            for (int i = 0; i < amount; i++) {
                serialize(array);
            }
            System.out.println("Serialize: " + (System.currentTimeMillis() - timeStamp) + " ms");

            timeStamp = System.currentTimeMillis();
            for (int i = 0; i < amount; i++) {
                deserialize(str);
            }
            System.out.println("Deserialize: " + (System.currentTimeMillis() - timeStamp) + " ms");

            arrays.clear();
            timeStamp = System.currentTimeMillis();
            // Prepaire map, that contains reference for all arrays.
            for (int i = 0; i < amount; i++) {
                arrays.put("key_" + i, Arrays.asList(array));
            }
            // Getting array by its key in map.
            for (int i = 0; i < amount; i++) {
                arrays.get("key_" + i).toArray();
            }
            System.out.println("Mapping: " + (System.currentTimeMillis() - timeStamp) + " ms");
        }
    }

<强>输出:

Serialize: 298 ms
Deserialize: 254 ms
Mapping: 27 ms