你这个不对 我需要的是用scan全量扫描

非常抱歉，我理解有误。那么针对您的需求，以下是使用 Java 1.8 和 Spark 从 HBase 表中全量扫描三个字段数据，并将结果保存到 HDFS 上的代码实现：

// 导入相关的依赖包
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.FileSystem;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.hbase.Cell;
import org.apache.hadoop.hbase.HBaseConfiguration;
import org.apache.hadoop.hbase.TableName;
import org.apache.hadoop.hbase.client.Connection;
import org.apache.hadoop.hbase.client.ConnectionFactory;
import org.apache.hadoop.hbase.client.Result;
import org.apache.hadoop.hbase.client.Scan;
import org.apache.hadoop.hbase.client.Table;
import org.apache.hadoop.hbase.filter.FilterList;
import org.apache.hadoop.hbase.filter.PageFilter;
import org.apache.hadoop.hbase.util.Bytes;
import org.apache.spark.SparkConf;
import org.apache.spark.api.java.JavaRDD;
import org.apache.spark.api.java.JavaSparkContext;

import java.io.IOException;
import java.net.URI;
import java.util.ArrayList;
import java.util.List;

public class HBaseScanToHDFSSave {
    public static void main(String[] args) throws IOException {
        // HBase 配置
        Configuration hbaseConf = HBaseConfiguration.create();
        hbaseConf.set("hbase.zookeeper.quorum", "localhost");
        hbaseConf.set("hbase.zookeeper.property.clientPort", "2181");
        Connection hbaseConn = ConnectionFactory.createConnection(hbaseConf);

        // Spark 配置
        SparkConf sparkConf = new SparkConf().setAppName("HBaseScanToHDFSSave").setMaster("local[*]");
        JavaSparkContext sparkContext = new JavaSparkContext(sparkConf);

        // 构建扫描对象
        String tableName = "table_name";
        Scan scan = new Scan();
        FilterList filters = new FilterList();
        filters.addFilter(new PageFilter(1000));
        scan.setFilter(filters);

        // 从 HBase 表中扫描数据
        Table table = hbaseConn.getTable(TableName.valueOf(tableName));
        ResultScanner resultScanner = table.getScanner(scan);

        // 将结果保存到 List 中
        List<String> resultList = new ArrayList<>();
        for (Result result : resultScanner) {
            String rowKey = Bytes.toString(result.getRow());
            String columnFamily = "column_family";
            String qualifier1 = "qualifier1";
            String qualifier2 = "qualifier2";
            String qualifier3 = "qualifier3";
            String value1 = Bytes.toString(result.getValue(Bytes.toBytes(columnFamily), Bytes.toBytes(qualifier1)));
            String value2 = Bytes.toString(result.getValue(Bytes.toBytes(columnFamily), Bytes.toBytes(qualifier2)));
            String value3 = Bytes.toString(result.getValue(Bytes.toBytes(columnFamily), Bytes.toBytes(qualifier3)));
            String rowValue = String.join("\t", rowKey, value1, value2, value3);
            resultList.add(rowValue);
        }

        // 将 List 转换为 RDD 并保存到 HDFS
        JavaRDD<String> resultRDD = sparkContext.parallelize(resultList);
        FileSystem fileSystem = FileSystem.get(URI.create("hdfs://localhost:9000/"), new Configuration());
        Path outputPath = new Path("/output/path");
        if (fileSystem.exists(outputPath)) {
            fileSystem.delete(outputPath, true);
        }
        resultRDD.saveAsTextFile(outputPath.toString());

        // 关闭资源
        resultScanner.close();
        table.close();
        hbaseConn.close();
        sparkContext.close();
    }
}

这个程序使用 HBase 的 `getScanner` 方法获取扫描器对象，通过扫描器对象进行全量扫描，并使用 `Result.getValue` 方法获取指定列族、列限定符的值。您需要将相关的配置参数和表名、列族、列限定符等信息替换为实际的值，同时需要指定 HDFS 的输出路径。