如何使用map和filter函数来使用RDD读取CSV文件，并使用CSV文件根据特定列进行选择？这里是一个示例CSV文件。

VendorID,tpep_pickup_datetime,tpep_dropoff_datetime,passenger_count,trip_distance,RatecodeID,store_and_fwd_flag,PULocationID,DOLocationID,payment_type,fare_amount,extra,mta_tax,tip_amount,tolls_amount,improvement_surcharge,total_amount

1,2017-07-01 00:06:25,2017-07-01 00:10:50,1,1.20,1,N,249,90,1,5.5,0.5,0.5,1.35,0,0.3,8.15
1,2017-07-01 00:20:04,2017-07-01 00:21:38,2,.20,1,N,249,158,2,3,0.5,0.5,0,0,0.3,4.3
1,2017-07-01 00:44:10,2017-07-01 00:59:29,1,4.30,1,N,100,45,1,15.5,0.5,0.5,3.35,0,0.3,20.15
1,2017-07-01 00:07:33,2017-07-01 00:31:30,1,8.30,1,N,138,162,1,27,0.5,0.5,6.8,5.76,0.3,40.86

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我尝试了下面的代码，但我不知道如何根据特定的列进行过滤并获取相关的行。

public class SparkUseCase{

    public static void main(String[] args) {    
    
        SparkConf conf = new SparkConf().setAppName("CSV Reader").setMaster("local[*]");
        JavaSparkContext sc = new JavaSparkContext(conf);
        JavaRDD<String> allRows = sc.textFile("in/trip_yellow_taxi.data");
        System.out.println(allRows.take(5));
        List<String> headers = Arrays.asList(allRows.take(1).get(0).split(","));

        String field="VendorID";
        
        JavaRDD<String>dataWithoutHeaders = allRows.filter(x -> !(x.split(",")[headers.indexOf(field)]).equals(field));
        
        JavaRDD<Integer> VendorID = dataWithoutHeaders.map(x -> Integer.valueOf(x.split(",")[headers.indexOf(field)]));
                
        for (Integer i:VendorID.collect()){
            System.out.println(i);
        }
        
      }
}

型
感谢你的帮助。
过滤案例：过滤所有RatecodeID为4的记录。