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ここに私のJava sparkコードがあります。これはSpark CSVデータ形式です。spark rdd生成時にCSVファイルの列を処理する方法は？
"f_name","l_name","job","gender","age","salary"
"Elsdon","Jaycob","Java programmer","male",43,2000
"Tamsen","Brittany","Java programmer","female",23,1500
"Floyd","Donny","Java programmer","male",33,1800
そして私は、上記のデータに
public class Person implements Serializable {
private String firstName;
private String lastName;
private String job;
private String gender;
private int salary;
private int age;
public Person(String firstName, String lastName, String job, String gender, int age, int salary) {
this.firstName = firstName;
this.lastName = lastName;
this.job = job;
this.gender = gender;
this.age = age;
this.salary = salary;
}
... getter and setter method.
が含まれており、以下のコードは、スパークJavaクライアントとJavaのRDDを生成しようとPersonクラスを生成します。
SparkConf sc = new SparkConf().setAppName("SparkTest").setMaster("local[*]");
JavaSparkContext jsc = new JavaSparkContext(sc);
JavaRDD<String> rdd_text = jsc.textFile("file:///" + srcDir + srcFile);
String[] header = rdd_text.map(line -> line.split(",")).first();
System.out.println(header[4]); // "age" is printed
JavaRDD<Person> persons = rdd_text.filter(line -> line.split(",")[4] != header[4]).map(
line -> {
String[] info = line.split(",");
System.out.println(info[4]); //43,23,33,"age" are printed
Person p = new Person(info[0], info[1], info[2], info[3],
Integer.parseInt(info[4]), Integer.parseInt(info[5]));
return p;
});
System.out.println(persons.collect());
のSystem.out.println（インフォ[4]）のコード行が印刷：
43
23
33
"age"
し、それが次の例外をスローし、
java.lang.NumberFormatException: For input string: ""age""
at java.lang.NumberFormatException.forInputString(NumberFormatException.java:65)
at java.lang.Integer.parseInt(Integer.java:569)
at java.lang.Integer.parseInt(Integer.java:615)
at com.aaa.spark.JavaClient.lambda$2(JavaClient.java:33)
at org.apache.spark.api.java.JavaPairRDD$$anonfun$toScalaFunction$1.apply(JavaPairRDD.scala:1040)
at scala.collection.Iterator$$anon$11.next(Iterator.scala:409)
at scala.collection.Iterator$class.foreach(Iterator.scala:893)
at scala.collection.AbstractIterator.foreach(Iterator.scala:1336)
at scala.collection.generic.Growable$class.$plus$plus$eq(Growable.scala:59)
at scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:104)
at scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:48)
at scala.collection.TraversableOnce$class.to(TraversableOnce.scala:310)
at scala.collection.AbstractIterator.to(Iterator.scala:1336)
at scala.collection.TraversableOnce$class.toBuffer(TraversableOnce.scala:302)
at scala.collection.AbstractIterator.toBuffer(Iterator.scala:1336)
at scala.collection.TraversableOnce$class.toArray(TraversableOnce.scala:289)
at scala.collection.AbstractIterator.toArray(Iterator.scala:1336)
at org.apache.spark.rdd.RDD$$anonfun$collect$1$$anonfun$13.apply(RDD.scala:936)
at org.apache.spark.rdd.RDD$$anonfun$collect$1$$anonfun$13.apply(RDD.scala:936)
at org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:2062)
at org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:2062)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87)
at org.apache.spark.scheduler.Task.run(Task.scala:108)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:335)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
at java.lang.Thread.run(Thread.java:748)
は、私がどのライン見当がつかないエラーコードと理由があります。 System.out.println(info[4])は "age"文字列値を出力します。 （情報[4]）ヘッダを持つ
jsc.textFile("file:///" + srcDir + srcFile);
ファイルの最初の行もInteger.parseIntによって処理された（「年齢」の値を持つ）とこのような理由：