Encoder<Transaction> encoder = Encoders.bean(Transaction.class);
Dataset<Row> transactionDS = sparkSession
                                    .read()
                                    .format("csv")
                                    .option("header", true)
                                    .option("delimiter", ",")
                                    .option("enforceSchema", false)
                                    .option("multiLine", false)
                                    .schema(encoder.schema())
                                    .load("s3a://xxx/testSchema.csv");
                                    .as(encoder);

    System.out.println("==============schema starts============");
    transactionDS.printSchema();
    System.out.println("==============schema ends============");

transactionDS.show(10, true); // this is the line that bombs.

我的简历是-

transactionId,accountId
1,2
10,44

我在日志中打印我的模式-（您看，列现在被翻转或排序了-啊！）

==============schema starts============
root
 |-- accountId: integer (nullable = true)
 |-- transactionId: long (nullable = true)

==============schema ends============

我正在接近错误

Caused by: java.lang.IllegalArgumentException: CSV header does not conform to the schema.
           Header: transactionId, accounted
           Schema: accountId, transactionId
           Expected: accountId but found: transactionId

这是我的Tranaction类的样子。

public class Transaction implements Serializable {

private static final long serialVersionUID = 7648268336292069686L;

private Long transactionId;
private Integer accountId;

public Long getTransactionId() {
    return transactionId;
}

public void setTransactionId(Long transactionId) {
    this.transactionId = transactionId;
}

public Integer getAccountId() {
    return accountId;
}

public void setAccountId(Integer accountId) {
    this.accountId = accountId;
}
}

问题-为什么Spark无法匹配我的模式？顺序混乱了。在我的CSV中，我传递了transactionid，accountId，但是Spark使用了我的模式accountId，transactionId。啊！