原因：java.lang.RuntimeException:java.lang.String不是日期架构的有效外部类型

我正在尝试使用Spark SQL将一些Java对象数据插入MySQL。下面是我的简化代码：

import java.io.Serializable;
import java.sql.Date;

import org.apache.spark.sql.types.DataTypes;
import org.apache.spark.sql.types.StructField;
import org.apache.spark.sql.types.StructType;

import lombok.AllArgsConstructor;
import lombok.Data;
import lombok.NoArgsConstructor;

@Data
@AllArgsConstructor
@NoArgsConstructor
public class Model implements Serializable {

    private String state;
    private String title;
    private String exportCntry;
    private String filepath;
    private String unit;
    private String frequency; 
    private String Seasonal_adjust; 
    private Date Last_updated;

    private static StructType structType = DataTypes.createStructType(new StructField[] {

              DataTypes.createStructField("state", DataTypes.StringType, false),
              DataTypes.createStructField("title", DataTypes.StringType, false),
              DataTypes.createStructField("exportCntry", DataTypes.StringType, false),
              DataTypes.createStructField("filepath", DataTypes.StringType, false),
              DataTypes.createStructField("unit", DataTypes.StringType, false),
              DataTypes.createStructField("frequency", DataTypes.StringType, false),
              DataTypes.createStructField("Seasonal_adjust", DataTypes.StringType, false),
              DataTypes.createStructField("Last_updated", DataTypes.DateType, false)
    });

    public static StructType getStructType() {
        return structType;
    }

    public static void setStructType(StructType structType) {
        Model.structType = structType;
    }

    public Object[] getAllValues() {
        return new Object[] { state, title, exportCntry, filepath, unit, frequency, unit, 
                                                        frequency, Seasonal_adjust, Last_updated
        };
    }
}

下面的代码是Spark SQL代码，它将上述

Model

java对象插入MySQL

---

这个异常似乎与

java.sql.Date

对象API有关。Spark SQL

Dataframe.write

方法不起作用。我错过了一些过程了吗？

根据您对过去问题的编辑，请注意，我们更喜欢这里的技术写作风格。我们轻轻地劝阻问候，希望你能帮助，谢谢，提前感谢，感谢信，问候，亲切的问候，签名，请你能帮助，闲聊的材料和缩写的txtspk，恳求，你被困多久了，投票建议，元评论等。只需解释你的问题，并展示你已经尝试了什么，你期望什么，实际上发生了什么。@Abra:谢谢你想在这里编辑。然而，斜体字的软件名称并不能使它们更清晰，而且会分散读者的注意力。请确保它们的包装正确。

import java.sql.Date;
import java.util.Arrays;
import java.util.LinkedList;
import java.util.List;
import java.util.Properties;
import java.util.Queue;

import org.apache.spark.SparkContext;
import org.apache.spark.api.java.JavaRDD;
import org.apache.spark.api.java.JavaSparkContext;
import org.apache.spark.sql.Dataset;
import org.apache.spark.sql.Row;
import org.apache.spark.sql.RowFactory;
import org.apache.spark.sql.SaveMode;
import org.apache.spark.sql.SparkSession;
import org.apache.spark.streaming.Durations;
import org.apache.spark.streaming.api.java.JavaDStream;
import org.apache.spark.streaming.api.java.JavaStreamingContext;

public class Processor {

    private static List<String> testData = Arrays.asList(
            "Alabama,ValueofExports,Israel,A/L/I/ALISRA052SCEN.csv,$,A,NSA,2018-06-26",
            "Alaska,ValueofExports,Israel,A/K/AKISRA052SCEN.csv,$,A,NSA,2018-06-26",
            "Arizona,ValueofExports,Israel,A/Z/I/AZISRA052SCEN.csv,$,A,NSA,2018-06-26",
            "Arkansas,ValueofExports,Israel,A/R/I/ARISRA052SCEN.csv,$,A,NSA,2018-06-26",
            "California,ValueofExports,Israel,C/A/I/CAISRA052SCEN.csv,$,A,NSA,2018-06-26",
            "Colorado,ValueofExports,Israel,C/O/I/COISRA052SCEN.csv,$,A,NSA,2018-06-26",
            "Connecticut,ValueofExports,Israel,C/T/I/CTISRA052SCEN.csv,$,A,NSA,2018-06-26",
            "Delaware,ValueofExports,Israel,D/E/I/DEISRA052SCEN.csv,$,A,NSA,2018-06-26"
    );

    public static void main(String[] args) throws Exception{
        // TODO Auto-generated method stub
        Properties jdbcProps = new Properties();
        jdbcProps.put("user", "root");
        jdbcProps.put("password", "password");

        SparkSession spark = SparkSession.builder().master("local[*]").appName("Spark Kafka Test").getOrCreate();

        JavaSparkContext jsc = JavaSparkContext.fromSparkContext(SparkContext.getOrCreate());
      JavaStreamingContext jssc = new JavaStreamingContext(jsc, Durations.milliseconds(1000));    

      JavaRDD<String> rddTest = jsc.parallelize(testData);
      Queue<JavaRDD<String>> queue = new LinkedList<JavaRDD<String>>();
      queue.add(rddTest);
      JavaDStream<String> jds = jssc.queueStream( queue );

        JavaDStream<Model> jdm = jds.map(str -> {
            String[] parameters = new String[str.split(",").length];
            parameters = str.split(",");

            Date date = Date.valueOf(parameters[7]);

            Model data = new Model(parameters[0], parameters[1], parameters[2], parameters[3], 
                    parameters[4], parameters[5], parameters[6], date);

            return data;
        });

        jdm.map(e -> {
            Row row = RowFactory.create(e.getAllValues());
            return row;
        }).foreachRDD(rdd -> {
            Dataset<Row> df = spark.createDataFrame(rdd, Model.getStructType());
            df.printSchema();
            df.write()
                    .mode(SaveMode.Append)
                    .jdbc("jdbc:mysql://localhost:3306/test?characterEncoding=utf8&serverTimezone=Asia/Seoul",
                            "test", jdbcProps);
        });

        jssc.start();
        jssc.awaitTermination();
        jssc.close();
    }

}

Caused by: java.lang.RuntimeException: java.lang.String is not a valid external type for schema of date
    at org.apache.spark.sql.catalyst.expressions.GeneratedClass$SpecificUnsafeProjection.StaticInvoke_7$(Unknown Source)
    at org.apache.spark.sql.catalyst.expressions.GeneratedClass$SpecificUnsafeProjection.apply(Unknown Source)
    at org.apache.spark.sql.catalyst.encoders.ExpressionEncoder.toRow(ExpressionEncoder.scala:289)