如何在Java中创建接受字符串数组的Spark UDF？

import org.apache.spark.sql.api.java.UDF1;
import org.apache.spark.sql.api.java.UDF2;
import org.apache.spark.sql.api.java.UDF3;
import org.apache.spark.sql.api.java.UDF4;
import org.apache.spark.sql.api.java.UDF5;
import org.apache.spark.sql.api.java.UDF6;
import org.apache.spark.sql.api.java.UDF7;
import org.apache.spark.sql.api.java.UDF8;
import org.apache.spark.sql.api.java.UDF9;
import org.apache.spark.sql.api.java.UDF10;
import org.apache.spark.sql.api.java.UDF11;
import org.apache.spark.sql.api.java.UDF12;
import org.apache.spark.sql.api.java.UDF13;
import org.apache.spark.sql.api.java.UDF14;
import org.apache.spark.sql.api.java.UDF15;
import org.apache.spark.sql.api.java.UDF16;
import org.apache.spark.sql.api.java.UDF17;
import org.apache.spark.sql.api.java.UDF18;
import org.apache.spark.sql.api.java.UDF19;
import org.apache.spark.sql.api.java.UDF20;
import org.apache.spark.sql.types.DataType;
import org.apache.spark.sql.types.DataTypes;
import org.apache.spark.sql.SparkSession;

public class StringArrayUDF implements UDF1<String[], String> {
    @Override
    public String call(String[] strings) throws Exception {
        // 在这里编写处理字符串数组的逻辑
        // 返回处理后的结果
        return "";
    }
}

SparkSession spark = SparkSession.builder().appName("JavaSparkUDF").getOrCreate();
spark.udf().register("stringArrayUDF", new StringArrayUDF(), DataTypes.StringType);

spark.sql("SELECT stringArrayUDF(array('string1', 'string2', 'string3'))").show();