我有下面的javaspark配置单元示例，可以在官方的apache/spark github上找到。我花了很多时间来理解如何在hortonworkshadoop沙盒中运行这个示例，但没有成功。
目前，我正在做以下工作：
当我在maven项目中导入apache/spark示例时，它工作得很好，而且我没有发现任何关于体面的问题，所以我猜这里没有问题。
下一步是准备要在我的hadoop沙盒中运行的代码—问题从这里开始，我可能设置了一些错误。我就是这么做的：
将sparksession设置为master local，将spark.sql.warehouse.dir更改为hive.metastore.uris并设置thrift://localhost：9083（如我在ambari的Hive中看到的）作为仓库位置。

SparkSession spark = SparkSession
  .builder()
  .appName("Java Spark Hive Example")
        .master("local[*]")
        .config("hive.metastore.uris", "thrift://localhost:9083")
  .enableHiveSupport()
  .getOrCreate();

然后我替换 spark.sql("LOAD DATA LOCAL INPATH 'examples/src/main/resources/kv1.txt' INTO TABLE src"); 我上传了kv1.txt的hdfs路径：

spark.sql("LOAD DATA LOCAL INPATH 'hdfs:///tmp/kv1.txt' INTO TABLE src");

最后一步是做一个jar mvn package 在pom.xml上-它构建时没有错误，并提供了original-spark-examples_2.11-2.3.0-snapshot.jar
我将程序集复制到hadoop沙盒 scp -P 2222 ./target/original-spark-examples_2.11-2.3.0-SNAPSHOT.jar root@sandbox.hortonworks.com:/root 并使用spark submit运行代码 /usr/hdp/current/spark2-client/bin/spark-submit --class "JavaSparkHiveExample" --master local ./original-spark-examples_2.11-2.3.0-SNAPSHOT.jar 返回以下错误：

[root@sandbox-hdp ~]# /usr/hdp/current/spark2-client/bin/spark-submit --class "JavaSparkHiveExample" --master local ./original-spark-examples_2.11-2.3.0-SNAPSHOT.jar
java.lang.ClassNotFoundException: JavaSparkHiveExample
        at java.net.URLClassLoader.findClass(URLClassLoader.java:381)
        at java.lang.ClassLoader.loadClass(ClassLoader.java:424)
        at java.lang.ClassLoader.loadClass(ClassLoader.java:357)
        at java.lang.Class.forName0(Native Method)
        at java.lang.Class.forName(Class.java:348)
        at org.apache.spark.util.Utils$.classForName(Utils.scala:230)
        at org.apache.spark.deploy.SparkSubmit$.org$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:739)
        at org.apache.spark.deploy.SparkSubmit$.doRunMain$1(SparkSubmit.scala:180)
        at org.apache.spark.deploy.SparkSubmit$.submit(SparkSubmit.scala:205)
        at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:119)
        at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)
[root@sandbox-hdp ~]#

..在这里我完全被卡住了，可能我错过了一些准备代码运行的步骤等等。
如果我能得到一些帮助，让这些代码在我的hadoop沙盒上运行，我将非常高兴。我能够很好地运行javawordcount.java spark示例，但是对于这个示例，我完全卡住了。谢谢：）
完整的javasparkhiveexample.java：

/*
 * Licensed to the Apache Software Foundation (ASF) under one or more
 * contributor license agreements.  See the NOTICE file distributed with
 * this work for additional information regarding copyright ownership.
 * The ASF licenses this file to You under the Apache License, Version 2.0
 * (the "License"); you may not use this file except in compliance with
 * the License.  You may obtain a copy of the License at
 *
 *    http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 */
package org.apache.spark.examples.sql.hive;

// $example on:spark_hive$
import java.io.File;
import java.io.Serializable;
import java.util.ArrayList;
import java.util.List;

import org.apache.spark.api.java.function.MapFunction;
import org.apache.spark.sql.Dataset;
import org.apache.spark.sql.Encoders;
import org.apache.spark.sql.Row;
import org.apache.spark.sql.SparkSession;
// $example off:spark_hive$

public class JavaSparkHiveExample {

  // $example on:spark_hive$
  public static class Record implements Serializable {
    private int key;
    private String value;

    public int getKey() {
      return key;
    }

    public void setKey(int key) {
      this.key = key;
    }

    public String getValue() {
      return value;
    }

    public void setValue(String value) {
      this.value = value;
    }
  }
  // $example off:spark_hive$

  public static void main(String[] args) {
    // $example on:spark_hive$
    // warehouseLocation points to the default location for managed databases and tables
    String warehouseLocation = new File("spark-warehouse").getAbsolutePath();
    SparkSession spark = SparkSession
      .builder()
      .appName("Java Spark Hive Example")
      .config("spark.sql.warehouse.dir", warehouseLocation)
      .enableHiveSupport()
      .getOrCreate();

    spark.sql("CREATE TABLE IF NOT EXISTS src (key INT, value STRING) USING hive");
    spark.sql("LOAD DATA LOCAL INPATH 'examples/src/main/resources/kv1.txt' INTO TABLE src");

    // Queries are expressed in HiveQL
    spark.sql("SELECT * FROM src").show();
    // +---+-------+
    // |key|  value|
    // +---+-------+
    // |238|val_238|
    // | 86| val_86|
    // |311|val_311|
    // ...

    // Aggregation queries are also supported.
    spark.sql("SELECT COUNT(*) FROM src").show();
    // +--------+
    // |count(1)|
    // +--------+
    // |    500 |
    // +--------+

    // The results of SQL queries are themselves DataFrames and support all normal functions.
    Dataset<Row> sqlDF = spark.sql("SELECT key, value FROM src WHERE key < 10 ORDER BY key");

    // The items in DataFrames are of type Row, which lets you to access each column by ordinal.
    Dataset<String> stringsDS = sqlDF.map(
        (MapFunction<Row, String>) row -> "Key: " + row.get(0) + ", Value: " + row.get(1),
        Encoders.STRING());
    stringsDS.show();
    // +--------------------+
    // |               value|
    // +--------------------+
    // |Key: 0, Value: val_0|
    // |Key: 0, Value: val_0|
    // |Key: 0, Value: val_0|
    // ...

    // You can also use DataFrames to create temporary views within a SparkSession.
    List<Record> records = new ArrayList<>();
    for (int key = 1; key < 100; key++) {
      Record record = new Record();
      record.setKey(key);
      record.setValue("val_" + key);
      records.add(record);
    }
    Dataset<Row> recordsDF = spark.createDataFrame(records, Record.class);
    recordsDF.createOrReplaceTempView("records");

    // Queries can then join DataFrames data with data stored in Hive.
    spark.sql("SELECT * FROM records r JOIN src s ON r.key = s.key").show();
    // +---+------+---+------+
    // |key| value|key| value|
    // +---+------+---+------+
    // |  2| val_2|  2| val_2|
    // |  2| val_2|  2| val_2|
    // |  4| val_4|  4| val_4|
    // ...
    // $example off:spark_hive$

    spark.stop();
  }
}