我正在使用Apache Spark的示例代码follow文档：https://spark.apache.org/docs/latest/ml-features.html#countvectorizer

    import java.util.Arrays;
    import org.apache.spark.SparkConf;
    import org.apache.spark.api.java.JavaSparkContext;
    import org.apache.spark.ml.feature.CountVectorizer;
    import org.apache.spark.ml.feature.CountVectorizerModel;
    import org.apache.spark.sql.DataFrame;
    import org.apache.spark.sql.Row;
    import org.apache.spark.sql.RowFactory;
    import org.apache.spark.sql.SQLContext;
    import org.apache.spark.sql.types.*;
    public class CountVectorizer_Demo {
    public static void main(String[] args) {
        SparkConf conf = new SparkConf().setAppName("LDA Online").setMaster(
                "local");
        JavaSparkContext sc = new JavaSparkContext(conf);

        SQLContext sqlContext = new SQLContext(sc);

        // Input data: Each row is a bag of words from a sentence or document.
        JavaRDD<Row> jrdd = sc.parallelize(Arrays.asList(
          RowFactory.create(Arrays.asList("a", "b", "c")),
          RowFactory.create(Arrays.asList("a", "b", "b", "c", "a"))
        ));
        StructType schema = new StructType(new StructField [] {
          new StructField("text", new ArrayType(DataTypes.StringType, true), false, Metadata.empty())
        });
        DataFrame df = sqlContext.createDataFrame(jrdd, schema);

        // fit a CountVectorizerModel from the corpus
        CountVectorizerModel cvModel = new CountVectorizer()
          .setInputCol("text")
          .setOutputCol("feature")
          .setVocabSize(3)
          .setMinDF(2) // a term must appear in more or equal to 2 documents to be included in the vocabulary
          .fit(df);

        // alternatively, define CountVectorizerModel with a-priori vocabulary
        CountVectorizerModel cvm = new CountVectorizerModel(new String[]{"a", "b", "c"})
          .setInputCol("text")
          .setOutputCol("feature");

        cvModel.transform(df).show();
    }
}

但我收到错误消息：

22年10月15日23:04:20信息BlockManagerMaster：使用703.6 MB RAM注册block manager localhost:56882，BlockManagerId（，localhost，56882）22年10月15日23:04:20信息BlockManagerMaster：在线程“main”java中注册BlockManager异常。lang.NoClassDefFoundError:org/apache/spark/sql/catalyst/InternalRow at org。阿帕奇。火花ml.功能。CountVectorizerParams$类。在组织中验证AndTransferMSChema（CountVectorizer.scala:72）。阿帕奇。火花ml.功能。计数矢量器。在组织中验证AndTransferMSChema（CountVectorizer.scala:107）。阿帕奇。火花ml.功能。计数矢量器。org上的transformSchema（CountVectorizer.scala:168）。阿帕奇。火花ml.PipelineStage。org上的transformSchema（Pipeline.scala:62）。阿帕奇。火花ml.功能。计数矢量器。在main处安装（CountVectorizer.scala:130）。CountVectorizer\u演示。main（CountVectorizer\u Demo.java:39）由：java引起。lang.ClassNotFoundException：组织。阿帕奇。火花sql。催化剂java的InternalRow。网URLClassLoader 1美元。在java上运行（URLClassLoader.java:366）。网URLClassLoader 1美元。在java上运行（URLClassLoader.java:355）。安全AccessController。java上的doPrivileged（本机方法）。网URLClassLoader。java上的findClass（URLClassLoader.java:354）。lang.ClassLoader。sun的loadClass（ClassLoader.java:425）。杂项。启动器$AppClassLoader。java上的loadClass（Launcher.java:308）。lang.ClassLoader。loadClass（ClassLoader.java:358）。。。6个以上

提前感谢。