我们正在使用Java自定义目录与冰山。表是正确创建的，但我们得到一个问题，当我们插入数据。

public String createCustomTable(String tableName) {
        try {
            TableIdentifier tableIdentifier = TableIdentifier.of(name(), tableName);
            Schema schema = readSchema(tableIdentifier);
            Map<String, String> properties = ImmutableMap.of(
                    TableProperties.DEFAULT_FILE_FORMAT, FileFormat.PARQUET.name()
            );
            PartitionSpec partitionSpec = PartitionSpec.builderFor(schema)
                    .identity(getPartitionKeyfromSchema(tableIdentifier.name()))
                    .build();
            String tableLocation = defaultLocation + tableIdentifier.namespace().toString() + "/" + tableIdentifier.name();
            catalog.createTable(tableIdentifier, schema, partitionSpec, tableLocation, properties);
            catalog.loadTable(TableIdentifier.of(name(), tableName));
            return "Table created";
        } catch (Exception e) {
            return e.getMessage();
        }
    }
    public String insertData(String tableName, String csvPath) throws IOException {
            Table icebergTable = catalog.loadTable(TableIdentifier.of(name(), tableName));
            SparkSession spark = SparkSession.builder()
                    .config("spark.master", "local")
                    .getOrCreate();
            String headerJson = readHeaderJson(tableName);
            LOGGER.info("Header JSON for {}: {}", tableName, headerJson);
            String[] columns = headerJson.split(",");
            Dataset<Row> df = spark.read()
                    .option("header", "false")
                    .option("inferSchema", "false")
                    .option("comment", "#")
                    .option("sep", "|")
                    .csv(csvPath)
                    .toDF(columns);
            LOGGER.info("Actual columns: {}", Arrays.toString(df.columns()));
            for (String col : df.columns()) {
                df = df.withColumn(col, df.col(col).cast("string"));
            }
            df.write().format("iceberg").mode(SaveMode.Append).save(icebergTable.location());
            LOGGER.info("Data inserted successfully into table: {}", tableName);
    }

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当我们通过Java中的主程序执行时，它可以完美地工作
然而，当我们创建一个jar并从Spark调用它时，它会给我们这个错误

ERROR:root:Error: An error occurred while calling o0.insertData.
: java.lang.ClassNotFoundException:
Failed to find data source: iceberg. Please find packages at
http://spark.apache.org/third-party-projects.html
        at org.apache.spark.sql.errors.QueryExecutionErrors$.failedToFindDataSourceError(QueryExecutionErrors.scala:443)        at org.apache.spark.sql.execution.datasources.DataSource$.lookupDataSource(DataSource.scala:670)
        at org.apache.spark.sql.execution.datasources.DataSource$.lookupDataSourceV2(DataSource.scala:720)
        at org.apache.spark.sql.DataFrameWriter.lookupV2Provider(DataFrameWriter.scala:852)
        at org.apache.spark.sql.DataFrameWriter.saveInternal(DataFrameWriter.scala:256)
        at org.apache.spark.sql.DataFrameWriter.save(DataFrameWriter.scala:239)
        at com.xyz.catalog.CustomCatalog.insertData(CustomCatalog.java:178)
        at java.base/jdk.internal.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
        at java.base/jdk.internal.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
        at java.base/jdk.internal.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)     
        at java.base/java.lang.reflect.Method.invoke(Method.java:566)
        at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244)
        at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357)
        at py4j.Gateway.invoke(Gateway.java:282)
        at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132)
        at py4j.commands.CallCommand.execute(CallCommand.java:79)
        at py4j.GatewayConnection.run(GatewayConnection.java:238)
        at java.base/java.lang.Thread.run(Thread.java:829)
Caused by: java.lang.ClassNotFoundException: iceberg.DefaultSource
        at java.base/jdk.internal.loader.BuiltinClassLoader.loadClass(BuiltinClassLoader.java:581)
        at java.base/jdk.internal.loader.ClassLoaders$AppClassLoader.loadClass(ClassLoaders.java:178)
        at java.base/java.lang.ClassLoader.loadClass(ClassLoader.java:527)
        at org.apache.spark.sql.execution.datasources.DataSource$.$anonfun$lookupDataSource$5(DataSource.scala:656)     
        at scala.util.Try$.apply(Try.scala:210)
        at org.apache.spark.sql.execution.datasources.DataSource$.$anonfun$lookupDataSource$4(DataSource.scala:656)     
        at scala.util.Failure.orElse(Try.scala:221)
        at org.apache.spark.sql.execution.datasources.DataSource$.lookupDataSource(DataSource.scala:656)
        ... 16 more

型
任何帮助将不胜感激
我们正在尝试使用自定义目录在冰山表中创建和插入数据。我们希望插入能够正常工作

df.write().format("iceberg").mode(SaveMode.Append).save(icebergTable.location());

型
然而，我们得到一个错误