我试图在运行ApacheToree-scala内核的jupyter笔记本中使用ApacheSpark读取kudu表。
spark版本：2.2.0 scala版本：2.11 apache toree版本：0.3
这是我用来读取kudu表的代码

val kuduMasterAddresses = KUDU_MASTER_ADDRESSES_HERE
val kuduMasters: String = Seq(kuduMasterAddresses).mkString(",")

val kuduContext = new KuduContext(kuduMasters, spark.sparkContext)

val table = TABLE_NAME_HERE

def readKudu(table: String) = {
    val tableKuduOptions: Map[String, String] = Map(
    "kudu.table"  -> table,
    "kudu.master" -> kuduMasters
    )
    spark.sqlContext.read.options(tableKuduOptions).kudu
}

val kuduTableDF = readKudu(table)

使用kuducontext.tableexists（table）返回true。使用kudutabledf.columns会给出一个具有正确列名的字符串数组。
当我尝试应用count、show等操作时，问题就出现了。。。引发当前异常：
名称：org.apache.spark.sparkeexception消息：由于阶段失败而中止作业：获取任务结果时出现异常：java.io.ioexception:java.lang.classnotfoundexception:org.apache.kudu.spark.kudu.kuducontext$timestackTrace:atorg.apache.spark.scheduler.dagscheduler.org$apache$spark$scheduler$dagscheduler$$failjobandindependentstages（dagscheduler）。scala:1567)在org.apache.spark.scheduler.dagscheduler$$anonfun$abortstage$1.apply（dagscheduler。scala:1555)在org.apache.spark.scheduler.dagscheduler$$anonfun$abortstage$1.apply（dagscheduler。scala:1554)在scala.collection.mutable.resizablearray$class.foreach（resizablearray。scala:59)在scala.collection.mutable.arraybuffer.foreach（arraybuffer。scala:48)在org.apache.spark.scheduler.dagscheduler.abortstage（dagscheduler。scala:1554)位于org.apache.spark.scheduler.dagscheduler$$anonfun$handletasksetfailed$1.apply（dagscheduler）。scala:803)在org.apache.spark.scheduler.dagscheduler$$anonfun$handletasksetfailed$1.apply（dagscheduler）。scala:803)在scala.option.foreach（option。scala:257)在org.apache.spark.scheduler.dagscheduler.handletasksetfailed（dagscheduler。scala:803)位于org.apache.spark.scheduler.dagschedulereventprocessloop.doonreceive（dagscheduler。scala:1782)在org.apache.spark.scheduler.dagschedulereventprocessloop.onreceive（dagscheduler。scala:1737)位于org.apache.spark.scheduler.dagschedulereventprocessloop.onreceive（dagscheduler。scala:1726)在org.apache.spark.util.eventloop$$anon$1.run（eventloop。scala:48)
在org.apache.spark.scheduler.dagscheduler.runjob（dagscheduler。scala:619)在org.apache.spark.sparkcontext.runjob（sparkcontext。scala:2031)在org.apache.spark.sparkcontext.runjob（sparkcontext。scala:2052)在org.apache.spark.sparkcontext.runjob（sparkcontext。scala:2071)在org.apache.spark.sql.execution.sparkplan.executetake（sparkplan。scala:336)在org.apache.spark.sql.execution.collectlimitexec.executecollect（限制。scala:38)org.apache.spark.sql.dataset.org$apache$spark$sql$dataset$$collectfromplan（数据集）。scala:2865)在org.apache.spark.sql.dataset$$anonfun$head$1.apply（dataset。scala:2154)在org.apache.spark.sql.dataset$$anonfun$head$1.apply（dataset。scala:2154)在org.apache.spark.sql.dataset$$anonfun$55.apply（数据集。scala:2846)位于org.apache.spark.sql.execution.sqlexecution$.withnewexecutionid（sqlexecution）。scala:65)在org.apache.spark.sql.dataset.withaction（dataset。scala:2845)在org.apache.spark.sql.dataset.head（dataset。scala:2154)在org.apache.spark.sql.dataset.take（dataset。scala:2367)在org.apache.spark.sql.dataset.showstring（数据集。scala:241)在org.apache.spark.sql.dataset.show（dataset。scala:641)在org.apache.spark.sql.dataset.show（dataset。scala:600)在org.apache.spark.sql.dataset.show（dataset。scala:609)
我已经在apache toree笔记本中使用了adddeps魔术，如下所示：

%AddDeps org.apache.kudu kudu-spark2_2.11 1.6.0 --transitive --trace
%AddDeps org.apache.kudu kudu-client 1.6.0 --transitive --trace

我在执行以下导入时没有问题：

import org.apache.kudu.spark.kudu._