Apache spark 齐柏林飞艇上悬而未决的关系

当我在齐柏林飞艇上运行查询时，它会为所有表返回此错误。当我在配置单元上运行相同的查询时，没有问题。蜂巢返回结果。 我使用spark解释器。 此代码也返回相同的错误

val df = spark.sql("SELECT * FROM dev_bm_bda_stg.ana_tfd_avr limit 100")

但当我试着通过spark shell运行它时，它起作用了

我使用spark 2.1.0，齐柏林飞艇0.7.3

我想问，我可能会错过什么配置

org.apache.spark.sql.AnalysisException: Table or view not found: `mydatabase`.`mytable`; line 1 pos 14;
'GlobalLimit 10
+- 'LocalLimit 10
   +- 'Project [*]
      +- 'UnresolvedRelation `mydatabase`.`mytable`
    at org.apache.spark.sql.catalyst.analysis.package$AnalysisErrorAt.failAnalysis(package.scala:42)
    at org.apache.spark.sql.catalyst.analysis.CheckAnalysis$$anonfun$checkAnalysis$1.apply(CheckAnalysis.scala:80)
    at org.apache.spark.sql.catalyst.analysis.CheckAnalysis$$anonfun$checkAnalysis$1.apply(CheckAnalysis.scala:76)
    at org.apache.spark.sql.catalyst.trees.TreeNode.foreachUp(TreeNode.scala:128)
    at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$foreachUp$1.apply(TreeNode.scala:127)
    at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$foreachUp$1.apply(TreeNode.scala:127)
    at scala.collection.immutable.List.foreach(List.scala:381)
    at org.apache.spark.sql.catalyst.trees.TreeNode.foreachUp(TreeNode.scala:127)
    at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$foreachUp$1.apply(TreeNode.scala:127)
    at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$foreachUp$1.apply(TreeNode.scala:127)
    at scala.collection.immutable.List.foreach(List.scala:381)
    at org.apache.spark.sql.catalyst.trees.TreeNode.foreachUp(TreeNode.scala:127)
    at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$foreachUp$1.apply(TreeNode.scala:127)
    at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$foreachUp$1.apply(TreeNode.scala:127)
    at scala.collection.immutable.List.foreach(List.scala:381)
    at org.apache.spark.sql.catalyst.trees.TreeNode.foreachUp(TreeNode.scala:127)
    at org.apache.spark.sql.catalyst.analysis.CheckAnalysis$class.checkAnalysis(CheckAnalysis.scala:76)
    at org.apache.spark.sql.catalyst.analysis.Analyzer.checkAnalysis(Analyzer.scala:57)
    at org.apache.spark.sql.execution.QueryExecution.assertAnalyzed(QueryExecution.scala:48)
    at org.apache.spark.sql.Dataset$.ofRows(Dataset.scala:63)
    at org.apache.spark.sql.SparkSession.sql(SparkSession.scala:600)
    at org.apache.spark.sql.SQLContext.sql(SQLContext.scala:699)
    at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
    at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
    at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
    at java.lang.reflect.Method.invoke(Method.java:497)
    at org.apache.zeppelin.spark.SparkSqlInterpreter.interpret(SparkSqlInterpreter.java:116)
    at org.apache.zeppelin.interpreter.LazyOpenInterpreter.interpret(LazyOpenInterpreter.java:97)
    at org.apache.zeppelin.interpreter.remote.RemoteInterpreterServer$InterpretJob.jobRun(RemoteInterpreterServer.java:498)
    at org.apache.zeppelin.scheduler.Job.run(Job.java:175)
    at org.apache.zeppelin.scheduler.FIFOScheduler$1.run(FIFOScheduler.java:139)
    at java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:511)
    at java.util.concurrent.FutureTask.run(FutureTask.java:266)
    at java.util.concurrent.ScheduledThreadPoolExecutor$ScheduledFutureTask.access$201(ScheduledThreadPoolExecutor.java:180)
    at java.util.concurrent.ScheduledThreadPoolExecutor$ScheduledFutureTask.run(ScheduledThreadPoolExecutor.java:293)
    at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
    at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
    at java.lang.Thread.run(Thread.java:745)