我有一个火花罐，其代码连接到oracle数据库，hive和cassandra。我能够在群集上执行jar。现在我试图从Spark Sandbox执行此jar，但无法成功 下面是代码： 通过.conf传递配置
val spark = SparkSession.builder().appName(appName).master(master).
config("hive.execution.engine",hiveEngine).config("hive.metastores.uris",hiveMeta)
.enableHiveSupport().getOrCreate()
//writing into hive
df_file_feed.write.format("hive").mode(org.apache.spark.sql.SaveMode.Append).saveAsTable("sap.mnkkkk")
警告和无法写入到配置单元
2019-02-02 20:09:07 WARN NativeCodeLoader:62 - Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
2019-02-02 20:09:15 INFO Persistence:77 - Property hive.metastore.integral.jdo.pushdown unknown - will be ignored
2019-02-02 20:09:15 INFO Persistence:77 - Property datanucleus.cache.level2 unknown - will be ignored
2019-02-02 20:09:17 INFO Datastore:77 - The class "org.apache.hadoop.hive.metastore.model.MFieldSchema" is tagged as "embedded-only" so does not have its own datastore table.
2019-02-02 20:09:17 INFO Datastore:77 - The class "org.apache.hadoop.hive.metastore.model.MOrder" is tagged as "embedded-only" so does not have its own datastore table.
2019-02-02 20:09:18 INFO Datastore:77 - The class "org.apache.hadoop.hive.metastore.model.MFieldSchema" is tagged as "embedded-only" so does not have its own datastore table.
2019-02-02 20:09:18 INFO Datastore:77 - The class "org.apache.hadoop.hive.metastore.model.MOrder" is tagged as "embedded-only" so does not have its own datastore table.
2019-02-02 20:09:18 INFO Query:77 - Reading in results for query "org.datanucleus.store.rdbms.query.SQLQuery@0" since the connection used is closing
2019-02-02 20:09:18 INFO Datastore:77 - The class "org.apache.hadoop.hive.metastore.model.MResourceUri" is tagged as "embedded-only" so does not have its own datastore table.
Exception in thread "main" org.apache.spark.sql.catalyst.analysis.NoSuchDatabaseException: Database 'sap' not found;
at org.apache.spark.sql.catalyst.catalog.SessionCatalog.org$apache$spark$sql$catalyst$catalog$SessionCatalog$$requireDbExists(SessionCatalog.scala:178)
at org.apache.spark.sql.catalyst.catalog.SessionCatalog.createTable(SessionCatalog.scala:311)
at org.apache.spark.sql.hive.execution.CreateHiveTableAsSelectCommand.run(CreateHiveTableAsSelectCommand.scala:72)
at org.apache.spark.sql.execution.command.DataWritingCommandExec.sideEffectResult$lzycompute(commands.scala:104)
at org.apache.spark.sql.execution.command.DataWritingCommandExec.sideEffectResult(commands.scala:102)
at org.apache.spark.sql.execution.command.DataWritingCommandExec.doExecute(commands.scala:122)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:131)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:127)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$executeQuery$1.apply(SparkPlan.scala:155)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:152)
at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:127)
at org.apache.spark.sql.execution.QueryExecution.toRdd$lzycompute(QueryExecution.scala:80)
at org.apache.spark.sql.execution.QueryExecution.toRdd(QueryExecution.scala:80)
at org.apache.spark.sql.DataFrameWriter$$anonfun$runCommand$1.apply(DataFrameWriter.scala:668)
at org.apache.spark.sql.DataFrameWriter$$anonfun$runCommand$1.apply(DataFrameWriter.scala:668)
at org.apache.spark.sql.execution.SQLExecution$$anonfun$withNewExecutionId$1.apply(SQLExecution.scala:78)
at org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:125)
at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:73)
at org.apache.spark.sql.DataFrameWriter.runCommand(DataFrameWriter.scala:668)
at org.apache.spark.sql.DataFrameWriter.createTable(DataFrameWriter.scala:465)
at org.apache.spark.sql.DataFrameWriter.saveAsTable(DataFrameWriter.scala:444)
at on datastore table.