![]() ![]() In theory, error messages should be painful at worst and boring at best. Hence the need for error messages, which have been around nearly as long as computers themselves. One of the defining things about computers is that they–or, more specifically, the people who program them–get so many things so very wrong. : : .SQLServerException: Type with name 'SQLAnalyticsConnectorDataSource5333c24c65794922a8d9f5f2b6e56617' already exists.Īt .(SQLAnalyticsJDBCWrapper.scala:210)Īt .ItemsScanBuilder$PlanInputPartitionsUtilities$.createCETASResources(ItemsScanBuilder.scala:231)Īt .ItemsScanBuilder$PlanInputPartitionsUtilities$.extractDataAndGetLocation(ItemsScanBuilder.scala:170)Īt .ItemsScanBuilder.build(ItemsScanBuilder.scala:95)Īt .2.PushDownUtils$.pruneColumns(PushDownUtils.scala:176)Īt .2.V2ScanRelationPushDown$$anonfun$pruneColumns$1.applyOrElse(V2ScanRelationPushDown.scala:320)Īt .2.V2ScanRelationPushDown$$anonfun$pruneColumns$1.applyOrElse(V2ScanRelationPushDown.scala:313)Īt .$anonfun$transformDownWithPruning$1(TreeNode.scala:584)Īt .$.withOrigin(TreeNode.scala:176)Īt .(TreeNode.scala:584)Īt .org$apache$spark$sql$catalyst$plans$logical$AnalysisHelper$$super$transformDownWithPruning(LogicalPlan.scala:31)Īt .transformDownWithPruning(AnalysisHelper.scala:267)Īt .transformDownWithPruning$(AnalysisHelper.scala:263)Īt .transformDownWithPruning(LogicalPlan.scala:31)Īt .$anonfun$transformDownWithPruning$3(TreeNode.scala:589)Īt .(TreeNode.scala:1236)Īt .$(TreeNode.scala:1235)Īt .(InsertIntoHadoopFsRelationCommand.scala:47)Īt .(TreeNode.scala:589)Īt .(TreeNode.scala:560)Īt .(TreeNode.scala:528)Īt .2.V2ScanRelationPushDown$.pruneColumns(V2ScanRelationPushDown.scala:313)Īt .2.V2ScanRelationPushDown$.$anonfun$apply$6(V2ScanRelationPushDown.scala:47)Īt .2.V2ScanRelationPushDown$.$anonfun$apply$7(V2ScanRelationPushDown.scala:50)Īt (LinearSeqOptimized.scala:126)Īt $(LinearSeqOptimized.scala:122)Īt .foldLeft(List.scala:91)Īt .2.V2ScanRelationPushDown$.apply(V2ScanRelationPushDown.scala:49)Īt .2.V2ScanRelationPushDown$.apply(V2ScanRelationPushDown.scala:37)Īt .$anonfun$execute$2(RuleExecutor.scala:211)Īt .$anonfun$execute$1(RuleExecutor.scala:208)Īt .$anonfun$execute$1$adapted(RuleExecutor.scala:200)Īt .foreach(List.scala:431)Īt .(RuleExecutor.scala:200)Īt .$anonfun$executeAndTrack$1(RuleExecutor.scala:179)Īt .catalyst.QueryPlanningTracker$.withTracker(QueryPlanningTracker.scala:93)Īt .(RuleExecutor.scala:179)Īt .execution.QueryExecution.$anonfun$optimizedPlan$1(QueryExecution.scala:146)Īt .(QueryPlanningTracker.scala:120)Īt .execution.QueryExecution.$anonfun$executePhase$2(QueryExecution.scala:219)Īt .execution.QueryExecution$.withInternalError(QueryExecution.scala:562)Īt .execution.QueryExecution.$anonfun$executePhase$1(QueryExecution.scala:219)Īt .SparkSession.withActive(SparkSession.scala:779)Īt .(QueryExecution.scala:218)Īt .$lzycompute(QueryExecution.scala:142)Īt .(QueryExecution.scala:138)Īt .(QueryExecution.scala:156)Īt .$lzycompute(QueryExecution.scala:161)Īt .(QueryExecution.scala:158)Īt .(QueryExecution.scala:178)Īt .$lzycompute(QueryExecution.scala:185)Īt .(QueryExecution.scala:182)Īt .(QueryExecution.scala:238)Īt .$apache$spark$sql$execution$QueryExecution$$explainString(QueryExecution.scala:294)Īt .(QueryExecution.scala:263)Īt .execution.SQLExecution$.$anonfun$withNewExecutionId$6(SQLExecution.scala:105)Īt .execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:183)Īt .execution.SQLExecution$.$anonfun$withNewExecutionId$1(SQLExecution.scala:97)Īt .execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:66)Īt .execution.QueryExecution$$anonfun$eagerlyExecuteCommands$1.applyOrElse(QueryExecution.scala:108)Īt .execution.QueryExecution$$anonfun$eagerlyExecuteCommands$1.applyOrElse(QueryExecution.scala:104)Īt .(QueryExecution.scala:104)Īt .$lzycompute(QueryExecution.scala:88)Īt .(QueryExecution.scala:82)Īt .(QueryExecution.scala:136)Īt .nCommand(DataFrameWriter.scala:885)Īt .DataFrameWriter.saveToV1Source(DataFrameWriter.scala:415)Īt .DataFrameWriter.saveInternal(DataFrameWriter.scala:382)Īt .DataFrameWriter.save(DataFrameWriter.scala:241)Īt .DataFrameWriter.parquet(DataFrameWriter.scala:818)Īt 0(Native Method)Īt (NativeMethodAccessorImpl.java:62)Īt (DelegatingMethodAccessorImpl.java:43)Īt .invoke(Method.java:498)Īt (MethodInvoker.java:244)Īt (ReflectionEngine.java:357)Īt (AbstractCommand.java:132)Īt (CallCommand.java:79)Īt py4j.Gatewa圜onnection.”To err is human, but to really foul things up you need a computer.” So goes an old quip attributed to Paul Ehrlich. ![]() Py4JJavaError: An error occurred while calling o3808.parquet. Could some please help? I haven't found anything helpful online yet. I have this error pop up when calling actions in spark such as count(), show(), or write.parquet().
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