[BUG]: Error while running a .net application containing a UDF against remote databricks apache spark (e.g. Azure Databricks)

**Describe the bug**
A clear and concise description of what the bug is.

**To Reproduce**

Prerequisites: simple .net application with a simple SQL query and a UDF, which runs properly against a local apache spark.
Steps to reproduce the behavior:
1. Setup connection to a remote databricks apache spark (I have tested against an Azure Databricks) on your local dev machine using "databricks-connect configure". Test the connection using the "databricks-connect test"
2. Test the .net application **without UDF** first: comment out UDF related line codes and make sure the simple query runs against configured remote Azure Databricks.
3. Uncomment UDF related line codes.
4. See error.

Error (copied from the command line)

```javascript
[2020-01-06T08:04:29.4589366Z] [L-020538381857] [Error] [JvmBridge] JVM method execution failed: Nonstatic method showString failed for class 15 when called with 3 arguments ([Index=1, Type=Int32, Value=20], [Index=2, Type=Int32, Value=20], [Index=3, Type=Boolean, Value=False], )
[2020-01-06T08:04:29.4590049Z] [L-020538381857] [Error] [JvmBridge] org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 0.0 failed 4 times, most recent failure: Lost task 0.3 in stage 0.0 (TID 3, 10.139.64.14, executor 1): org.apache.spark.api.python.PythonException: Traceback (most recent call last):
File "/databricks/spark/python/pyspark/worker.py", line 342, in main
("%d.%d" % sys.version_info[:2], version))
Exception: Python in worker has different version 3.7 than that in driver 0.4.0, PySpark cannot run with different minor versions.Please check environment variables PYSPARK_PYTHON and PYSPARK_DRIVER_PYTHON are correctly set.

at org.apache.spark.api.python.BasePythonRunner$ReaderIterator.handlePythonException(PythonRunner.scala:534)
at org.apache.spark.sql.execution.python.PythonUDFRunner$$anon$1.read(PythonUDFRunner.scala:81)
at org.apache.spark.sql.execution.python.PythonUDFRunner$$anon$1.read(PythonUDFRunner.scala:64)
at org.apache.spark.api.python.BasePythonRunner$ReaderIterator.hasNext(PythonRunner.scala:488)
at org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:37)
at scala.collection.Iterator$$anon$12.hasNext(Iterator.scala:440)
at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:409)
at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:409)
at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.processNext(Unknown Source)
at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
at org.apache.spark.sql.execution.WholeStageCodegenExec$$anonfun$13$$anon$1.hasNext(WholeStageCodegenExec.scala:640)
at org.apache.spark.sql.execution.collect.UnsafeRowBatchUtils$.encodeUnsafeRows(UnsafeRowBatchUtils.scala:62)
at org.apache.spark.sql.execution.collect.Collector$$anonfun$2.apply(Collector.scala:159)
at org.apache.spark.sql.execution.collect.Collector$$anonfun$2.apply(Collector.scala:158)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)
at org.apache.spark.scheduler.Task.doRunTask(Task.scala:140)
at org.apache.spark.scheduler.Task.run(Task.scala:113)
at org.apache.spark.executor.Executor$TaskRunner$$anonfun$13.apply(Executor.scala:533)
at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1541)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:539)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
at java.lang.Thread.run(Thread.java:748)

Driver stacktrace:
at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:2362)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:2350)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:2349)
at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48)
at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:2349)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:1102)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:1102)
at scala.Option.foreach(Option.scala:257)
at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:1102)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:2581)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2529)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2517)
at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:49)
at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:897)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2280)
at org.apache.spark.sql.execution.collect.Collector.runSparkJobs(Collector.scala:270)
at org.apache.spark.sql.execution.collect.Collector.collect(Collector.scala:280)
at org.apache.spark.sql.execution.collect.Collector$.collect(Collector.scala:80)
at org.apache.spark.sql.execution.collect.Collector$.collect(Collector.scala:86)
at org.apache.spark.sql.execution.ResultCacheManager.getOrComputeResult(ResultCacheManager.scala:508)
at org.apache.spark.sql.execution.CollectLimitExec.executeCollectResult(limit.scala:55)
at org.apache.spark.sql.execution.SparkPlan.executeCollect(SparkPlan.scala:300)
at com.databricks.service.SparkServiceImpl$$anonfun$executePlan$1$$anonfun$apply$2.apply(SparkServiceImpl.scala:84)
at com.databricks.service.SparkServiceImpl$$anonfun$executePlan$1$$anonfun$apply$2.apply(SparkServiceImpl.scala:78)
at org.apache.spark.sql.execution.SQLExecution$$anonfun$withCustomExecutionEnv$1.apply(SQLExecution.scala:111)
at org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:240)
at org.apache.spark.sql.execution.SQLExecution$.withCustomExecutionEnv(SQLExecution.scala:97)
at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:170)
at com.databricks.service.SparkServiceImpl$$anonfun$executePlan$1.apply(SparkServiceImpl.scala:77)
at com.databricks.service.SparkServiceImpl$$anonfun$executePlan$1.apply(SparkServiceImpl.scala:74)
at com.databricks.logging.UsageLogging$$anonfun$recordOperation$1.apply(UsageLogging.scala:417)
at com.databricks.logging.UsageLogging$$anonfun$withAttributionContext$1.apply(UsageLogging.scala:239)
at scala.util.DynamicVariable.withValue(DynamicVariable.scala:58)
at com.databricks.logging.UsageLogging$class.withAttributionContext(UsageLogging.scala:234)
at com.databricks.spark.util.PublicDBLogging.withAttributionContext(DatabricksSparkUsageLogger.scala:18)
at com.databricks.logging.UsageLogging$class.withAttributionTags(UsageLogging.scala:276)
at com.databricks.spark.util.PublicDBLogging.withAttributionTags(DatabricksSparkUsageLogger.scala:18)
at com.databricks.logging.UsageLogging$class.recordOperation(UsageLogging.scala:398)
at com.databricks.spark.util.PublicDBLogging.recordOperation(DatabricksSparkUsageLogger.scala:18)
at com.databricks.spark.util.PublicDBLogging.recordOperation0(DatabricksSparkUsageLogger.scala:55)
at com.databricks.spark.util.DatabricksSparkUsageLogger.recordOperation(DatabricksSparkUsageLogger.scala:98)
at com.databricks.spark.util.UsageLogger$class.recordOperation(UsageLogger.scala:67)
at com.databricks.spark.util.DatabricksSparkUsageLogger.recordOperation(DatabricksSparkUsageLogger.scala:67)
at com.databricks.spark.util.UsageLogging$class.recordOperation(UsageLogger.scala:342)
at com.databricks.service.SparkServiceImpl$.recordOperation(SparkServiceImpl.scala:54)
at com.databricks.service.SparkServiceImpl$.executePlan(SparkServiceImpl.scala:74)
at com.databricks.service.SparkServiceRPCHandler.com$databricks$service$SparkServiceRPCHandler$$execute0(SparkServiceRPCHandler.scala:487)
at com.databricks.service.SparkServiceRPCHandler$$anonfun$executeRPC0$1.apply(SparkServiceRPCHandler.scala:376)
at com.databricks.service.SparkServiceRPCHandler$$anonfun$executeRPC0$1.apply(SparkServiceRPCHandler.scala:317)
at scala.util.DynamicVariable.withValue(DynamicVariable.scala:58)
at com.databricks.service.SparkServiceRPCHandler.executeRPC0(SparkServiceRPCHandler.scala:317)
at com.databricks.service.SparkServiceRPCHandler$$anon$3.call(SparkServiceRPCHandler.scala:272)
at com.databricks.service.SparkServiceRPCHandler$$anon$3.call(SparkServiceRPCHandler.scala:260)
at java.util.concurrent.FutureTask.run(FutureTask.java:266)
at com.databricks.service.SparkServiceRPCHandler$$anonfun$executeRPC$1.apply(SparkServiceRPCHandler.scala:304)
at com.databricks.service.SparkServiceRPCHandler$$anonfun$executeRPC$1.apply(SparkServiceRPCHandler.scala:284)
at scala.util.DynamicVariable.withValue(DynamicVariable.scala:58)
at com.databricks.service.SparkServiceRPCHandler.executeRPC(SparkServiceRPCHandler.scala:283)
at com.databricks.service.SparkServiceRPCServlet.doPost(SparkServiceRPCServer.scala:124)
at javax.servlet.http.HttpServlet.service(HttpServlet.java:707)
at javax.servlet.http.HttpServlet.service(HttpServlet.java:790)
at org.eclipse.jetty.servlet.ServletHolder.handle(ServletHolder.java:848)
at org.eclipse.jetty.servlet.ServletHandler.doHandle(ServletHandler.java:585)
at org.eclipse.jetty.servlet.ServletHandler.doScope(ServletHandler.java:515)
at org.eclipse.jetty.server.handler.ScopedHandler.handle(ScopedHandler.java:141)
at org.eclipse.jetty.server.handler.HandlerWrapper.handle(HandlerWrapper.java:134)
at org.eclipse.jetty.server.Server.handle(Server.java:539)
at org.eclipse.jetty.server.HttpChannel.handle(HttpChannel.java:333)
at org.eclipse.jetty.server.HttpConnection.onFillable(HttpConnection.java:251)
at org.eclipse.jetty.io.AbstractConnection$ReadCallback.succeeded(AbstractConnection.java:283)
at org.eclipse.jetty.io.FillInterest.fillable(FillInterest.java:108)
at org.eclipse.jetty.io.SelectChannelEndPoint$2.run(SelectChannelEndPoint.java:93)
at org.eclipse.jetty.util.thread.strategy.ExecuteProduceConsume.executeProduceConsume(ExecuteProduceConsume.java:303)
at org.eclipse.jetty.util.thread.strategy.ExecuteProduceConsume.produceConsume(ExecuteProduceConsume.java:148)
at org.eclipse.jetty.util.thread.strategy.ExecuteProduceConsume.run(ExecuteProduceConsume.java:136)
at org.eclipse.jetty.util.thread.QueuedThreadPool.runJob(QueuedThreadPool.java:671)
at org.eclipse.jetty.util.thread.QueuedThreadPool$2.run(QueuedThreadPool.java:589)
at java.lang.Thread.run(Thread.java:748)
Caused by: org.apache.spark.api.python.PythonException: Traceback (most recent call last):
File "/databricks/spark/python/pyspark/worker.py", line 342, in main
("%d.%d" % sys.version_info[:2], version))
Exception: Python in worker has different version 3.7 than that in driver 0.4.0, PySpark cannot run with different minor versions.Please check environment variables PYSPARK_PYTHON and PYSPARK_DRIVER_PYTHON are correctly set.

at org.apache.spark.api.python.BasePythonRunner$ReaderIterator.handlePythonException(PythonRunner.scala:534)
at org.apache.spark.sql.execution.python.PythonUDFRunner$$anon$1.read(PythonUDFRunner.scala:81)
at org.apache.spark.sql.execution.python.PythonUDFRunner$$anon$1.read(PythonUDFRunner.scala:64)
at org.apache.spark.api.python.BasePythonRunner$ReaderIterator.hasNext(PythonRunner.scala:488)
at org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:37)
at scala.collection.Iterator$$anon$12.hasNext(Iterator.scala:440)
at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:409)
at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:409)
at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.processNext(Unknown Source)
at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
at org.apache.spark.sql.execution.WholeStageCodegenExec$$anonfun$13$$anon$1.hasNext(WholeStageCodegenExec.scala:640)
at org.apache.spark.sql.execution.collect.UnsafeRowBatchUtils$.encodeUnsafeRows(UnsafeRowBatchUtils.scala:62)
at org.apache.spark.sql.execution.collect.Collector$$anonfun$2.apply(Collector.scala:159)
at org.apache.spark.sql.execution.collect.Collector$$anonfun$2.apply(Collector.scala:158)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)
at org.apache.spark.scheduler.Task.doRunTask(Task.scala:140)
at org.apache.spark.scheduler.Task.run(Task.scala:113)
at org.apache.spark.executor.Executor$TaskRunner$$anonfun$13.apply(Executor.scala:533)
at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1541)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:539)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
... 1 more

[2020-01-06T08:04:29.5052265Z] [L-020538381857] [Exception] [JvmBridge] JVM method execution failed: Nonstatic method showString failed for class 15 when called with 3 arguments ([Index=1, Type=Int32, Value=20], [Index=2, Type=Int32, Value=20], [Index=3, Type=Boolean, Value=False], )
at Microsoft.Spark.Interop.Ipc.JvmBridge.CallJavaMethod(Boolean isStatic, Object classNameOrJvmObjectReference, String methodName, Object[] args)
Unhandled exception. System.Exception: JVM method execution failed: Nonstatic method showString failed for class 15 when called with 3 arguments ([Index=1, Type=Int32, Value=20], [Index=2, Type=Int32, Value=20], [Index=3, Type=Boolean, Value=False], )
at Microsoft.Spark.Interop.Ipc.JvmBridge.CallJavaMethod(Boolean isStatic, Object classNameOrJvmObjectReference, String methodName, Object[] args)
at Microsoft.Spark.Interop.Ipc.JvmBridge.CallNonStaticJavaMethod(JvmObjectReference objectId, String methodName, Object[] args)
at Microsoft.Spark.Interop.Ipc.JvmObjectReference.Invoke(String methodName, Object[] args)
at Microsoft.Spark.Sql.DataFrame.Show(Int32 numRows, Int32 truncate, Boolean vertical)
at TestApp.Program.Main(String[] args) in C:\_projects\TestApp\test-data-science\Sources\TestApp\Program.cs:line 40
```

**Expected behavior**
A .net application containing a UDF works properly using connection to a remote databricks.

**Additional context**
Similar program in Python (same SQL query and similar UDF) works using the same configured remote connection properly.

Application has been started using spark-submit, i.e.
`%SPARK_HOME%\bin\spark-submit --class org.apache.spark.deploy.dotnet.DotnetRunner --master local microsoft-spark-2.4.x-0.7.0.jar dotnet TestApp.dll`