Cannot perform join between points and polygon using Scala 2.11 and Spark 2.3.1

[djpirra]

Currently trying to join to dataframes with the following command:

val df_green_pickup = green_data.join(neighborhoods).where($"pickup_point" within $"polygon") display(df_green_pickup)

Having the following exception:

SparkException: Job aborted due to stage failure: Task 0 in stage 44.0 failed 4 times, most recent failure: Lost task 0.3 in stage 44.0 (TID 875, 10.139.64.11, executor 10): java.lang.NoSuchMethodError: org.apache.spark.sql.catalyst.expressions.codegen.ExprCode.value()Ljava/lang/String; at org.apache.spark.sql.catalyst.expressions.Within$$anonfun$doGenCode$2.apply(predicates.scala:202) at org.apache.spark.sql.catalyst.expressions.Within$$anonfun$doGenCode$2.apply(predicates.scala:180) at org.apache.spark.sql.catalyst.expressions.BinaryExpression.nullSafeCodeGen(Expression.scala:553) at org.apache.spark.sql.catalyst.expressions.Within.doGenCode(predicates.scala:180) at org.apache.spark.sql.catalyst.expressions.Expression$$anonfun$genCode$2.apply(Expression.scala:111) at org.apache.spark.sql.catalyst.expressions.Expression$$anonfun$genCode$2.apply(Expression.scala:108) at scala.Option.getOrElse(Option.scala:121) at org.apache.spark.sql.catalyst.expressions.Expression.genCode(Expression.scala:108) at org.apache.spark.sql.catalyst.expressions.codegen.GeneratePredicate$.create(GeneratePredicate.scala:60) at org.apache.spark.sql.catalyst.expressions.codegen.GeneratePredicate$.generate(GeneratePredicate.scala:46) at org.apache.spark.sql.execution.SparkPlan.newPredicate(SparkPlan.scala:382) at org.apache.spark.sql.execution.joins.CartesianProductExec$$anonfun$doExecute$1.apply(CartesianProductExec.scala:84) at org.apache.spark.sql.execution.joins.CartesianProductExec$$anonfun$doExecute$1.apply(CartesianProductExec.scala:81) at org.apache.spark.rdd.RDD$$anonfun$mapPartitionsWithIndexInternal$1$$anonfun$apply$24.apply(RDD.scala:830) at org.apache.spark.rdd.RDD$$anonfun$mapPartitionsWithIndexInternal$1$$anonfun$apply$24.apply(RDD.scala:830) at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:42) at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:336) at org.apache.spark.rdd.RDD.iterator(RDD.scala:300) at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87) at org.apache.spark.scheduler.Task.run(Task.scala:112) at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:384) 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)

Did anyone tried this on the same versions?

Thank you

[lmerchante]

Similar error with same versions in test code:

import magellan.{Point, Polygon}
import org.apache.spark.sql.magellan.dsl.expressions._
import org.apache.spark.sql.types._

val points = sc.parallelize(Seq((-1.0, -1.0), (-1.0, 1.0), (1.0, -1.0))).toDF("x", "y").select(point($"x", $"y").as("point"))
points.show()

This is the trace:

scala> points.show()
java.lang.NoSuchMethodError: org.apache.spark.sql.catalyst.expressions.codegen.CodegenContext.addMutableState(Ljava/lang/String;Ljava/lang/String;Ljava/lang/String;)V
  at org.apache.spark.sql.types.PointConverter.doGenCode(PointConverter.scala:43)
  at org.apache.spark.sql.catalyst.expressions.Expression$$anonfun$genCode$2.apply(Expression.scala:107)
  at org.apache.spark.sql.catalyst.expressions.Expression$$anonfun$genCode$2.apply(Expression.scala:104)
  at scala.Option.getOrElse(Option.scala:121)
  at org.apache.spark.sql.catalyst.expressions.Expression.genCode(Expression.scala:104)
  at org.apache.spark.sql.catalyst.expressions.Cast.doGenCode(Cast.scala:624)
  at org.apache.spark.sql.catalyst.expressions.Expression$$anonfun$genCode$2.apply(Expression.scala:107)
  at org.apache.spark.sql.catalyst.expressions.Expression$$anonfun$genCode$2.apply(Expression.scala:104)
  at scala.Option.getOrElse(Option.scala:121)
  at org.apache.spark.sql.catalyst.expressions.Expression.genCode(Expression.scala:104)
  at org.apache.spark.sql.catalyst.expressions.Cast.genCode(Cast.scala:619)
  at org.apache.spark.sql.catalyst.expressions.Alias.genCode(namedExpressions.scala:142)
  at org.apache.spark.sql.execution.ProjectExec$$anonfun$6.apply(basicPhysicalOperators.scala:60)
  at org.apache.spark.sql.execution.ProjectExec$$anonfun$6.apply(basicPhysicalOperators.scala:60)
  at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)
  at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)
  at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
  at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48)
  at scala.collection.TraversableLike$class.map(TraversableLike.scala:234)
  at scala.collection.AbstractTraversable.map(Traversable.scala:104)
  at org.apache.spark.sql.execution.ProjectExec.doConsume(basicPhysicalOperators.scala:60)
  at org.apache.spark.sql.execution.CodegenSupport$class.consume(WholeStageCodegenExec.scala:181)
  at org.apache.spark.sql.execution.SerializeFromObjectExec.consume(objects.scala:101)
  at org.apache.spark.sql.execution.SerializeFromObjectExec.doConsume(objects.scala:121)
  at org.apache.spark.sql.execution.CodegenSupport$class.constructDoConsumeFunction(WholeStageCodegenExec.scala:208)
  at org.apache.spark.sql.execution.CodegenSupport$class.consume(WholeStageCodegenExec.scala:179)
  at org.apache.spark.sql.execution.InputAdapter.consume(WholeStageCodegenExec.scala:354)
  at org.apache.spark.sql.execution.InputAdapter.doProduce(WholeStageCodegenExec.scala:383)
  at org.apache.spark.sql.execution.CodegenSupport$$anonfun$produce$1.apply(WholeStageCodegenExec.scala:88)
  at org.apache.spark.sql.execution.CodegenSupport$$anonfun$produce$1.apply(WholeStageCodegenExec.scala:83)
  at org.apache.spark.sql.execution.SparkPlan$$anonfun$executeQuery$1.apply(SparkPlan.scala:155)
  at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
  at org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:152)
  at org.apache.spark.sql.execution.CodegenSupport$class.produce(WholeStageCodegenExec.scala:83)
  at org.apache.spark.sql.execution.InputAdapter.produce(WholeStageCodegenExec.scala:354)
  at org.apache.spark.sql.execution.SerializeFromObjectExec.doProduce(objects.scala:114)
  at org.apache.spark.sql.execution.CodegenSupport$$anonfun$produce$1.apply(WholeStageCodegenExec.scala:88)
  at org.apache.spark.sql.execution.CodegenSupport$$anonfun$produce$1.apply(WholeStageCodegenExec.scala:83)
  at org.apache.spark.sql.execution.SparkPlan$$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.CodegenSupport$class.produce(WholeStageCodegenExec.scala:83)
  at org.apache.spark.sql.execution.SerializeFromObjectExec.produce(objects.scala:101)
  at org.apache.spark.sql.execution.ProjectExec.doProduce(basicPhysicalOperators.scala:45)
  at org.apache.spark.sql.execution.CodegenSupport$$anonfun$produce$1.apply(WholeStageCodegenExec.scala:88)
  at org.apache.spark.sql.execution.CodegenSupport$$anonfun$produce$1.apply(WholeStageCodegenExec.scala:83)
  at org.apache.spark.sql.execution.SparkPlan$$anonfun$executeQuery$1.apply(SparkPlan.scala:155)
  at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
  at org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:152)
  at org.apache.spark.sql.execution.CodegenSupport$class.produce(WholeStageCodegenExec.scala:83)
  at org.apache.spark.sql.execution.ProjectExec.produce(basicPhysicalOperators.scala:35)
  at org.apache.spark.sql.execution.BaseLimitExec$class.doProduce(limit.scala:70)
  at org.apache.spark.sql.execution.LocalLimitExec.doProduce(limit.scala:97)
  at org.apache.spark.sql.execution.CodegenSupport$$anonfun$produce$1.apply(WholeStageCodegenExec.scala:88)
  at org.apache.spark.sql.execution.CodegenSupport$$anonfun$produce$1.apply(WholeStageCodegenExec.scala:83)
  at org.apache.spark.sql.execution.SparkPlan$$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.CodegenSupport$class.produce(WholeStageCodegenExec.scala:83)
  at org.apache.spark.sql.execution.LocalLimitExec.produce(limit.scala:97)
  at org.apache.spark.sql.execution.WholeStageCodegenExec.doCodeGen(WholeStageCodegenExec.scala:524)
  at org.apache.spark.sql.execution.WholeStageCodegenExec.doExecute(WholeStageCodegenExec.scala:576)
  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$$anonfun$executeQuery$1.apply(SparkPlan.scala:155)
  at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
  at org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:152)
  at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:127)
  at org.apache.spark.sql.execution.SparkPlan.getByteArrayRdd(SparkPlan.scala:247)
  at org.apache.spark.sql.execution.SparkPlan.executeTake(SparkPlan.scala:337)
  at org.apache.spark.sql.execution.CollectLimitExec.executeCollect(limit.scala:38)
  at org.apache.spark.sql.Dataset.org$apache$spark$sql$Dataset$$collectFromPlan(Dataset.scala:3272)
  at org.apache.spark.sql.Dataset$$anonfun$head$1.apply(Dataset.scala:2484)
  at org.apache.spark.sql.Dataset$$anonfun$head$1.apply(Dataset.scala:2484)
  at org.apache.spark.sql.Dataset$$anonfun$52.apply(Dataset.scala:3253)
  at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:77)
  at org.apache.spark.sql.Dataset.withAction(Dataset.scala:3252)
  at org.apache.spark.sql.Dataset.head(Dataset.scala:2484)
  at org.apache.spark.sql.Dataset.take(Dataset.scala:2698)
  at org.apache.spark.sql.Dataset.showString(Dataset.scala:254)
  at org.apache.spark.sql.Dataset.show(Dataset.scala:723)
  at org.apache.spark.sql.Dataset.show(Dataset.scala:682)
  at org.apache.spark.sql.Dataset.show(Dataset.scala:691)
  ... 53 elided

[Perados]

@djpirra and @lmerchante Magellan 1.0.5 is not compatible with Spark 2.3.1. You have to wait until the next release or compile from source, since the master branch is already compatible with Spark 2.3.1. I tested it last week and it works just fine.

[djpirra]

It does not work with full compatibility. I have compiled from master and was able to read the points and polygons, but it didn’t worked when I try to intersect them... Something is still not working right. Em qua, 19 de set de 2018 às 17:29, Diego Mora Cespedes < [email protected]> escreveu:

@djpirra <https://github.com/djpirra> and @lmerchante <https://github.com/lmerchante> Magellan 1.0.5 is not compatible with Spark 2.3.1. You have to wait until the next release or compile from source, since the master branch is already compatible with Spark 2.3.1. I tested it last week and it works just fine. — You are receiving this because you were mentioned. Reply to this email directly, view it on GitHub <#230 (comment)>, or mute the thread <https://github.com/notifications/unsubscribe-auth/APPYdgpqxlv5NItwjAlGo_OwHA873MSVks5uckbBgaJpZM4WXHgj> .

-- Melhores Cumprimentos, Luis Simões

[emartgu]

I have the same problem as @djpirra.

[Perados]

@djpirra I see a display there, I guess you are using Databricks, Zeppelin or something like that? Can you test the master branch on a traditional Spark shell for example?
I tested the master branch again today, all the main features work (read files, join points and polygons, etc...) in Spark 2.3.1. I am even planning on deploying it to production soon, we cannot wait for the official release. 🚀

Also, don't forget to run magellan.Utils.injectRules(spark) before anything else.

[agalst]

The same for me compiling the master branch and using it on Azure Databricks.

[maziyarpanahi]

Is this because of the way we compile the master or is there something in our notebooks that prevents the success? (Zeppelin 0.8.0)

Update: I just tested the with master branch and Spark 2.3.2 shell and the moment I get to points.join(polygons).where($"polygon" >? $"polygon").show() part of examples I get the same error:

scala> points.join(polygons).where($"polygon" >? $"polygon").show()
org.apache.spark.sql.AnalysisException: Detected implicit cartesian product for INNER join between logical plans
Project [pointconverter(_1#3, _2#4) AS point#10]
+- SerializeFromObject [assertnotnull(input[0, scala.Tuple2, true])._1 AS _1#3, assertnotnull(input[0, scala.Tuple2, true])._2 AS _2#4]
   +- ExternalRDD [obj#2]
and
Filter Within(polygon#19, polygon#19)
+- SerializeFromObject [newInstance(class org.apache.spark.sql.types.PolygonUDT).serialize AS polygon#19]
   +- ExternalRDD [obj#18]
Join condition is missing or trivial.
Either: use the CROSS JOIN syntax to allow cartesian products between these
relations, or: enable implicit cartesian products by setting the configuration
variable spark.sql.crossJoin.enabled=true;
...

I can see this variable spark.sql.crossJoin.enabled=true; is already set in the settings of this library, also I started my spark-shell with --conf spark.sql.crossJoin.enabled=true. Still the same error.

[jjcarbs]

I was able to get this working in a Databricks notebook environment using the 5.0 Runtime (Spark 2.4.0, Scala 2.11). You will need to change the sparkVersion in build.sbt to 2.4.0 from 2.3.1

[khajaasmath786]

I get the similar error. any resolutions please?

Stoping Spark Session Explicitly
Exception in thread "main" java.lang.NoSuchMethodError: org.apache.spark.sql.catalyst.expressions.codegen.CodegenContext.addMutableState(Ljava/lang/String;Ljava/lang/String;Ljava/lang/String;)V
at org.apache.spark.sql.types.WKT.doGenCode(WKT.scala:30)
at org.apache.spark.sql.catalyst.expressions.Expression$$anonfun$genCode$2.apply(Expression.scala:107)
at org.apache.spark.sql.catalyst.expressions.Expression$$anonfun$genCode$2.apply(Expression.scala:104)
at scala.Option.getOrElse(Option.scala:121)
at org.apache.spark.sql.catalyst.expressions.Expression.genCode(Expression.scala:104)
at org.apache.spark.sql.catalyst.expressions.UnaryExpression.nullSafeCodeGen(Expression.scala:406)
at org.apache.spark.sql.catalyst.expressions.GetStructField.doGenCode(complexTypeExtractors.scala:126)
at org.apache.spark.sql.catalyst.expressions.Expression$$anonfun$genCode$2.apply(Expression.scala:107)
at org.apache.spark.sql.catalyst.expressions.Expression$$anonfun$genCode$2.apply(Expression.scala:104)
at scala.Option.getOrElse(Option.scala:121)
at org.apache.spark.sql.catalyst.expressions.Expression.genCode(Expression.scala:104)
at org.apache.spark.sql.catalyst.expressions.Cast.doGenCode(Cast.scala:624)
at org.apache.spark.sql.catalyst.expressions.Expression$$anonfun$genCode$2.apply(Expression.scala:107)
at org.apache.spark.sql.catalyst.expressions.Expression$$anonfun$genCode$2.apply(Expression.scala:104)
at scala.Option.getOrElse(Option.scala:121)
at org.apache.spark.sql.catalyst.expressions.Expression.genCode(Expression.scala:104)
at org.apache.spark.sql.catalyst.expressions.Cast.genCode(Cast.scala:619)
at org.apache.spark.sql.catalyst.expressions.Alias.genCode(namedExpressions.scala:142)
at org.apache.spark.sql.execution.ProjectExec$$anonfun$6.apply(basicPhysicalOperators.scala:60)
at org.apache.spark.sql.execution.ProjectExec$$anonfun$6.apply(basicPhysicalOperators.scala:60)
at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)
at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)
at scala.collection.immutable.List.foreach(List.scala:381)
at scala.collection.TraversableLike$class.map(TraversableLike.scala:234)
at scala.collection.immutable.List.map(List.scala:285)
at org.apache.spark.sql.execution.ProjectExec.doConsume(basicPhysicalOperators.scala:60)
at org.apache.spark.sql.execution.CodegenSupport$class.consume(WholeStageCodegenExec.scala:181)
at org.apache.spark.sql.execution.FileSourceScanExec.consume(DataSourceScanExec.scala:158)
at org.apache.spark.sql.execution.ColumnarBatchScan$class.produceRows(ColumnarBatchScan.scala:166)
at org.apache.spark.sql.execution.ColumnarBatchScan$class.doProduce(ColumnarBatchScan.scala:80)
at org.apache.spark.sql.execution.FileSourceScanExec.doProduce(DataSourceScanExec.scala:158)
at org.apache.spark.sql.execution.CodegenSupport$$anonfun$produce$1.apply(WholeStageCodegenExec.scala:88)
at org.apache.spark.sql.execution.CodegenSupport$$anonfun$produce$1.apply(WholeStageCodegenExec.scala:83)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$executeQuery$1.apply(SparkPlan.scala:155)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:152)
at org.apache.spark.sql.execution.CodegenSupport$class.produce(WholeStageCodegenExec.scala:83)
at org.apache.spark.sql.execution.FileSourceScanExec.produce(DataSourceScanExec.scala:158)
at org.apache.spark.sql.execution.ProjectExec.doProduce(basicPhysicalOperators.scala:45)
at org.apache.spark.sql.execution.CodegenSupport$$anonfun$produce$1.apply(WholeStageCodegenExec.scala:88)
at org.apache.spark.sql.execution.CodegenSupport$$anonfun$produce$1.apply(WholeStageCodegenExec.scala:83)
at org.apache.spark.sql.execution.SparkPlan$$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.CodegenSupport$class.produce(WholeStageCodegenExec.scala:83)
at org.apache.spark.sql.execution.ProjectExec.produce(basicPhysicalOperators.scala:35)
at org.apache.spark.sql.execution.BaseLimitExec$class.doProduce(limit.scala:70)
at org.apache.spark.sql.execution.LocalLimitExec.doProduce(limit.scala:97)
at org.apache.spark.sql.execution.CodegenSupport$$anonfun$produce$1.apply(WholeStageCodegenExec.scala:88)
at org.apache.spark.sql.execution.CodegenSupport$$anonfun$produce$1.apply(WholeStageCodegenExec.scala:83)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$executeQuery$1.apply(SparkPlan.scala:155)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:152)
at org.apache.spark.sql.execution.CodegenSupport$class.produce(WholeStageCodegenExec.scala:83)
at org.apache.spark.sql.execution.LocalLimitExec.produce(limit.scala:97)
at org.apache.spark.sql.execution.WholeStageCodegenExec.doCodeGen(WholeStageCodegenExec.scala:524)
at org.apache.spark.sql.execution.WholeStageCodegenExec.doExecute(WholeStageCodegenExec.scala:576)
at org.apache.spark.sql.execution.SparkPlan$$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.SparkPlan.getByteArrayRdd(SparkPlan.scala:247)
at org.apache.spark.sql.execution.SparkPlan.executeTake(SparkPlan.scala:337)
at org.apache.spark.sql.execution.CollectLimitExec.executeCollect(limit.scala:38)
at org.apache.spark.sql.Dataset.org$apache$spark$sql$Dataset$$collectFromPlan(Dataset.scala:3272)
at org.apache.spark.sql.Dataset$$anonfun$head$1.apply(Dataset.scala:2484)
at org.apache.spark.sql.Dataset$$anonfun$head$1.apply(Dataset.scala:2484)
at org.apache.spark.sql.Dataset$$anonfun$52.apply(Dataset.scala:3253)
at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:77)
at org.apache.spark.sql.Dataset.withAction(Dataset.scala:3252)
at org.apache.spark.sql.Dataset.head(Dataset.scala:2484)
at org.apache.spark.sql.Dataset.take(Dataset.scala:2698)
at org.apache.spark.sql.Dataset.showString(Dataset.scala:254)
at org.apache.spark.sql.Dataset.show(Dataset.scala:723)
at org.apache.spark.sql.Dataset.show(Dataset.scala:682)
at com.navistar.telematics.datascience.drivers.GeoFenceNavDealersLocationDriver$.apply(GeoFenceNavDealerLocationDriver.scala:156)
at com.navistar.telematics.datascience.drivers.GeoFenceNavDealersLocationDriver$$anonfun$main$1.apply$mcV$sp(GeoFenceNavDealerLocationDriver.scala:99)
at com.navistar.telematics.datascience.drivers.GeoFenceNavDealersLocationDriver$$anonfun$main$1.apply(GeoFenceNavDealerLocationDriver.scala:99)
at com.navistar.telematics.datascience.drivers.GeoFenceNavDealersLocationDriver$$anonfun$main$1.apply(GeoFenceNavDealerLocationDriver.scala:99)
at scala.util.Try$.apply(Try.scala:192)
at com.navistar.telematics.utils.TimeTracker$.apply(TimeTracker.scala:12)
at com.navistar.telematics.datascience.drivers.GeoFenceNavDealersLocationDriver$.main(GeoFenceNavDealerLocationDriver.scala:99)
at com.navistar.telematics.datascience.drivers.GeoFenceNavDealersLocationDriver.main(GeoFenceNavDealerLocationDriver.scala)