>
> Trying to run tests in spark-sklearn, anybody check the below exception
>
> pip freeze:
>
> nose==1.3.7
> numpy==1.16.1
> pandas==0.19.2
> python-dateutil==2.7.5
> pytz==2018.9
> scikit-learn==0.19.2
> scipy==1.2.0
> six==1.12.0
> spark-sklearn==0.3.0
>
> Spark version:
> spark-2.2.3-bin-hadoop2.6/bin/pyspark
>
>
> running into following exception:
>
> ======================================================================
> ERROR: test_scipy_sparse (spark_sklearn.converter_test.CSRVectorUDTTests)
> ----------------------------------------------------------------------
> Traceback (most recent call last):
> File
> "/home/spothineni/Downloads/spark-sklearn-release-0.3.0/python/spark_sklearn/converter_test.py",
> line 83, in test_scipy_sparse
> self.assertEqual(df.count(), 1)
> File
> "/home/spothineni/Downloads/spark-2.4.1-bin-hadoop2.6/python/pyspark/sql/dataframe.py",
> line 522, in count
> return int(self._jdf.count())
> File
> "/home/spothineni/Downloads/spark-2.4.1-bin-hadoop2.6/python/lib/py4j-0.10.7-src.zip/py4j/java_gateway.py",
> line 1257, in __call__
> answer, self.gateway_client, self.target_id, self.name)
> File
> "/home/spothineni/Downloads/spark-2.4.1-bin-hadoop2.6/python/pyspark/sql/utils.py",
> line 63, in deco
> return f(*a, **kw)
> File
> "/home/spothineni/Downloads/spark-2.4.1-bin-hadoop2.6/python/lib/py4j-0.10.7-src.zip/py4j/protocol.py",
> line 328, in get_return_value
> format(target_id, ".", name), value)
> Py4JJavaError: An error occurred while calling o652.count.
> : org.apache.spark.SparkException: Job aborted due to stage failure: Task 11
> in stage 0.0 failed 1 times, most recent failure: Lost task 11.0 in stage 0.0
> (TID 11, localhost, executor driver): net.razorvine.pickle.PickleException:
> expected zero arguments for construction of ClassDict (for numpy.dtype)
> at
> net.razorvine.pickle.objects.ClassDictConstructor.construct(ClassDictConstructor.java:23)
> at net.razorvine.pickle.Unpickler.load_reduce(Unpickler.java:707)
> at net.razorvine.pickle.Unpickler.dispatch(Unpickler.java:175)
> at net.razorvine.pickle.Unpickler.load(Unpickler.java:99)
> at net.razorvine.pickle.Unpickler.loads(Unpickler.java:112)
> at
> org.apache.spark.api.python.SerDeUtil$$anonfun$pythonToJava$1$$anonfun$apply$1.apply(SerDeUtil.scala:188)
> at
> org.apache.spark.api.python.SerDeUtil$$anonfun$pythonToJava$1$$anonfun$apply$1.apply(SerDeUtil.scala:187)
> at scala.collection.Iterator$$anon$12.nextCur(Iterator.scala:435)
> at scala.collection.Iterator$$anon$12.hasNext(Iterator.scala:441)
> at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:409)
> at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:409)
> at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:409)
> at
> org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.agg_doAggregateWithoutKey_0$(Unknown
> Source)
> at
> org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.processNext(Unknown
> Source)
> at
> org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
> at
> org.apache.spark.sql.execution.WholeStageCodegenExec$$anonfun$13$$anon$1.hasNext(WholeStageCodegenExec.scala:636)
> at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:409)
> at
> org.apache.spark.shuffle.sort.BypassMergeSortShuffleWriter.write(BypassMergeSortShuffleWriter.java:125)
> at
> org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:99)
> at
> org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:55)
> at org.apache.spark.scheduler.Task.run(Task.scala:121)
> at
> org.apache.spark.executor.Executor$TaskRunner$$anonfun$10.apply(Executor.scala:403)
> at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1360)
> at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:409)
> at
> java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
> at
> java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
> at java.lang.Thread.run(Thread.java:745)
>
> Driver stacktrace:
> at
> org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1889)
> at
> org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1877)
> at
> org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1876)
> at
> scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
> at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48)
> at
> org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1876)
> at
> org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:926)
> at
> org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:926)
> at scala.Option.foreach(Option.scala:257)
> at
> org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:926)
> at
> org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:2110)
> at
> org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2059)
> at
> org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2048)
> at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:49)
> at
> org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:737)
> at org.apache.spark.SparkContext.runJob(SparkContext.scala:2061)
> at org.apache.spark.SparkContext.runJob(SparkContext.scala:2082)
> at org.apache.spark.SparkContext.runJob(SparkContext.scala:2101)
> at org.apache.spark.SparkContext.runJob(SparkContext.scala:2126)
> at org.apache.spark.rdd.RDD$$anonfun$collect$1.apply(RDD.scala:945)
> at
> org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
> at
> org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112)
> at org.apache.spark.rdd.RDD.withScope(RDD.scala:363)
> at org.apache.spark.rdd.RDD.collect(RDD.scala:944)
> at
> org.apache.spark.sql.execution.SparkPlan.executeCollect(SparkPlan.scala:299)
> at
> org.apache.spark.sql.Dataset$$anonfun$count$1.apply(Dataset.scala:2830)
> at
> org.apache.spark.sql.Dataset$$anonfun$count$1.apply(Dataset.scala:2829)
> at org.apache.spark.sql.Dataset$$anonfun$53.apply(Dataset.scala:3364)
> at
> org.apache.spark.sql.execution.SQLExecution$$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.Dataset.withAction(Dataset.scala:3363)
> at org.apache.spark.sql.Dataset.count(Dataset.scala:2829)
> 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:498)
> at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244)
> at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357)
> at py4j.Gateway.invoke(Gateway.java:282)
> at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132)
> at py4j.commands.CallCommand.execute(CallCommand.java:79)
> at py4j.GatewayConnection.run(GatewayConnection.java:238)
> at java.lang.Thread.run(Thread.java:745)
> Caused by: net.razorvine.pickle.PickleException: expected zero arguments for
> construction of ClassDict (for numpy.dtype)
> at
> net.razorvine.pickle.objects.ClassDictConstructor.construct(ClassDictConstructor.java:23)
> at net.razorvine.pickle.Unpickler.load_reduce(Unpickler.java:707)
> at net.razorvine.pickle.Unpickler.dispatch(Unpickler.java:175)
> at net.razorvine.pickle.Unpickler.load(Unpickler.java:99)
> at net.razorvine.pickle.Unpickler.loads(Unpickler.java:112)
> at
> org.apache.spark.api.python.SerDeUtil$$anonfun$pythonToJava$1$$anonfun$apply$1.apply(SerDeUtil.scala:188)
> at
> org.apache.spark.api.python.SerDeUtil$$anonfun$pythonToJava$1$$anonfun$apply$1.apply(SerDeUtil.scala:187)
> at scala.collection.Iterator$$anon$12.nextCur(Iterator.scala:435)
> at scala.collection.Iterator$$anon$12.hasNext(Iterator.scala:441)
> at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:409)
> at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:409)
> at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:409)
> at
> org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.agg_doAggregateWithoutKey_0$(Unknown
> Source)
> at
> org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.processNext(Unknown
> Source)
> at
> org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
> at
> org.apache.spark.sql.execution.WholeStageCodegenExec$$anonfun$13$$anon$1.hasNext(WholeStageCodegenExec.scala:636)
> at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:409)
> at
> org.apache.spark.shuffle.sort.BypassMergeSortShuffleWriter.write(BypassMergeSortShuffleWriter.java:125)
> at
> org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:99)
> at
> org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:55)
> at org.apache.spark.scheduler.Task.run(Task.scala:121)
> at
> org.apache.spark.executor.Executor$TaskRunner$$anonfun$10.apply(Executor.scala:403)
> at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1360)
> at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:409)
> at
> java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
> at
> java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
> ... 1 more
>
>
