I haven't used spark-sklearn much, but their travis file gives the combination they test with: https://github.com/databricks/spark-sklearn/blob/master/.travis.yml#L8 Also, your first email is a bit confusing - you mentioned Spark 2.2.3 but the traceback path says spark-2.4.1-bin-hadoop2.6
I then tried with the same pip versions you mentioned (but I used python 3.6 and spark-2.4.1-bin-hadoop2.7 though) - and it still worked for me On Tue, Apr 9, 2019, 01:52 Sudhir Babu Pothineni <sbpothin...@gmail.com> wrote: > Thanks Stephen, saw that, but this is already released version of > spark-sklearn-0.3.0, tests should be working. > > So just checking if I am doing anything wrong, version of other libraries > etc.. > > Thanks > Sudhir > > On Apr 8, 2019, at 1:52 PM, Stephen Boesch <java...@gmail.com> wrote: > > There are several suggestions on this SOF > https://stackoverflow.com/questions/38984775/spark-errorexpected-zero-arguments-for-construction-of-classdict-for-numpy-cor > > 1 > > You need to convert the final value to a python list. You implement the > function as follows: > > def uniq_array(col_array): > x = np.unique(col_array) > return list(x) > > This is because Spark doesn't understand the numpy array format. In order > to feed a python object that Spark DataFrames understand as an ArrayType, > you need to convert the output to a python list before returning it. > > > > > The source of the problem is that object returned from the UDF doesn't > conform to the declared type. np.unique not only returns numpy.ndarray but > also converts numerics to the corresponding NumPy types which are not > compatible <https://issues.apache.org/jira/browse/SPARK-12157> with > DataFrame API. You can try something like this: > > udf(lambda x: list(set(x)), ArrayType(IntegerType())) > > or this (to keep order) > > udf(lambda xs: list(OrderedDict((x, None) for x in xs)), > ArrayType(IntegerType())) > > instead. > > If you really want np.unique you have to convert the output: > > udf(lambda x: np.unique(x).tolist(), ArrayType(IntegerType())) > > > > > > > > > > > > > > Am Mo., 8. Apr. 2019 um 11:43 Uhr schrieb Sudhir Babu Pothineni < > sbpothin...@gmail.com>: > >> >> >> >> 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 >> >> >>
