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From Abdeali Kothari <abdealikoth...@gmail.com>
Subject Re: spark-sklearn
Date Tue, 09 Apr 2019 04:17:43 GMT
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 <sbpothineni@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 <javadba@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 <
> sbpothineni@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
>>
>>
>>

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