---------------------------------------------------------------------------
Py4JJavaError Traceback (most recent call last)
<ipython-input-70-2fb1fb90ca99> in <module>()
----> 1 p.select('matrix').head()
D:\workspace\hadoop\spark-2.2.0-bin-hadoop2.6\python\lib\pyspark.zip\pyspark\sql\dataframe.py in head(self, n)
968 """
969 if n is None:
--> 970 rs = self.head(1)
971 return rs[0] if rs else None
972 return self.take(n)
D:\workspace\hadoop\spark-2.2.0-bin-hadoop2.6\python\lib\pyspark.zip\pyspark\sql\dataframe.py in head(self, n)
970 rs = self.head(1)
971 return rs[0] if rs else None
--> 972 return self.take(n)
973
974 @ignore_unicode_prefix
D:\workspace\hadoop\spark-2.2.0-bin-hadoop2.6\python\lib\pyspark.zip\pyspark\sql\dataframe.py in take(self, num)
474 [Row(age=2, name=u'Alice'), Row(age=5, name=u'Bob')]
475 """
--> 476 return self.limit(num).collect()
477
478 @since(1.3)
D:\workspace\hadoop\spark-2.2.0-bin-hadoop2.6\python\lib\pyspark.zip\pyspark\sql\dataframe.py in collect(self)
436 """
437 with SCCallSiteSync(self._sc) as css:
--> 438 port = self._jdf.collectToPython()
439 return list(_load_from_socket(port, BatchedSerializer(PickleSerializer())))
440
D:\workspace\hadoop\spark-2.2.0-bin-hadoop2.6\python\lib\py4j-0.10.4-src.zip\py4j\java_gateway.py in __call__(self, *args)
1131 answer = self.gateway_client.send_command(command)
1132 return_value = get_return_value(
-> 1133 answer, self.gateway_client, self.target_id, self.name)
1134
1135 for temp_arg in temp_args:
D:\workspace\hadoop\spark-2.2.0-bin-hadoop2.6\python\lib\pyspark.zip\pyspark\sql\utils.py in deco(*a, **kw)
61 def deco(*a, **kw):
62 try:
---> 63 return f(*a, **kw)
64 except py4j.protocol.Py4JJavaError as e:
65 s = e.java_exception.toString()
D:\workspace\hadoop\spark-2.2.0-bin-hadoop2.6\python\lib\py4j-0.10.4-src.zip\py4j\protocol.py in get_return_value(answer, gateway_client, target_id, name)
317 raise Py4JJavaError(
318 "An error occurred while calling {0}{1}{2}.\n".
--> 319 format(target_id, ".", name), value)
320 else:
321 raise Py4JError(
Py4JJavaError: An error occurred while calling o5231.collectToPython.
: org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 75.0 failed 1 times, most recent failure: Lost task 0.0 in stage 75.0 (TID 938, localhost, executor driver): org.apache.spark.api.python.PythonException: Traceback (most recent call last):
File "D:\workspace\hadoop\spark-2.2.0-bin-hadoop2.6\python\lib\pyspark.zip\pyspark\worker.py", line 177, in main
File "D:\workspace\hadoop\spark-2.2.0-bin-hadoop2.6\python\lib\pyspark.zip\pyspark\worker.py", line 172, in process
File "D:\workspace\hadoop\spark-2.2.0-bin-hadoop2.6\python\lib\pyspark.zip\pyspark\serializers.py", line 268, in dump_stream
vs = list(itertools.islice(iterator, batch))
File "D:\workspace\hadoop\spark-2.2.0-bin-hadoop2.6\python\lib\pyspark.zip\pyspark\sql\types.py", line 576, in toInternal
return tuple(f.toInternal(v) for f, v in zip(self.fields, obj))
File "D:\workspace\hadoop\spark-2.2.0-bin-hadoop2.6\python\lib\pyspark.zip\pyspark\sql\types.py", line 576, in <genexpr>
return tuple(f.toInternal(v) for f, v in zip(self.fields, obj))
File "D:\workspace\hadoop\spark-2.2.0-bin-hadoop2.6\python\lib\pyspark.zip\pyspark\sql\types.py", line 436, in toInternal
return self.dataType.toInternal(obj)
File "D:\workspace\hadoop\spark-2.2.0-bin-hadoop2.6\python\lib\pyspark.zip\pyspark\sql\types.py", line 654, in toInternal
return self._cachedSqlType().toInternal(self.serialize(obj))
File "D:\workspace\hadoop\spark-2.2.0-bin-hadoop2.6\python\lib\pyspark.zip\pyspark\mllib\linalg\__init__.py", line 166, in serialize
values = [float(v) for v in obj]
File "D:\workspace\hadoop\spark-2.2.0-bin-hadoop2.6\python\lib\pyspark.zip\pyspark\mllib\linalg\__init__.py", line 166, in <listcomp>
values = [float(v) for v in obj]
TypeError: only size-1 arrays can be converted to Python scalars
at org.apache.spark.api.python.PythonRunner$$anon$1.read(PythonRDD.scala:193)
at org.apache.spark.api.python.PythonRunner$$anon$1.<init>(PythonRDD.scala:234)
at org.apache.spark.api.python.PythonRunner.compute(PythonRDD.scala:152)
at org.apache.spark.api.python.PythonRDD.compute(PythonRDD.scala:63)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87)
at org.apache.spark.scheduler.Task.run(Task.scala:108)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:335)
at java.util.concurrent.ThreadPoolExecutor.runWorker(Unknown Source)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(Unknown Source)
at java.lang.Thread.run(Unknown Source)
Driver stacktrace:
at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1499)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1487)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1486)
at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48)
at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1486)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:814)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:814)
at scala.Option.foreach(Option.scala:257)
at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:814)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:1714)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1669)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1658)
at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48)
at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:630)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2022)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2043)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2062)
at org.apache.spark.sql.execution.SparkPlan.executeTake(SparkPlan.scala:336)
at org.apache.spark.sql.execution.CollectLimitExec.executeCollect(limit.scala:38)
at org.apache.spark.sql.Dataset$$anonfun$collectToPython$1.apply$mcI$sp(Dataset.scala:2803)
at org.apache.spark.sql.Dataset$$anonfun$collectToPython$1.apply(Dataset.scala:2800)
at org.apache.spark.sql.Dataset$$anonfun$collectToPython$1.apply(Dataset.scala:2800)
at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:65)
at org.apache.spark.sql.Dataset.withNewExecutionId(Dataset.scala:2823)
at org.apache.spark.sql.Dataset.collectToPython(Dataset.scala:2800)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(Unknown Source)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(Unknown Source)
at java.lang.reflect.Method.invoke(Unknown Source)
at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244)
at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357)
at py4j.Gateway.invoke(Gateway.java:280)
at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132)
at py4j.commands.CallCommand.execute(CallCommand.java:79)
at py4j.GatewayConnection.run(GatewayConnection.java:214)
at java.lang.Thread.run(Unknown Source)
Caused by: org.apache.spark.api.python.PythonException: Traceback (most recent call last):
File "D:\workspace\hadoop\spark-2.2.0-bin-hadoop2.6\python\lib\pyspark.zip\pyspark\worker.py", line 177, in main
File "D:\workspace\hadoop\spark-2.2.0-bin-hadoop2.6\python\lib\pyspark.zip\pyspark\worker.py", line 172, in process
File "D:\workspace\hadoop\spark-2.2.0-bin-hadoop2.6\python\lib\pyspark.zip\pyspark\serializers.py", line 268, in dump_stream
vs = list(itertools.islice(iterator, batch))
File "D:\workspace\hadoop\spark-2.2.0-bin-hadoop2.6\python\lib\pyspark.zip\pyspark\sql\types.py", line 576, in toInternal
return tuple(f.toInternal(v) for f, v in zip(self.fields, obj))
File "D:\workspace\hadoop\spark-2.2.0-bin-hadoop2.6\python\lib\pyspark.zip\pyspark\sql\types.py", line 576, in <genexpr>
return tuple(f.toInternal(v) for f, v in zip(self.fields, obj))
File "D:\workspace\hadoop\spark-2.2.0-bin-hadoop2.6\python\lib\pyspark.zip\pyspark\sql\types.py", line 436, in toInternal
return self.dataType.toInternal(obj)
File "D:\workspace\hadoop\spark-2.2.0-bin-hadoop2.6\python\lib\pyspark.zip\pyspark\sql\types.py", line 654, in toInternal
return self._cachedSqlType().toInternal(self.serialize(obj))
File "D:\workspace\hadoop\spark-2.2.0-bin-hadoop2.6\python\lib\pyspark.zip\pyspark\mllib\linalg\__init__.py", line 166, in serialize
values = [float(v) for v in obj]
File "D:\workspace\hadoop\spark-2.2.0-bin-hadoop2.6\python\lib\pyspark.zip\pyspark\mllib\linalg\__init__.py", line 166, in <listcomp>
values = [float(v) for v in obj]
TypeError: only size-1 arrays can be converted to Python scalars
at org.apache.spark.api.python.PythonRunner$$anon$1.read(PythonRDD.scala:193)
at org.apache.spark.api.python.PythonRunner$$anon$1.<init>(PythonRDD.scala:234)
at org.apache.spark.api.python.PythonRunner.compute(PythonRDD.scala:152)
at org.apache.spark.api.python.PythonRDD.compute(PythonRDD.scala:63)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87)
at org.apache.spark.scheduler.Task.run(Task.scala:108)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:335)
at java.util.concurrent.ThreadPoolExecutor.runWorker(Unknown Source)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(Unknown Source)
... 1 more
I am implementing an LSTM autoencoder to reconstruct a multi-features sequence
The columns of my dataframe are: 0_F1, 0_F2, 0_F3, 0_F4, 0_F5, 1_F1, 1_F2, 1_F3, 1_F4, 1_F5, 2_F1, 2_F2, 2_F3, 2_F4, 2_F5
Each row if a sequence of 5 features within 3 timesteps
Here is my code
I get this error when trying to predict