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Missing embedding results #86

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daralthus opened this issue Nov 15, 2021 · 3 comments
Open

Missing embedding results #86

daralthus opened this issue Nov 15, 2021 · 3 comments

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@daralthus
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daralthus commented Nov 15, 2021 •
edited

Hello,

It seems like embeddings are not returned when running any of the embedding predictions. Sentiment and other models do return results fine though.

Any ideas what could I be missing here?

image

nlu 3.3.0
pyspark 3.0.2
py4j 0.10.9
spark-nlp 3.3.2
running on google colab
@ahmedlone127
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Hey because of the new update you have to add get_embeddings=True to predict to get the embeddings :)

@C-K-Loan
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Hi yes exactly thanks for answering the questions @ahmedlone127

@daralthus
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Thanks, I just tried this and facing a bit of an issue.

I am adding a stack trace that I got on colabs after running:

!pip install faiss-gpu nlu pyspark==3.0.1

import nlu
nlu.load('elmo').predict("elmo was trained",  get_embeddings=True)

Traceback (most recent call last):
  File "/usr/local/lib/python3.7/dist-packages/nlu/pipe/utils/predict_helper.py", line 103, in predict_help
    drop_irrelevant_cols, return_spark_df,get_embeddings)
  File "/usr/local/lib/python3.7/dist-packages/nlu/pipe/utils/predict_helper.py", line 24, in __predict_standard_spark
    output_level=output_level,
  File "/usr/local/lib/python3.7/dist-packages/nlu/pipe/pipeline.py", line 374, in pythonify_spark_dataframe
    anno_2_ex_config,self.light_pipe_configured, get_embeddings)
  File "/usr/local/lib/python3.7/dist-packages/nlu/pipe/pipeline.py", line 325, in unpack_and_apply_extractors
    return apply_extractors_and_merge(pdf.toPandas().applymap(extract_pyspark_rows), anno_2_ex_config,
  File "/usr/local/lib/python3.7/dist-packages/pyspark/sql/pandas/conversion.py", line 138, in toPandas
    pdf = pd.DataFrame.from_records(self.collect(), columns=self.columns)
  File "/usr/local/lib/python3.7/dist-packages/pyspark/sql/dataframe.py", line 596, in collect
    sock_info = self._jdf.collectToPython()
  File "/usr/local/lib/python3.7/dist-packages/py4j/java_gateway.py", line 1305, in __call__
    answer, self.gateway_client, self.target_id, self.name)
  File "/usr/local/lib/python3.7/dist-packages/pyspark/sql/utils.py", line 128, in deco
    return f(*a, **kw)
  File "/usr/local/lib/python3.7/dist-packages/py4j/protocol.py", line 328, in get_return_value
    format(target_id, ".", name), value)
py4j.protocol.Py4JJavaError: An error occurred while calling o461.collectToPython.
: org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 2.0 failed 1 times, most recent failure: Lost task 0.0 in stage 2.0 (TID 2, a4de18ad4510, executor driver): java.lang.UnsupportedOperationException: sun.misc.Unsafe or java.nio.DirectByteBuffer.<init>(long, int) not available
	at io.netty.util.internal.PlatformDependent.directBuffer(PlatformDependent.java:490)
	at io.netty.buffer.NettyArrowBuf.getDirectBuffer(NettyArrowBuf.java:243)
	at io.netty.buffer.NettyArrowBuf.nioBuffer(NettyArrowBuf.java:233)
	at io.netty.buffer.ArrowBuf.nioBuffer(ArrowBuf.java:245)
	at org.apache.arrow.vector.ipc.ReadChannel.readFully(ReadChannel.java:81)
	at org.apache.arrow.vector.ipc.message.MessageSerializer.readMessageBody(MessageSerializer.java:696)
	at org.apache.arrow.vector.ipc.message.MessageSerializer.deserializeRecordBatch(MessageSerializer.java:344)
	at org.apache.spark.sql.execution.arrow.ArrowConverters$.loadBatch(ArrowConverters.scala:189)
	at org.apache.spark.sql.execution.arrow.ArrowConverters$$anon$2.nextBatch(ArrowConverters.scala:165)
	at org.apache.spark.sql.execution.arrow.ArrowConverters$$anon$2.<init>(ArrowConverters.scala:144)
	at org.apache.spark.sql.execution.arrow.ArrowConverters$.fromBatchIterator(ArrowConverters.scala:143)
	at org.apache.spark.sql.execution.arrow.ArrowConverters$.$anonfun$toDataFrame$1(ArrowConverters.scala:203)
	at org.apache.spark.rdd.RDD.$anonfun$mapPartitions$2(RDD.scala:837)
	at org.apache.spark.rdd.RDD.$anonfun$mapPartitions$2$adapted(RDD.scala:837)
	at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
	at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:349)
	at org.apache.spark.rdd.RDD.iterator(RDD.scala:313)
	at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
	at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:349)
	at org.apache.spark.rdd.RDD.iterator(RDD.scala:313)
	at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
	at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:349)
	at org.apache.spark.rdd.RDD.iterator(RDD.scala:313)
	at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)
	at org.apache.spark.scheduler.Task.run(Task.scala:127)
	at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:446)
	at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1377)
	at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:449)
	at java.base/java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1128)
	at java.base/java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:628)
	at java.base/java.lang.Thread.run(Thread.java:829)

Driver stacktrace:
	at org.apache.spark.scheduler.DAGScheduler.failJobAndIndependentStages(DAGScheduler.scala:2059)
	at org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2(DAGScheduler.scala:2008)
	at org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2$adapted(DAGScheduler.scala:2007)
	at scala.collection.mutable.ResizableArray.foreach(ResizableArray.scala:62)
	at scala.collection.mutable.ResizableArray.foreach$(ResizableArray.scala:55)
	at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:49)
	at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:2007)
	at org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1(DAGScheduler.scala:973)
	at org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1$adapted(DAGScheduler.scala:973)
	at scala.Option.foreach(Option.scala:407)
	at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:973)
	at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:2239)
	at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2188)
	at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2177)
	at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:49)
	at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:775)
	at org.apache.spark.SparkContext.runJob(SparkContext.scala:2099)
	at org.apache.spark.SparkContext.runJob(SparkContext.scala:2120)
	at org.apache.spark.SparkContext.runJob(SparkContext.scala:2139)
	at org.apache.spark.SparkContext.runJob(SparkContext.scala:2164)
	at org.apache.spark.rdd.RDD.$anonfun$collect$1(RDD.scala:1004)
	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:388)
	at org.apache.spark.rdd.RDD.collect(RDD.scala:1003)
	at org.apache.spark.sql.execution.SparkPlan.executeCollect(SparkPlan.scala:385)
	at org.apache.spark.sql.Dataset.$anonfun$collectToPython$1(Dataset.scala:3450)
	at org.apache.spark.sql.Dataset.$anonfun$withAction$1(Dataset.scala:3618)
	at org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$5(SQLExecution.scala:100)
	at org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:160)
	at org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$1(SQLExecution.scala:87)
	at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:764)
	at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:64)
	at org.apache.spark.sql.Dataset.withAction(Dataset.scala:3616)
	at org.apache.spark.sql.Dataset.collectToPython(Dataset.scala:3447)
	at java.base/jdk.internal.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
	at java.base/jdk.internal.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
	at java.base/jdk.internal.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
	at java.base/java.lang.reflect.Method.invoke(Method.java:566)
	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.base/java.lang.Thread.run(Thread.java:829)
Caused by: java.lang.UnsupportedOperationException: sun.misc.Unsafe or java.nio.DirectByteBuffer.<init>(long, int) not available
	at io.netty.util.internal.PlatformDependent.directBuffer(PlatformDependent.java:490)
	at io.netty.buffer.NettyArrowBuf.getDirectBuffer(NettyArrowBuf.java:243)
	at io.netty.buffer.NettyArrowBuf.nioBuffer(NettyArrowBuf.java:233)
	at io.netty.buffer.ArrowBuf.nioBuffer(ArrowBuf.java:245)
	at org.apache.arrow.vector.ipc.ReadChannel.readFully(ReadChannel.java:81)
	at org.apache.arrow.vector.ipc.message.MessageSerializer.readMessageBody(MessageSerializer.java:696)
	at org.apache.arrow.vector.ipc.message.MessageSerializer.deserializeRecordBatch(MessageSerializer.java:344)
	at org.apache.spark.sql.execution.arrow.ArrowConverters$.loadBatch(ArrowConverters.scala:189)
	at org.apache.spark.sql.execution.arrow.ArrowConverters$$anon$2.nextBatch(ArrowConverters.scala:165)
	at org.apache.spark.sql.execution.arrow.ArrowConverters$$anon$2.<init>(ArrowConverters.scala:144)
	at org.apache.spark.sql.execution.arrow.ArrowConverters$.fromBatchIterator(ArrowConverters.scala:143)
	at org.apache.spark.sql.execution.arrow.ArrowConverters$.$anonfun$toDataFrame$1(ArrowConverters.scala:203)
	at org.apache.spark.rdd.RDD.$anonfun$mapPartitions$2(RDD.scala:837)
	at org.apache.spark.rdd.RDD.$anonfun$mapPartitions$2$adapted(RDD.scala:837)
	at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
	at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:349)
	at org.apache.spark.rdd.RDD.iterator(RDD.scala:313)
	at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
	at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:349)
	at org.apache.spark.rdd.RDD.iterator(RDD.scala:313)
	at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
	at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:349)
	at org.apache.spark.rdd.RDD.iterator(RDD.scala:313)
	at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)
	at org.apache.spark.scheduler.Task.run(Task.scala:127)
	at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:446)
	at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1377)
	at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:449)
	at java.base/java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1128)
	at java.base/java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:628)
	... 1 more

No accepted Data type or usable columns found or applying the NLU models failed. 
Make sure that the first column you pass to .predict() is the one that nlu should predict on OR rename the column you want to predict on to 'text'  
On try to reset restart Jupyter session and run the setup script again, you might have used too much memory
Full Stacktrace was (<class 'py4j.protocol.Py4JJavaError'>, Py4JJavaError('An error occurred while calling o461.collectToPython.\n', JavaObject id=o469), <traceback object at 0x7f17c491c7d0>)
Additional info:
<class 'py4j.protocol.Py4JJavaError'> predict_helper.py 103
An error occurred while calling o461.collectToPython.
: org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 2.0 failed 1 times, most recent failure: Lost task 0.0 in stage 2.0 (TID 2, a4de18ad4510, executor driver): java.lang.UnsupportedOperationException: sun.misc.Unsafe or java.nio.DirectByteBuffer.<init>(long, int) not available
	at io.netty.util.internal.PlatformDependent.directBuffer(PlatformDependent.java:490)
	at io.netty.buffer.NettyArrowBuf.getDirectBuffer(NettyArrowBuf.java:243)
	at io.netty.buffer.NettyArrowBuf.nioBuffer(NettyArrowBuf.java:233)
	at io.netty.buffer.ArrowBuf.nioBuffer(ArrowBuf.java:245)
	at org.apache.arrow.vector.ipc.ReadChannel.readFully(ReadChannel.java:81)
	at org.apache.arrow.vector.ipc.message.MessageSerializer.readMessageBody(MessageSerializer.java:696)
	at org.apache.arrow.vector.ipc.message.MessageSerializer.deserializeRecordBatch(MessageSerializer.java:344)
	at org.apache.spark.sql.execution.arrow.ArrowConverters$.loadBatch(ArrowConverters.scala:189)
	at org.apache.spark.sql.execution.arrow.ArrowConverters$$anon$2.nextBatch(ArrowConverters.scala:165)
	at org.apache.spark.sql.execution.arrow.ArrowConverters$$anon$2.<init>(ArrowConverters.scala:144)
	at org.apache.spark.sql.execution.arrow.ArrowConverters$.fromBatchIterator(ArrowConverters.scala:143)
	at org.apache.spark.sql.execution.arrow.ArrowConverters$.$anonfun$toDataFrame$1(ArrowConverters.scala:203)
	at org.apache.spark.rdd.RDD.$anonfun$mapPartitions$2(RDD.scala:837)
	at org.apache.spark.rdd.RDD.$anonfun$mapPartitions$2$adapted(RDD.scala:837)
	at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
	at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:349)
	at org.apache.spark.rdd.RDD.iterator(RDD.scala:313)
	at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
	at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:349)
	at org.apache.spark.rdd.RDD.iterator(RDD.scala:313)
	at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
	at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:349)
	at org.apache.spark.rdd.RDD.iterator(RDD.scala:313)
	at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)
	at org.apache.spark.scheduler.Task.run(Task.scala:127)
	at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:446)
	at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1377)
	at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:449)
	at java.base/java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1128)
	at java.base/java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:628)
	at java.base/java.lang.Thread.run(Thread.java:829)

Driver stacktrace:
	at org.apache.spark.scheduler.DAGScheduler.failJobAndIndependentStages(DAGScheduler.scala:2059)
	at org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2(DAGScheduler.scala:2008)
	at org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2$adapted(DAGScheduler.scala:2007)
	at scala.collection.mutable.ResizableArray.foreach(ResizableArray.scala:62)
	at scala.collection.mutable.ResizableArray.foreach$(ResizableArray.scala:55)
	at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:49)
	at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:2007)
	at org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1(DAGScheduler.scala:973)
	at org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1$adapted(DAGScheduler.scala:973)
	at scala.Option.foreach(Option.scala:407)
	at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:973)
	at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:2239)
	at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2188)
	at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2177)
	at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:49)
	at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:775)
	at org.apache.spark.SparkContext.runJob(SparkContext.scala:2099)
	at org.apache.spark.SparkContext.runJob(SparkContext.scala:2120)
	at org.apache.spark.SparkContext.runJob(SparkContext.scala:2139)
	at org.apache.spark.SparkContext.runJob(SparkContext.scala:2164)
	at org.apache.spark.rdd.RDD.$anonfun$collect$1(RDD.scala:1004)
	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:388)
	at org.apache.spark.rdd.RDD.collect(RDD.scala:1003)
	at org.apache.spark.sql.execution.SparkPlan.executeCollect(SparkPlan.scala:385)
	at org.apache.spark.sql.Dataset.$anonfun$collectToPython$1(Dataset.scala:3450)
	at org.apache.spark.sql.Dataset.$anonfun$withAction$1(Dataset.scala:3618)
	at org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$5(SQLExecution.scala:100)
	at org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:160)
	at org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$1(SQLExecution.scala:87)
	at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:764)
	at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:64)
	at org.apache.spark.sql.Dataset.withAction(Dataset.scala:3616)
	at org.apache.spark.sql.Dataset.collectToPython(Dataset.scala:3447)
	at java.base/jdk.internal.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
	at java.base/jdk.internal.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
	at java.base/jdk.internal.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
	at java.base/java.lang.reflect.Method.invoke(Method.java:566)
	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.base/java.lang.Thread.run(Thread.java:829)
Caused by: java.lang.UnsupportedOperationException: sun.misc.Unsafe or java.nio.DirectByteBuffer.<init>(long, int) not available
	at io.netty.util.internal.PlatformDependent.directBuffer(PlatformDependent.java:490)
	at io.netty.buffer.NettyArrowBuf.getDirectBuffer(NettyArrowBuf.java:243)
	at io.netty.buffer.NettyArrowBuf.nioBuffer(NettyArrowBuf.java:233)
	at io.netty.buffer.ArrowBuf.nioBuffer(ArrowBuf.java:245)
	at org.apache.arrow.vector.ipc.ReadChannel.readFully(ReadChannel.java:81)
	at org.apache.arrow.vector.ipc.message.MessageSerializer.readMessageBody(MessageSerializer.java:696)
	at org.apache.arrow.vector.ipc.message.MessageSerializer.deserializeRecordBatch(MessageSerializer.java:344)
	at org.apache.spark.sql.execution.arrow.ArrowConverters$.loadBatch(ArrowConverters.scala:189)
	at org.apache.spark.sql.execution.arrow.ArrowConverters$$anon$2.nextBatch(ArrowConverters.scala:165)
	at org.apache.spark.sql.execution.arrow.ArrowConverters$$anon$2.<init>(ArrowConverters.scala:144)
	at org.apache.spark.sql.execution.arrow.ArrowConverters$.fromBatchIterator(ArrowConverters.scala:143)
	at org.apache.spark.sql.execution.arrow.ArrowConverters$.$anonfun$toDataFrame$1(ArrowConverters.scala:203)
	at org.apache.spark.rdd.RDD.$anonfun$mapPartitions$2(RDD.scala:837)
	at org.apache.spark.rdd.RDD.$anonfun$mapPartitions$2$adapted(RDD.scala:837)
	at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
	at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:349)
	at org.apache.spark.rdd.RDD.iterator(RDD.scala:313)
	at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
	at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:349)
	at org.apache.spark.rdd.RDD.iterator(RDD.scala:313)
	at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
	at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:349)
	at org.apache.spark.rdd.RDD.iterator(RDD.scala:313)
	at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)
	at org.apache.spark.scheduler.Task.run(Task.scala:127)
	at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:446)
	at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1377)
	at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:449)
	at java.base/java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1128)
	at java.base/java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:628)
	... 1 more

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---------------------------------------------------------------------------
Py4JJavaError                             Traceback (most recent call last)
/usr/local/lib/python3.7/dist-packages/nlu/pipe/utils/predict_helper.py in predict_help(pipe, data, output_level, positions, keep_stranger_features, metadata, multithread, drop_irrelevant_cols, return_spark_df, get_embeddings)
    102             return __predict_standard_spark(pipe, data, output_level, positions, keep_stranger_features, metadata,
--> 103                                             drop_irrelevant_cols, return_spark_df,get_embeddings)
    104         except Exception as err:

10 frames
Py4JJavaError: An error occurred while calling o461.collectToPython.
: org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 2.0 failed 1 times, most recent failure: Lost task 0.0 in stage 2.0 (TID 2, a4de18ad4510, executor driver): java.lang.UnsupportedOperationException: sun.misc.Unsafe or java.nio.DirectByteBuffer.<init>(long, int) not available
	at io.netty.util.internal.PlatformDependent.directBuffer(PlatformDependent.java:490)
	at io.netty.buffer.NettyArrowBuf.getDirectBuffer(NettyArrowBuf.java:243)
	at io.netty.buffer.NettyArrowBuf.nioBuffer(NettyArrowBuf.java:233)
	at io.netty.buffer.ArrowBuf.nioBuffer(ArrowBuf.java:245)
	at org.apache.arrow.vector.ipc.ReadChannel.readFully(ReadChannel.java:81)
	at org.apache.arrow.vector.ipc.message.MessageSerializer.readMessageBody(MessageSerializer.java:696)
	at org.apache.arrow.vector.ipc.message.MessageSerializer.deserializeRecordBatch(MessageSerializer.java:344)
	at org.apache.spark.sql.execution.arrow.ArrowConverters$.loadBatch(ArrowConverters.scala:189)
	at org.apache.spark.sql.execution.arrow.ArrowConverters$$anon$2.nextBatch(ArrowConverters.scala:165)
	at org.apache.spark.sql.execution.arrow.ArrowConverters$$anon$2.<init>(ArrowConverters.scala:144)
	at org.apache.spark.sql.execution.arrow.ArrowConverters$.fromBatchIterator(ArrowConverters.scala:143)
	at org.apache.spark.sql.execution.arrow.ArrowConverters$.$anonfun$toDataFrame$1(ArrowConverters.scala:203)
	at org.apache.spark.rdd.RDD.$anonfun$mapPartitions$2(RDD.scala:837)
	at org.apache.spark.rdd.RDD.$anonfun$mapPartitions$2$adapted(RDD.scala:837)
	at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
	at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:349)
	at org.apache.spark.rdd.RDD.iterator(RDD.scala:313)
	at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
	at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:349)
	at org.apache.spark.rdd.RDD.iterator(RDD.scala:313)
	at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
	at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:349)
	at org.apache.spark.rdd.RDD.iterator(RDD.scala:313)
	at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)
	at org.apache.spark.scheduler.Task.run(Task.scala:127)
	at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:446)
	at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1377)
	at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:449)
	at java.base/java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1128)
	at java.base/java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:628)
	at java.base/java.lang.Thread.run(Thread.java:829)

Driver stacktrace:
	at org.apache.spark.scheduler.DAGScheduler.failJobAndIndependentStages(DAGScheduler.scala:2059)
	at org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2(DAGScheduler.scala:2008)
	at org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2$adapted(DAGScheduler.scala:2007)
	at scala.collection.mutable.ResizableArray.foreach(ResizableArray.scala:62)
	at scala.collection.mutable.ResizableArray.foreach$(ResizableArray.scala:55)
	at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:49)
	at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:2007)
	at org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1(DAGScheduler.scala:973)
	at org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1$adapted(DAGScheduler.scala:973)
	at scala.Option.foreach(Option.scala:407)
	at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:973)
	at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:2239)
	at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2188)
	at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2177)
	at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:49)
	at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:775)
	at org.apache.spark.SparkContext.runJob(SparkContext.scala:2099)
	at org.apache.spark.SparkContext.runJob(SparkContext.scala:2120)
	at org.apache.spark.SparkContext.runJob(SparkContext.scala:2139)
	at org.apache.spark.SparkContext.runJob(SparkContext.scala:2164)
	at org.apache.spark.rdd.RDD.$anonfun$collect$1(RDD.scala:1004)
	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:388)
	at org.apache.spark.rdd.RDD.collect(RDD.scala:1003)
	at org.apache.spark.sql.execution.SparkPlan.executeCollect(SparkPlan.scala:385)
	at org.apache.spark.sql.Dataset.$anonfun$collectToPython$1(Dataset.scala:3450)
	at org.apache.spark.sql.Dataset.$anonfun$withAction$1(Dataset.scala:3618)
	at org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$5(SQLExecution.scala:100)
	at org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:160)
	at org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$1(SQLExecution.scala:87)
	at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:764)
	at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:64)
	at org.apache.spark.sql.Dataset.withAction(Dataset.scala:3616)
	at org.apache.spark.sql.Dataset.collectToPython(Dataset.scala:3447)
	at java.base/jdk.internal.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
	at java.base/jdk.internal.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
	at java.base/jdk.internal.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
	at java.base/java.lang.reflect.Method.invoke(Method.java:566)
	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.base/java.lang.Thread.run(Thread.java:829)
Caused by: java.lang.UnsupportedOperationException: sun.misc.Unsafe or java.nio.DirectByteBuffer.<init>(long, int) not available
	at io.netty.util.internal.PlatformDependent.directBuffer(PlatformDependent.java:490)
	at io.netty.buffer.NettyArrowBuf.getDirectBuffer(NettyArrowBuf.java:243)
	at io.netty.buffer.NettyArrowBuf.nioBuffer(NettyArrowBuf.java:233)
	at io.netty.buffer.ArrowBuf.nioBuffer(ArrowBuf.java:245)
	at org.apache.arrow.vector.ipc.ReadChannel.readFully(ReadChannel.java:81)
	at org.apache.arrow.vector.ipc.message.MessageSerializer.readMessageBody(MessageSerializer.java:696)
	at org.apache.arrow.vector.ipc.message.MessageSerializer.deserializeRecordBatch(MessageSerializer.java:344)
	at org.apache.spark.sql.execution.arrow.ArrowConverters$.loadBatch(ArrowConverters.scala:189)
	at org.apache.spark.sql.execution.arrow.ArrowConverters$$anon$2.nextBatch(ArrowConverters.scala:165)
	at org.apache.spark.sql.execution.arrow.ArrowConverters$$anon$2.<init>(ArrowConverters.scala:144)
	at org.apache.spark.sql.execution.arrow.ArrowConverters$.fromBatchIterator(ArrowConverters.scala:143)
	at org.apache.spark.sql.execution.arrow.ArrowConverters$.$anonfun$toDataFrame$1(ArrowConverters.scala:203)
	at org.apache.spark.rdd.RDD.$anonfun$mapPartitions$2(RDD.scala:837)
	at org.apache.spark.rdd.RDD.$anonfun$mapPartitions$2$adapted(RDD.scala:837)
	at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
	at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:349)
	at org.apache.spark.rdd.RDD.iterator(RDD.scala:313)
	at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
	at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:349)
	at org.apache.spark.rdd.RDD.iterator(RDD.scala:313)
	at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
	at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:349)
	at org.apache.spark.rdd.RDD.iterator(RDD.scala:313)
	at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)
	at org.apache.spark.scheduler.Task.run(Task.scala:127)
	at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:446)
	at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1377)
	at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:449)
	at java.base/java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1128)
	at java.base/java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:628)
	... 1 more


During handling of the above exception, another exception occurred:

Exception                                 Traceback (most recent call last)
/usr/local/lib/python3.7/dist-packages/nlu/pipe/utils/predict_helper.py in predict_help(pipe, data, output_level, positions, keep_stranger_features, metadata, multithread, drop_irrelevant_cols, return_spark_df, get_embeddings)
    105             logger.warning(f"Predictions Failed={err}")
    106             pipe.print_exception_err(err)
--> 107             raise Exception("Failure to process data with NLU")
    108 
    109     # except Exception as err:

Exception: Failure to process data with NLU```

@C-K-Loan C-K-Loan reopened this May 2, 2022
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@daralthus @C-K-Loan @ahmedlone127