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20 hours ago •
JohnSnowLabs
JohnSnowLabs
Missing embedding results
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?
nlu 3.3.0 pyspark 3.0.2 py4j 0.10.9 spark-nlp 3.3.2 running on google colab
Hey because of the new update you have to add get_embeddings=True to predict to get the embeddings :)
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```