pyspark toPandas() works locally but fails in cluster
I have an app where after doing various processes in pyspark I have a smaller dataset which I need to convert to pandas before uploading to elasticsearch. I have
res = result.select("*").toPandas()
On my local when I use
spark-submit --master "local[*]" app.py
It works perfectly fine. I also have a 2 worker cluster, when I run it on my cluster using:
spark-submit --master MASTER_IP:7077 app.py
I get the following error:
Traceback (most recent call last):
File "/home/nitinram/Elisity-Master/esaas/ml_model/landspeed_violation_spark/landspeed_violation_spark.py", line 173, in <module>
results = landspeed_calculator(ps_df_compiled,landspeed_params, sc)
File "/home/nitinram/Elisity-Master/esaas/ml_model/landspeed_violation_spark/landspeed_violation_spark_utilities.py", line 273, in landspeed_calculator
res = result.select("*").toPandas()
File "/opt/spark/python/lib/pyspark.zip/pyspark/sql/pandas/conversion.py", line 110, in toPandas
split_batches=self_destruct)
File "/opt/spark/python/lib/pyspark.zip/pyspark/sql/pandas/conversion.py", line 286, in _collect_as_arrow
jsocket_auth_server.getResult()
File "/opt/spark/python/lib/py4j-0.10.9.3-src.zip/py4j/java_gateway.py", line 1322, in __call__
answer, self.gateway_client, self.target_id, self.name)
File "/opt/spark/python/lib/pyspark.zip/pyspark/sql/utils.py", line 111, in deco
return f(*a, **kw)
File "/opt/spark/python/lib/py4j-0.10.9.3-src.zip/py4j/protocol.py", line 328, in get_return_value
format(target_id, ".", name), value)
py4j.protocol.Py4JJavaError: An error occurred while calling o2696.getResult.
: org.apache.spark.SparkException: Exception thrown in awaitResult:
at org.apache.spark.util.ThreadUtils$.awaitResult(ThreadUtils.scala:301)
at org.apache.spark.security.SocketAuthServer.getResult(SocketAuthServer.scala:97)
at org.apache.spark.security.SocketAuthServer.getResult(SocketAuthServer.scala:93)
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.ClientServerConnection.waitForCommands(ClientServerConnection.java:182)
at py4j.ClientServerConnection.run(ClientServerConnection.java:106)
at java.base/java.lang.Thread.run(Thread.java:829)
Caused by: org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 206.0 failed 4 times, most recent failure: Lost task 0.3 in stage 206.0 (TID 114) (10.5.24.113 executor 1😞 org.apache.spark.api.python.PythonException: Traceback (most recent call last):
File "/opt/spark/python/lib/pyspark.zip/pyspark/worker.py", line 603, in main
func, profiler, deserializer, serializer = read_udfs(pickleSer, infile, eval_type)
File "/opt/spark/python/lib/pyspark.zip/pyspark/worker.py", line 449, in read_udfs
udfs.append(read_single_udf(pickleSer, infile, eval_type, runner_conf, udf_index=i))
File "/opt/spark/python/lib/pyspark.zip/pyspark/worker.py", line 251, in read_single_udf
f, return_type = read_command(pickleSer, infile)
File "/opt/spark/python/lib/pyspark.zip/pyspark/worker.py", line 71, in read_command
command = serializer._read_with_length(file)
File "/opt/spark/python/lib/pyspark.zip/pyspark/serializers.py", line 160, in _read_with_length
return self.loads(obj)
File "/opt/spark/python/lib/pyspark.zip/pyspark/serializers.py", line 430, in loads
return pickle.loads(obj, encoding=encoding)
ModuleNotFoundError: No module named 'pandas'
at org.apache.spark.api.python.BasePythonRunner$ReaderIterator.handlePythonException(PythonRunner.scala:555)
at org.apache.spark.sql.execution.python.PythonArrowOutput$$anon$1.read(PythonArrowOutput.scala:101)
at org.apache.spark.sql.execution.python.PythonArrowOutput$$anon$1.read(PythonArrowOutput.scala:50)
at org.apache.spark.api.python.BasePythonRunner$ReaderIterator.hasNext(PythonRunner.scala:508)
at org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:37)
at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:491)
at scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:460)
at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage69.processNext(Unknown Source)
at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
at org.apache.spark.sql.execution.WholeStageCodegenExec$$anon$1.hasNext(WholeStageCodegenExec.scala:759)
at scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:460)
at org.apache.spark.shuffle.sort.BypassMergeSortShuffleWriter.write(BypassMergeSortShuffleWriter.java:140)
at org.apache.spark.shuffle.ShuffleWriteProcessor.write(ShuffleWriteProcessor.scala:59)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:99)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:52)
at org.apache.spark.scheduler.Task.run(Task.scala:131)
at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:506)
at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1462)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:509)
at java.base/java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1128)
at java.base/java.util.concurrent.ThreadPoolExecutor$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:2454)
at org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2(DAGScheduler.scala:2403)
at org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2$adapted(DAGScheduler.scala:2402)
at scala.collection.mutable.ResizableArray.foreach(ResizableArray.scala:62)
at scala.collection.mutable.ResizableArray.foreach$(ResizableArray.scala:55)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:49)
at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:2402)
at org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1(DAGScheduler.scala:1160)
at org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1$adapted(DAGScheduler.scala:1160)
at scala.Option.foreach(Option.scala:407)
at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:1160)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:2642)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2584)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2573)
at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:49)
Caused by: org.apache.spark.api.python.PythonException: Traceback (most recent call last):
File "/opt/spark/python/lib/pyspark.zip/pyspark/worker.py", line 603, in main
func, profiler, deserializer, serializer = read_udfs(pickleSer, infile, eval_type)
File "/opt/spark/python/lib/pyspark.zip/pyspark/worker.py", line 449, in read_udfs
udfs.append(read_single_udf(pickleSer, infile, eval_type, runner_conf, udf_index=i))
File "/opt/spark/python/lib/pyspark.zip/pyspark/worker.py", line 251, in read_single_udf
f, return_type = read_command(pickleSer, infile)
File "/opt/spark/python/lib/pyspark.zip/pyspark/worker.py", line 71, in read_command
command = serializer._read_with_length(file)
File "/opt/spark/python/lib/pyspark.zip/pyspark/serializers.py", line 160, in _read_with_length
return self.loads(obj)
File "/opt/spark/python/lib/pyspark.zip/pyspark/serializers.py", line 430, in loads
return pickle.loads(obj, encoding=encoding)
ModuleNotFoundError: No module named 'pandas'
at org.apache.spark.api.python.BasePythonRunner$ReaderIterator.handlePythonException(PythonRunner.scala:555)
at org.apache.spark.sql.execution.python.PythonArrowOutput$$anon$1.read(PythonArrowOutput.scala:101)
at org.apache.spark.sql.execution.python.PythonArrowOutput$$anon$1.read(PythonArrowOutput.scala:50)
at org.apache.spark.api.python.BasePythonRunner$ReaderIterator.hasNext(PythonRunner.scala:508)
at org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:37)
at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:491)
at scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:460)
at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage69.processNext(Unknown Source)
at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
at org.apache.spark.sql.execution.WholeStageCodegenExec$$anon$1.hasNext(WholeStageCodegenExec.scala:759)
at scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:460)
at org.apache.spark.shuffle.sort.BypassMergeSortShuffleWriter.write(BypassMergeSortShuffleWriter.java:140)
at org.apache.spark.shuffle.ShuffleWriteProcessor.write(ShuffleWriteProcessor.scala:59)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:99)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:52)
at org.apache.spark.scheduler.Task.run(Task.scala:131)
at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:506)
at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1462)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:509)
at java.base/java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1128)
at java.base/java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:628)
at java.base/java.lang.Thread.run(Thread.java:829)
My environment is I have spark installed in all the machines and I have a virtual environment with the other library dependencies. The same virtual environment exists across all the workers and the driver. I have pandas installed on the driver and every worker nodes in the virtual environment. I also have "spark.sql.execution.arrow.pyspark.enabled" set to "true". Any ideas on how to solve this? I checked to see if result has 0 elements but its shape is (78, 31).
