PySpark - Error when checking if I have NaN in some columns - python-3.x

Question

Try to check if I have NaN value in some columns with
ddf_temp = ddf.select('col1', 'col2' ...) # all int type
ddf_temp.select([count(when(isnull(c), c)).alias(c) for c in ddf_temp.columns]).show()
I could isolate which columns gives me those error but I cannot find out why I got this :
---------------------------------------------------------------------------
Py4JJavaError Traceback (most recent call last)
<ipython-input-47-76c75cf06695> in <module>()
3 # ddf_temp = ddf10.select('state_bottle_cost')
4 ddf_temp = ddf10.where(col('state_bottle_retail').isNull())
----> 5 ddf_temp.show()
6 # ddf_temp = ddf10.select('store_number', 'zip_code', 'county_number', 'category', 'vendor_number', 'pack', 'bottles_sold')
7 # ddf_temp.select([count(when(isnull(c), c)).alias(c) for c in ddf_temp.columns]).show()
3 frames
/content/spark-2.4.3-bin-hadoop2.7/python/lib/py4j-0.10.7-src.zip/py4j/protocol.py in get_return_value(answer, gateway_client, target_id, name)
326 raise Py4JJavaError(
327 "An error occurred while calling {0}{1}{2}.\n".
--> 328 format(target_id, ".", name), value)
329 else:
330 raise Py4JError(
Py4JJavaError: An error occurred while calling o2010.showString.
: org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 43.0 failed 1 times, most recent failure: Lost task 0.0 in stage 43.0 (TID 233, localhost, executor driver): org.apache.spark.api.python.PythonException: Traceback (most recent call last):
File "/content/spark-2.4.3-bin-hadoop2.7/python/lib/pyspark.zip/pyspark/worker.py", line 377, in main
process()
File "/content/spark-2.4.3-bin-hadoop2.7/python/lib/pyspark.zip/pyspark/worker.py", line 372, in process
serializer.dump_stream(func(split_index, iterator), outfile)
File "/content/spark-2.4.3-bin-hadoop2.7/python/lib/pyspark.zip/pyspark/serializers.py", line 345, in dump_stream
self.serializer.dump_stream(self._batched(iterator), stream)
File "/content/spark-2.4.3-bin-hadoop2.7/python/lib/pyspark.zip/pyspark/serializers.py", line 141, in dump_stream
for obj in iterator:
File "/content/spark-2.4.3-bin-hadoop2.7/python/lib/pyspark.zip/pyspark/serializers.py", line 334, in _batched
for item in iterator:
File "<string>", line 1, in <lambda>
File "/content/spark-2.4.3-bin-hadoop2.7/python/lib/pyspark.zip/pyspark/worker.py", line 85, in <lambda>
return lambda *a: f(*a)
File "/content/spark-2.4.3-bin-hadoop2.7/python/lib/pyspark.zip/pyspark/util.py", line 99, in wrapper
return f(*args, **kwargs)
File "<ipython-input-11-9ec9e286520d>", line 3, in <lambda>
TypeError: 'NoneType' object is not subscriptable
at org.apache.spark.api.python.BasePythonRunner$ReaderIterator.handlePythonException(PythonRunner.scala:452)
at org.apache.spark.sql.execution.python.PythonUDFRunner$$anon$1.read(PythonUDFRunner.scala:81)
at org.apache.spark.sql.execution.python.PythonUDFRunner$$anon$1.read(PythonUDFRunner.scala:64)
at org.apache.spark.api.python.BasePythonRunner$ReaderIterator.hasNext(PythonRunner.scala:406)
at org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:37)
at scala.collection.Iterator$$anon$12.hasNext(Iterator.scala:440)
at scala.collection.Iterator$$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 scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:409)
at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:409)
at scala.collection.Iterator$GroupedIterator.fill(Iterator.scala:1124)
at scala.collection.Iterator$GroupedIterator.hasNext(Iterator.scala:1130)
at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:409)
at scala.collection.Iterator$class.foreach(Iterator.scala:891)
at scala.collection.AbstractIterator.foreach(Iterator.scala:1334)
at org.apache.spark.api.python.PythonRDD$.writeIteratorToStream(PythonRDD.scala:224)
at org.apache.spark.sql.execution.python.PythonUDFRunner$$anon$2.writeIteratorToStream(PythonUDFRunner.scala:50)
at org.apache.spark.api.python.BasePythonRunner$WriterThread$$anonfun$run$1.apply(PythonRunner.scala:345)
at org.apache.spark.util.Utils$.logUncaughtExceptions(Utils.scala:1945)
at org.apache.spark.api.python.BasePythonRunner$WriterThread.run(PythonRunner.scala:194)
Driver stacktrace:
at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$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$$anon$1.run(EventLoop.scala:49)
at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:737)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2061)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2082)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2101)
at org.apache.spark.sql.execution.SparkPlan.executeTake(SparkPlan.scala:365)
at org.apache.spark.sql.execution.CollectLimitExec.executeCollect(limit.scala:38)
at org.apache.spark.sql.Dataset.org$apache$spark$sql$Dataset$$collectFromPlan(Dataset.scala:3383)
at org.apache.spark.sql.Dataset$$anonfun$head$1.apply(Dataset.scala:2544)
at org.apache.spark.sql.Dataset$$anonfun$head$1.apply(Dataset.scala:2544)
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.head(Dataset.scala:2544)
at org.apache.spark.sql.Dataset.take(Dataset.scala:2758)
at org.apache.spark.sql.Dataset.getRows(Dataset.scala:254)
at org.apache.spark.sql.Dataset.showString(Dataset.scala:291)
at sun.reflect.GeneratedMethodAccessor122.invoke(Unknown Source)
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:748)
Caused by: org.apache.spark.api.python.PythonException: Traceback (most recent call last):
File "/content/spark-2.4.3-bin-hadoop2.7/python/lib/pyspark.zip/pyspark/worker.py", line 377, in main
process()
File "/content/spark-2.4.3-bin-hadoop2.7/python/lib/pyspark.zip/pyspark/worker.py", line 372, in process
serializer.dump_stream(func(split_index, iterator), outfile)
File "/content/spark-2.4.3-bin-hadoop2.7/python/lib/pyspark.zip/pyspark/serializers.py", line 345, in dump_stream
self.serializer.dump_stream(self._batched(iterator), stream)
File "/content/spark-2.4.3-bin-hadoop2.7/python/lib/pyspark.zip/pyspark/serializers.py", line 141, in dump_stream
for obj in iterator:
File "/content/spark-2.4.3-bin-hadoop2.7/python/lib/pyspark.zip/pyspark/serializers.py", line 334, in _batched
for item in iterator:
File "<string>", line 1, in <lambda>
File "/content/spark-2.4.3-bin-hadoop2.7/python/lib/pyspark.zip/pyspark/worker.py", line 85, in <lambda>
return lambda *a: f(*a)
File "/content/spark-2.4.3-bin-hadoop2.7/python/lib/pyspark.zip/pyspark/util.py", line 99, in wrapper
return f(*args, **kwargs)
File "<ipython-input-11-9ec9e286520d>", line 3, in <lambda>
TypeError: 'NoneType' object is not subscriptable
at org.apache.spark.api.python.BasePythonRunner$ReaderIterator.handlePythonException(PythonRunner.scala:452)
at org.apache.spark.sql.execution.python.PythonUDFRunner$$anon$1.read(PythonUDFRunner.scala:81)
at org.apache.spark.sql.execution.python.PythonUDFRunner$$anon$1.read(PythonUDFRunner.scala:64)
at org.apache.spark.api.python.BasePythonRunner$ReaderIterator.hasNext(PythonRunner.scala:406)
at org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:37)
at scala.collection.Iterator$$anon$12.hasNext(Iterator.scala:440)
at scala.collection.Iterator$$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 scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:409)
at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:409)
at scala.collection.Iterator$GroupedIterator.fill(Iterator.scala:1124)
at scala.collection.Iterator$GroupedIterator.hasNext(Iterator.scala:1130)
at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:409)
at scala.collection.Iterator$class.foreach(Iterator.scala:891)
at scala.collection.AbstractIterator.foreach(Iterator.scala:1334)
at org.apache.spark.api.python.PythonRDD$.writeIteratorToStream(PythonRDD.scala:224)
at org.apache.spark.sql.execution.python.PythonUDFRunner$$anon$2.writeIteratorToStream(PythonUDFRunner.scala:50)
at org.apache.spark.api.python.BasePythonRunner$WriterThread$$anonfun$run$1.apply(PythonRunner.scala:345)
at org.apache.spark.util.Utils$.logUncaughtExceptions(Utils.scala:1945)
at org.apache.spark.api.python.BasePythonRunner$WriterThread.run(PythonRunner.scala:194)
EDIT :
remove_first_char = udf(lambda x: x[1:])
ddf4 = ddf3.withColumn('State Bottle Cost', remove_first_char('State Bottle Cost'))
multiply_by_100 = udf(lambda x: x*100)
ddf5 = ddf4.withColumn('State Bottle Cost', ddf4['State Bottle Cost'].cast(DoubleType()))
ddf5 = ddf5.withColumn('State Bottle Cost', multiply_by_100('State Bottle Cost'))
ddf5 = ddf5.withColumn('State Bottle Cost', ddf5['State Bottle Cost'].cast(IntegerType()))

Answer 1

You have Nones in your dataframe and by applying the UDF it will execute None[1:] which gives you the error TypeError: 'NoneType' object is not subscriptable (you can try it in a python shell).
When using built-in pyspark functions it will always map null->null. If you would want to do it via UDF (which is not recommended since spark does internal optimization on built-in sql functions), you would need to catch the None case: lambda x: x if not x else x[1:]