Failed to execute user defined function RegexTokenizer in Pyspark - text

Question

I am trying to perform text classification using text feature in the data using Pyspark. Below is my code for text preprocessing and the code is giving failed to execute user defined function RegexTokenizer.
tokenizer = RegexTokenizer(inputCol = "text", outputCol = "words", pattern = "\\W")
add_stopwords = StopWordsRemover.loadDefaultStopWords("english")
remover = StopWordsRemover(inputCol = "words", outputCol = "filtered").setStopWords(add_stopwords)
label_stringIdx = StringIndexer(inputCol = "label", outputCol = "target")
countVectors = CountVectorizer(inputCol="filtered", outputCol="features", vocabSize=1000, minDF=5)
#pipleline for text pre-processing
pipeline = Pipeline(stages=[tokenizer,remover, countVectors, label_stringIdx])
#fit the dat for the pipeline
pipelineFit = pipeline.fit(dataset)
dataset = pipelineFit.transform(dataset)
dataset.show()
The Error is:
/usr/local/lib/python3.6/dist-packages/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 o589.fit.
: org.apache.spark.SparkException: Job aborted due to stage failure: Task 2 in stage 92.0 failed 1 times, most recent failure: Lost task 2.0 in stage 92.0 (TID 1317, 1e1a151fa0f5, executor driver): org.apache.spark.SparkException: Failed to execute user defined function(RegexTokenizer$$Lambda$3017/0x000000084123e040: (string) => array<string>)
at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage2.processNext(Unknown Source)
at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
at org.apache.spark.sql.execution.WholeStageCodegenExec$$anon$1.hasNext(WholeStageCodegenExec.scala:729)
at scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:458)
at scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:458)
at scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:458)
at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:489)
at org.apache.spark.util.collection.ExternalSorter.insertAll(ExternalSorter.scala:192)
at org.apache.spark.shuffle.sort.SortShuffleWriter.write(SortShuffleWriter.scala:62)
at org.apache.spark.shuffle.ShuffleWriteProcessor.write(ShuffleWriteProcessor.scala:59)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:99)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:52)
at org.apache.spark.scheduler.Task.run(Task.scala:127)
at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:444)
at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1377)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:447)
at java.base/java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1128)
at java.base/java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:628)
at java.base/java.lang.Thread.run(Thread.java:834)
Caused by: java.lang.NullPointerException
at org.apache.spark.ml.feature.RegexTokenizer.$anonfun$createTransformFunc$2(Tokenizer.scala:146)
... 19 more
Driver stacktrace:
at org.apache.spark.scheduler.DAGScheduler.failJobAndIndependentStages(DAGScheduler.scala:2023)
at org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2(DAGScheduler.scala:1972)
at org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2$adapted(DAGScheduler.scala:1971)
at scala.collection.mutable.ResizableArray.foreach(ResizableArray.scala:62)
at scala.collection.mutable.ResizableArray.foreach$(ResizableArray.scala:55)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:49)
at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1971)
at org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1(DAGScheduler.scala:950)
at org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1$adapted(DAGScheduler.scala:950)
at scala.Option.foreach(Option.scala:407)
at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:950)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:2203)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2152)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2141)
at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:49)
at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:752)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2093)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2114)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2133)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2158)
at org.apache.spark.rdd.RDD.count(RDD.scala:1227)
at org.apache.spark.ml.feature.CountVectorizer.fit(CountVectorizer.scala:233)
at org.apache.spark.ml.feature.CountVectorizer.fit(CountVectorizer.scala:149)
at java.base/jdk.internal.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at java.base/jdk.internal.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at java.base/jdk.internal.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.base/java.lang.reflect.Method.invoke(Method.java:566)
at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244)
at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357)
at py4j.Gateway.invoke(Gateway.java:282)
at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132)
at py4j.commands.CallCommand.execute(CallCommand.java:79)
at py4j.GatewayConnection.run(GatewayConnection.java:238)
at java.base/java.lang.Thread.run(Thread.java:834)
Caused by: org.apache.spark.SparkException: Failed to execute user defined function(RegexTokenizer$$Lambda$3017/0x000000084123e040: (string) => array<string>)
at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage2.processNext(Unknown Source)
at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
at org.apache.spark.sql.execution.WholeStageCodegenExec$$anon$1.hasNext(WholeStageCodegenExec.scala:729)
at scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:458)
at scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:458)
at scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:458)
at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:489)
at org.apache.spark.util.collection.ExternalSorter.insertAll(ExternalSorter.scala:192)
at org.apache.spark.shuffle.sort.SortShuffleWriter.write(SortShuffleWriter.scala:62)
at org.apache.spark.shuffle.ShuffleWriteProcessor.write(ShuffleWriteProcessor.scala:59)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:99)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:52)
at org.apache.spark.scheduler.Task.run(Task.scala:127)
at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:444)
at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1377)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:447)
at java.base/java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1128)
at java.base/java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:628)
... 1 more
Caused by: java.lang.NullPointerException
at org.apache.spark.ml.feature.RegexTokenizer.$anonfun$createTransformFunc$2(Tokenizer.scala:146)
... 19 more
Any help is highly appreciated.

Answer 1

This problem is because you have null values in the input column text.
val tokenizer = new RegexTokenizer()
.setInputCol("text")
.setOutputCol("words")
.setPattern("\\W")
val inputDF = Seq("this is text", null).toDF("text")
inputDF.show(false)
/**
* +------------+
* |text |
* +------------+
* |this is text|
* |null |
* +------------+
*/
// this fails
tokenizer.transform(inputDF)
.show(false)
/**
* Caused by: java.lang.NullPointerException
* at org.apache.spark.ml.feature.RegexTokenizer$$anonfun$createTransformFunc$2.apply(Tokenizer.scala:143)
* at org.apache.spark.ml.feature.RegexTokenizer$$anonfun$createTransformFunc$2.apply(Tokenizer.scala:141)
*/
Either remove null rows or impute null columns
// replace nulls from text col to specified string as below
val nullImputedDF = inputDF.na.fill("I am null imputed", Seq("text"))
tokenizer.transform(nullImputedDF)
.show(false)
/**
* +-----------------+----------------------+
* |text |words |
* +-----------------+----------------------+
* |this is text |[this, is, text] |
* |I am null imputed|[i, am, null, imputed]|
* +-----------------+----------------------+
*/