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Cannot group by with data after flatMap (Spark SQL)

Time：12-03

I have a task with Spark SQL, original data is:

 --------- --------- -------------------- -------- ------------ --------- ---------- -------------- 
|InvoiceNo|StockCode|         Description|Quantity| InvoiceDate|UnitPrice|CustomerID|       Country|
 --------- --------- -------------------- -------- ------------ --------- ---------- -------------- 
|   536365|   85123A|WHITE HANGING HEA...|       6|12/1/10 8:26|     2.55|     17850|United Kingdom|
|   536365|    71053| WHITE METAL LANTERN|       6|12/1/10 8:26|     3.39|     17850|United Kingdom|
|   536365|   84406B|CREAM CUPID HEART...|       8|12/1/10 8:26|     2.75|     17850|United Kingdom|
|   536365|   84029G|KNITTED UNION FLA...|       6|12/1/10 8:26|     3.39|     17850|United Kingdom|
|   536365|   84029E|RED WOOLLY HOTTIE...|       6|12/1/10 8:26|     3.39|     17850|United Kingdom|
|   536365|    22752|SET 7 BABUSHKA NE...|       2|12/1/10 8:26|     7.65|     17850|United Kingdom|
|   536365|    21730|GLASS STAR FROSTE...|       6|12/1/10 8:26|     4.25|     17850|United Kingdom|
|   536366|    22633|HAND WARMER UNION...|       6|12/1/10 8:28|     1.85|     17850|United Kingdom|
|   536366|    22632|HAND WARMER RED P...|       6|12/1/10 8:28|     1.85|     17850|United Kingdom|
|   536367|    84879|ASSORTED COLOUR B...|      32|12/1/10 8:34|     1.69|     13047|United Kingdom|
|   536367|    22745|POPPY'S PLAYHOUSE...|       6|12/1/10 8:34|      2.1|     13047|United Kingdom|
|   536367|    22748|POPPY'S PLAYHOUSE...|       6|12/1/10 8:34|      2.1|     13047|United Kingdom|
|   536367|    22749|FELTCRAFT PRINCES...|       8|12/1/10 8:34|     3.75|     13047|United Kingdom|
|   536367|    22310|IVORY KNITTED MUG...|       6|12/1/10 8:34|     1.65|     13047|United Kingdom|
|   536367|    84969|BOX OF 6 ASSORTED...|       6|12/1/10 8:34|     4.25|     13047|United Kingdom|
|   536367|    22623|BOX OF VINTAGE JI...|       3|12/1/10 8:34|     4.95|     13047|United Kingdom|
|   536367|    22622|BOX OF VINTAGE AL...|       2|12/1/10 8:34|     9.95|     13047|United Kingdom|
|   536367|    21754|HOME BUILDING BLO...|       3|12/1/10 8:34|     5.95|     13047|United Kingdom|
|   536367|    21755|LOVE BUILDING BLO...|       3|12/1/10 8:34|     5.95|     13047|United Kingdom|
|   536367|    21777|RECIPE BOX WITH M...|       4|12/1/10 8:34|     7.95|     13047|United Kingdom|
 --------- --------- -------------------- -------- ------------ --------- ---------- --------------

With my task, I want to count which word is the word that appears the most in Description field. So I did the following: use flatMap to create a new DataFrame from the original DataFrame by separating the Description field by spaces then build a new table, below is a new table:

 ------ ------- --- 
|number|   word|lit|
 ------ ------- --- 
|     0|  WHITE|  1|
|     1|HANGING|  1|
|     2|  HEART|  1|
|     3|T-LIGHT|  1|
|     4| HOLDER|  1|
|     5|  WHITE|  1|
|     6|  METAL|  1|
|     7|LANTERN|  1|
|     8|  CREAM|  1|
|     9|  CUPID|  1|
|    10| HEARTS|  1|
|    11|   COAT|  1|
|    12| HANGER|  1|
|    13|KNITTED|  1|
|    14|  UNION|  1|
|    15|   FLAG|  1|
|    16|    HOT|  1|
|    17|  WATER|  1|
|    18| BOTTLE|  1|
|    19|    RED|  1|
 ------ ------- ---

And this is my code:

SparkSession spark = SparkSession.builder().appName("Part-4").master("local").getOrCreate();
Dataset<Row> data = spark.read()
        .option("inferSchema", true)
        .option("header", true)
        .csv("hdfs://localhost:9000/retails.csv");

data.flatMap(new FlatMapFunction<Row, Row>() {
    private static final long serialVersionUID = 1L;
    private int cnt = 0;
    
    @Override
    public Iterator<Row> call(Row r) throws Exception {
        List<String> listItem = Arrays.asList(r.getString(2).split(" "));
        
        List<Row> listItemRow = new ArrayList<Row>();
        for (String item : listItem) {
            listItemRow.add(RowFactory.create(cnt, item, 1));
            cnt  ;
        }
        
        return listItemRow.iterator();
    }
}, RowEncoder.apply(new StructType().add("number", "integer").add("word", "string").add("lit", "integer"))).createOrReplaceTempView("data");

spark.sql("select * from data").show();

I have a problem, that if I group by or perform other complex SQL operations, the program gives an error.

This is my code when group by: spark.sql("select word, count(lit) from data group by word").show();

And this is my error:

java.lang.NullPointerException
        at com.spark.part_4.Main$1.call(Main.java:33)
        at com.spark.part_4.Main$1.call(Main.java:27)
        at org.apache.spark.sql.Dataset.$anonfun$flatMap$2(Dataset.scala:2876)
        at scala.collection.Iterator$$anon$11.nextCur(Iterator.scala:484)
        at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:490)
        at scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:458)
        at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.agg_doAggregateWithKeys_0$(Unknown Source)
        at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.processNext(Unknown Source)
        at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
        at org.apache.spark.sql.execution.WholeStageCodegenExec$$anon$1.hasNext(WholeStageCodegenExec.scala:755)
        at scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:458)
        at org.apache.spark.shuffle.sort.BypassMergeSortShuffleWriter.write(BypassMergeSortShuffleWriter.java:132)
        at org.apache.spark.shuffle.ShuffleWriteProcessor.write(ShuffleWriteProcessor.scala:59)
        at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:99)
        at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:52)
        at org.apache.spark.scheduler.Task.run(Task.scala:131)
        at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:497)
        at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1439)
        at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:500)
        at java.base/java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1128)
        at java.base/java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:628)
        at java.base/java.lang.Thread.run(Thread.java:829)
21/12/03 00:08:39 WARN TaskSetManager: Lost task 0.0 in stage 2.0 (TID 2) (192.168.1.10 executor driver): java.lang.NullPointerException
        at com.spark.part_4.Main$1.call(Main.java:33)
        at com.spark.part_4.Main$1.call(Main.java:27)
        at org.apache.spark.sql.Dataset.$anonfun$flatMap$2(Dataset.scala:2876)
        at scala.collection.Iterator$$anon$11.nextCur(Iterator.scala:484)
        at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:490)
        at scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:458)
        at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.agg_doAggregateWithKeys_0$(Unknown Source)
        at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.processNext(Unknown Source)
        at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
        at org.apache.spark.sql.execution.WholeStageCodegenExec$$anon$1.hasNext(WholeStageCodegenExec.scala:755)
        at scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:458)
        at org.apache.spark.shuffle.sort.BypassMergeSortShuffleWriter.write(BypassMergeSortShuffleWriter.java:132)
        at org.apache.spark.shuffle.ShuffleWriteProcessor.write(ShuffleWriteProcessor.scala:59)
        at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:99)
        at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:52)
        at org.apache.spark.scheduler.Task.run(Task.scala:131)
        at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:497)
        at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1439)
        at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:500)
        at java.base/java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1128)
        at java.base/java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:628)
        at java.base/java.lang.Thread.run(Thread.java:829)

21/12/03 00:08:39 ERROR TaskSetManager: Task 0 in stage 2.0 failed 1 times; aborting job
21/12/03 00:08:39 INFO TaskSchedulerImpl: Removed TaskSet 2.0, whose tasks have all completed, from pool 
21/12/03 00:08:39 INFO TaskSchedulerImpl: Cancelling stage 2
21/12/03 00:08:39 INFO TaskSchedulerImpl: Killing all running tasks in stage 2: Stage cancelled
21/12/03 00:08:39 INFO DAGScheduler: ShuffleMapStage 2 (show at Main.java:45) failed in 0.298 s due to 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) (192.168.1.10 executor driver): java.lang.NullPointerException
        at com.spark.part_4.Main$1.call(Main.java:33)
        at com.spark.part_4.Main$1.call(Main.java:27)
        at org.apache.spark.sql.Dataset.$anonfun$flatMap$2(Dataset.scala:2876)
        at scala.collection.Iterator$$anon$11.nextCur(Iterator.scala:484)
        at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:490)
        at scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:458)
        at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.agg_doAggregateWithKeys_0$(Unknown Source)
        at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.processNext(Unknown Source)
        at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
        at org.apache.spark.sql.execution.WholeStageCodegenExec$$anon$1.hasNext(WholeStageCodegenExec.scala:755)
        at scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:458)
        at org.apache.spark.shuffle.sort.BypassMergeSortShuffleWriter.write(BypassMergeSortShuffleWriter.java:132)
        at org.apache.spark.shuffle.ShuffleWriteProcessor.write(ShuffleWriteProcessor.scala:59)
        at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:99)
        at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:52)
        at org.apache.spark.scheduler.Task.run(Task.scala:131)
        at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:497)
        at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1439)
        at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:500)
        at java.base/java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1128)
        at java.base/java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:628)
        at java.base/java.lang.Thread.run(Thread.java:829)

Driver stacktrace:
21/12/03 00:08:39 INFO DAGScheduler: Job 2 failed: show at Main.java:45, took 0.312624 s
Exception in thread "main" 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) (192.168.1.10 executor driver): java.lang.NullPointerException
        at com.spark.part_4.Main$1.call(Main.java:33)
        at com.spark.part_4.Main$1.call(Main.java:27)
        at org.apache.spark.sql.Dataset.$anonfun$flatMap$2(Dataset.scala:2876)
        at scala.collection.Iterator$$anon$11.nextCur(Iterator.scala:484)
        at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:490)
        at scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:458)
        at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.agg_doAggregateWithKeys_0$(Unknown Source)
        at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.processNext(Unknown Source)
        at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
        at org.apache.spark.sql.execution.WholeStageCodegenExec$$anon$1.hasNext(WholeStageCodegenExec.scala:755)
        at scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:458)
        at org.apache.spark.shuffle.sort.BypassMergeSortShuffleWriter.write(BypassMergeSortShuffleWriter.java:132)
        at org.apache.spark.shuffle.ShuffleWriteProcessor.write(ShuffleWriteProcessor.scala:59)
        at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:99)
        at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:52)
        at org.apache.spark.scheduler.Task.run(Task.scala:131)
        at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:497)
        at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1439)
        at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:500)
        at java.base/java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1128)
        at java.base/java.util.concurrent.ThreadPoolExecutor$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:2253)
        at org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2(DAGScheduler.scala:2202)
        at org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2$adapted(DAGScheduler.scala:2201)
        at scala.collection.mutable.ResizableArray.foreach(ResizableArray.scala:62)
        at scala.collection.mutable.ResizableArray.foreach$(ResizableArray.scala:55)
        at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:49)
        at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:2201)
        at org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1(DAGScheduler.scala:1078)
        at org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1$adapted(DAGScheduler.scala:1078)
        at scala.Option.foreach(Option.scala:407)
        at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:1078)
        at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:2440)
        at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2382)
        at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2371)
        at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:49)
        at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:868)
        at org.apache.spark.SparkContext.runJob(SparkContext.scala:2202)
        at org.apache.spark.SparkContext.runJob(SparkContext.scala:2223)
        at org.apache.spark.SparkContext.runJob(SparkContext.scala:2242)
        at org.apache.spark.sql.execution.SparkPlan.executeTake(SparkPlan.scala:472)
        at org.apache.spark.sql.execution.SparkPlan.executeTake(SparkPlan.scala:425)
        at org.apache.spark.sql.execution.CollectLimitExec.executeCollect(limit.scala:47)
        at org.apache.spark.sql.Dataset.collectFromPlan(Dataset.scala:3696)
        at org.apache.spark.sql.Dataset.$anonfun$head$1(Dataset.scala:2722)
        at org.apache.spark.sql.Dataset.$anonfun$withAction$1(Dataset.scala:3687)
        at org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$5(SQLExecution.scala:103)
        at org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:163)
        at org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$1(SQLExecution.scala:90)
        at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:772)
        at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:64)
        at org.apache.spark.sql.Dataset.withAction(Dataset.scala:3685)
        at org.apache.spark.sql.Dataset.head(Dataset.scala:2722)
        at org.apache.spark.sql.Dataset.take(Dataset.scala:2929)
        at org.apache.spark.sql.Dataset.getRows(Dataset.scala:301)
        at org.apache.spark.sql.Dataset.showString(Dataset.scala:338)
        at org.apache.spark.sql.Dataset.show(Dataset.scala:825)
        at org.apache.spark.sql.Dataset.show(Dataset.scala:784)
        at org.apache.spark.sql.Dataset.show(Dataset.scala:793)
        at com.spark.part_4.Main.main(Main.java:45)
        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 org.apache.spark.deploy.JavaMainApplication.start(SparkApplication.scala:52)
        at org.apache.spark.deploy.SparkSubmit.org$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:951)
        at org.apache.spark.deploy.SparkSubmit.doRunMain$1(SparkSubmit.scala:180)
        at org.apache.spark.deploy.SparkSubmit.submit(SparkSubmit.scala:203)
        at org.apache.spark.deploy.SparkSubmit.doSubmit(SparkSubmit.scala:90)
        at org.apache.spark.deploy.SparkSubmit$$anon$2.doSubmit(SparkSubmit.scala:1030)
        at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:1039)
        at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)
Caused by: java.lang.NullPointerException
        at com.spark.part_4.Main$1.call(Main.java:33)
        at com.spark.part_4.Main$1.call(Main.java:27)
        at org.apache.spark.sql.Dataset.$anonfun$flatMap$2(Dataset.scala:2876)
        at scala.collection.Iterator$$anon$11.nextCur(Iterator.scala:484)
        at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:490)
        at scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:458)
        at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.agg_doAggregateWithKeys_0$(Unknown Source)
        at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.processNext(Unknown Source)
        at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
        at org.apache.spark.sql.execution.WholeStageCodegenExec$$anon$1.hasNext(WholeStageCodegenExec.scala:755)
        at scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:458)
        at org.apache.spark.shuffle.sort.BypassMergeSortShuffleWriter.write(BypassMergeSortShuffleWriter.java:132)
        at org.apache.spark.shuffle.ShuffleWriteProcessor.write(ShuffleWriteProcessor.scala:59)
        at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:99)
        at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:52)
        at org.apache.spark.scheduler.Task.run(Task.scala:131)
        at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:497)
        at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1439)
        at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:500)
        at java.base/java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1128)
        at java.base/java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:628)
        at java.base/java.lang.Thread.run(Thread.java:829)

I hope to get help from everyone, thank you...

CodePudding user response：

You are getting a java.lang.NullPointerException when applying your FlatMapFunction because you may have empty values in your dataset. It seems you are using the Description column in this example.

With an empty value, the column may be read as null by spark and the following line

List<String> listItem = Arrays.asList(r.getString(2).split(" "));

is likely to raise this exception when r.getString(2) returns null and you attempt to call the function split on a null reference.

You may attempt to address this by checking if there are null values before splitting eg

        data.flatMap(new FlatMapFunction<Row, Row>() {
            private static final long serialVersionUID = 1L;
            private int cnt = 0;
            
            public Iterator<Row> call(Row r) throws Exception {
                    
                List<Row> listItemRow = new ArrayList<Row>();
                //check if null before splitting here
                if(r.getString(2) != null) { 
                    List<String> listItem = Arrays.asList(r.getString(2).split(" "));
                    for (String item : listItem) {
                        listItemRow.add(RowFactory.create(cnt, item, 1));
                        cnt  ;
                    }
                }
                        
                return listItemRow.iterator();
            }
        }, RowEncoder.apply(
                new StructType().add("number", "integer")
                                .add("word", "string")
                                .add("lit", "integer")
        )).createOrReplaceTempView("data");

You may view these rows with null values using

data.where("Description is null").show();

and similarly filter these rows before applying your flatMap eg

data.where("Description is not null")
    .flatMap(new FlatMapFunction<Row, Row>() {
//continue the rest of your code

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