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2 / 5
Jan 2024

Using mongo-connector version 10.0.1
the below are my config

.config("spark.mongodb.write.connection.uri", "mongodb://127.0.0.1:27017/") .config("spark.mongodb.write.database", "test") .config("spark.mongodb.write.collection", "spark") .config("spark.mongodb.write.operationType", "insert")

this is what im trying to do and im not sure why this is happening

spark_df.write.format("mongodb").mode("append").save()

Below is the error I’m getting

24/01/09 11:17:26 ERROR Utils: Aborting task java.lang.NullPointerException at org.apache.spark.api.python.SerDeUtil$.$anonfun$toJavaArray$1(SerDeUtil.scala:72) at scala.collection.Iterator$$anon$10.next(Iterator.scala:461) at scala.collection.Iterator$$anon$10.next(Iterator.scala:461) at scala.collection.Iterator$$anon$10.next(Iterator.scala:461) at org.apache.spark.sql.execution.datasources.v2.DataWritingSparkTask$.$anonfun$run$1(WriteToDataSourceV2Exec.scala:419) at org.apache.spark.util.Utils$.tryWithSafeFinallyAndFailureCallbacks(Utils.scala:1525) at org.apache.spark.sql.execution.datasources.v2.DataWritingSparkTask$.run(WriteToDataSourceV2Exec.scala:457) at org.apache.spark.sql.execution.datasources.v2.V2TableWriteExec.$anonfun$writeWithV2$2(WriteToDataSourceV2Exec.scala:358) at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90) 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:1491) 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:834) 24/01/09 11:17:26 ERROR DataWritingSparkTask: Aborting commit for partition 0 (task 13, attempt 0, stage 2.0) 24/01/09 11:17:26 WARN Utils: Suppressing exception in catch: Write aborted for: PartitionId: 0, TaskId: 13. Manual data clean up may be required. com.mongodb.spark.sql.connector.exceptions.DataException: Write aborted for: PartitionId: 0, TaskId: 13. Manual data clean up may be required. at com.mongodb.spark.sql.connector.write.MongoDataWriter.abort(MongoDataWriter.java:121) at org.apache.spark.sql.execution.datasources.v2.DataWritingSparkTask$.$anonfun$run$6(WriteToDataSourceV2Exec.scala:453) at org.apache.spark.util.Utils$.tryWithSafeFinallyAndFailureCallbacks(Utils.scala:1536) at org.apache.spark.sql.execution.datasources.v2.DataWritingSparkTask$.run(WriteToDataSourceV2Exec.scala:457) at org.apache.spark.sql.execution.datasources.v2.V2TableWriteExec.$anonfun$writeWithV2$2(WriteToDataSourceV2Exec.scala:358) at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90) 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:1491) 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:834) 24/01/09 11:17:26 ERROR Executor: Exception in task 0.0 in stage 2.0 (TID 13) java.lang.NullPointerException at org.apache.spark.api.python.SerDeUtil$.$anonfun$toJavaArray$1(SerDeUtil.scala:72) at scala.collection.Iterator$$anon$10.next(Iterator.scala:461) at scala.collection.Iterator$$anon$10.next(Iterator.scala:461) at scala.collection.Iterator$$anon$10.next(Iterator.scala:461) at org.apache.spark.sql.execution.datasources.v2.DataWritingSparkTask$.$anonfun$run$1(WriteToDataSourceV2Exec.scala:419) at org.apache.spark.util.Utils$.tryWithSafeFinallyAndFailureCallbacks(Utils.scala:1525) at org.apache.spark.sql.execution.datasources.v2.DataWritingSparkTask$.run(WriteToDataSourceV2Exec.scala:457) at org.apache.spark.sql.execution.datasources.v2.V2TableWriteExec.$anonfun$writeWithV2$2(WriteToDataSourceV2Exec.scala:358) at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90) at org.apache.spark.scheduler.Task.run(Task.scala:131) at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:506) at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1491) 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:834) Suppressed: com.mongodb.spark.sql.connector.exceptions.DataException: Write aborted for: PartitionId: 0, TaskId: 13. Manual data clean up may be required. at com.mongodb.spark.sql.connector.write.MongoDataWriter.abort(MongoDataWriter.java:121) at org.apache.spark.sql.execution.datasources.v2.DataWritingSparkTask$.$anonfun$run$6(WriteToDataSourceV2Exec.scala:453) at org.apache.spark.util.Utils$.tryWithSafeFinallyAndFailureCallbacks(Utils.scala:1536) ... 10 more 24/01/09 11:17:26 WARN TaskSetManager: Lost task 0.0 in stage 2.0 (TID 13) (host.docker.internal executor driver): java.lang.NullPointerException at org.apache.spark.api.python.SerDeUtil$.$anonfun$toJavaArray$1(SerDeUtil.scala:72) at scala.collection.Iterator$$anon$10.next(Iterator.scala:461) at scala.collection.Iterator$$anon$10.next(Iterator.scala:461) at scala.collection.Iterator$$anon$10.next(Iterator.scala:461) at org.apache.spark.sql.execution.datasources.v2.DataWritingSparkTask$.$anonfun$run$1(WriteToDataSourceV2Exec.scala:419) at org.apache.spark.util.Utils$.tryWithSafeFinallyAndFailureCallbacks(Utils.scala:1525) at org.apache.spark.sql.execution.datasources.v2.DataWritingSparkTask$.run(WriteToDataSourceV2Exec.scala:457) at org.apache.spark.sql.execution.datasources.v2.V2TableWriteExec.$anonfun$writeWithV2$2(WriteToDataSourceV2Exec.scala:358) at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90) 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:1491) 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:834) Suppressed: com.mongodb.spark.sql.connector.exceptions.DataException: Write aborted for: PartitionId: 0, TaskId: 13. Manual data clean up may be required. at com.mongodb.spark.sql.connector.write.MongoDataWriter.abort(MongoDataWriter.java:121) at org.apache.spark.sql.execution.datasources.v2.DataWritingSparkTask$.$anonfun$run$6(WriteToDataSourceV2Exec.scala:453) at org.apache.spark.util.Utils$.tryWithSafeFinallyAndFailureCallbacks(Utils.scala:1536) ... 10 more 24/01/09 11:17:26 ERROR TaskSetManager: Task 0 in stage 2.0 failed 1 times; aborting job 24/01/09 11:17:26 ERROR AppendDataExec: Data source write support com.mongodb.spark.sql.connector.write.MongoBatchWrite@65dd8323 is aborting. 24/01/09 11:17:26 ERROR AppendDataExec: Data source write support com.mongodb.spark.sql.connector.write.MongoBatchWrite@65dd8323 failed to abort. Traceback (most recent call last): File "C:\Users\delve\AppData\Local\Programs\Python\Python39\lib\runpy.py", line 197, in _run_module_as_main return _run_code(code, main_globals, None, File "C:\Users\delve\AppData\Local\Programs\Python\Python39\lib\runpy.py", line 87, in _run_code exec(code, run_globals) File "C:\Users\delve\dev\spark_ao\pool\app\service\c_list\process\parser.py", line 1508, in <module> response = spark_df.write.format("mongodb").mode("append").save() File "C:\Users\delve\dev\spark_ao\.venv\lib\site-packages\pyspark\sql\readwriter.py", line 738, in save self._jwrite.save() File "C:\Users\delve\dev\spark_ao\.venv\lib\site-packages\py4j\java_gateway.py", line 1321, in __call__ return_value = get_return_value( File "C:\Users\delve\dev\spark_ao\.venv\lib\site-packages\pyspark\sql\utils.py", line 111, in deco return f(*a, **kw) File "C:\Users\delve\dev\spark_ao\.venv\lib\site-packages\py4j\protocol.py", line 326, in get_return_value raise Py4JJavaError( py4j.protocol.Py4JJavaError: An error occurred while calling o85.save. : org.apache.spark.SparkException: Writing job failed. at org.apache.spark.sql.errors.QueryExecutionErrors$.writingJobFailedError(QueryExecutionErrors.scala:606) at org.apache.spark.sql.execution.datasources.v2.V2TableWriteExec.writeWithV2(WriteToDataSourceV2Exec.scala:381) at org.apache.spark.sql.execution.datasources.v2.V2TableWriteExec.writeWithV2$(WriteToDataSourceV2Exec.scala:330) at org.apache.spark.sql.execution.datasources.v2.AppendDataExec.writeWithV2(WriteToDataSourceV2Exec.scala:236) at org.apache.spark.sql.execution.datasources.v2.V2ExistingTableWriteExec.run(WriteToDataSourceV2Exec.scala:309) at org.apache.spark.sql.execution.datasources.v2.V2ExistingTableWriteExec.run$(WriteToDataSourceV2Exec.scala:308) at org.apache.spark.sql.execution.datasources.v2.AppendDataExec.run(WriteToDataSourceV2Exec.scala:236) at org.apache.spark.sql.execution.datasources.v2.V2CommandExec.result$lzycompute(V2CommandExec.scala:43) at org.apache.spark.sql.execution.datasources.v2.V2CommandExec.result(V2CommandExec.scala:43) at org.apache.spark.sql.execution.datasources.v2.V2CommandExec.executeCollect(V2CommandExec.scala:49) at org.apache.spark.sql.execution.QueryExecution$$anonfun$eagerlyExecuteCommands$1.$anonfun$applyOrElse$1(QueryExecution.scala:97) at org.apache.spark.sql.execution.SQLExecution$.$anonfun$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$1(SQLExecution.scala:90) at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:775) at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:64) at org.apache.spark.sql.execution.QueryExecution$$anonfun$eagerlyExecuteCommands$1.applyOrElse(QueryExecution.scala:97) at org.apache.spark.sql.execution.QueryExecution$$anonfun$eagerlyExecuteCommands$1.applyOrElse(QueryExecution.scala:93) at org.apache.spark.sql.catalyst.trees.TreeNode.$anonfun$transformDownWithPruning$1(TreeNode.scala:481) at org.apache.spark.sql.catalyst.trees.CurrentOrigin$.withOrigin(TreeNode.scala:82) at org.apache.spark.sql.catalyst.trees.TreeNode.transformDownWithPruning(TreeNode.scala:481) at org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.org$apache$spark$sql$catalyst$plans$logical$AnalysisHelper$$super$transformDownWithPruning(LogicalPlan.scala:30) at org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper.transformDownWithPruning(AnalysisHelper.scala:267) at org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper.transformDownWithPruning$(AnalysisHelper.scala:263) at org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.transformDownWithPruning(LogicalPlan.scala:30) at org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.transformDownWithPruning(LogicalPlan.scala:30) at org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(TreeNode.scala:457) at org.apache.spark.sql.execution.QueryExecution.eagerlyExecuteCommands(QueryExecution.scala:93) at org.apache.spark.sql.execution.QueryExecution.commandExecuted$lzycompute(QueryExecution.scala:80) at org.apache.spark.sql.execution.QueryExecution.commandExecuted(QueryExecution.scala:78) at org.apache.spark.sql.execution.QueryExecution.assertCommandExecuted(QueryExecution.scala:115) at org.apache.spark.sql.DataFrameWriter.runCommand(DataFrameWriter.scala:848) at org.apache.spark.sql.DataFrameWriter.saveInternal(DataFrameWriter.scala:311) at org.apache.spark.sql.DataFrameWriter.save(DataFrameWriter.scala:247) 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:834) Caused by: 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 13) (host.docker.internal executor driver): java.lang.NullPointerException at org.apache.spark.api.python.SerDeUtil$.$anonfun$toJavaArray$1(SerDeUtil.scala:72) at scala.collection.Iterator$$anon$10.next(Iterator.scala:461) at scala.collection.Iterator$$anon$10.next(Iterator.scala:461) at scala.collection.Iterator$$anon$10.next(Iterator.scala:461) at org.apache.spark.sql.execution.datasources.v2.DataWritingSparkTask$.$anonfun$run$1(WriteToDataSourceV2Exec.scala:419) at org.apache.spark.util.Utils$.tryWithSafeFinallyAndFailureCallbacks(Utils.scala:1525) at org.apache.spark.sql.execution.datasources.v2.DataWritingSparkTask$.run(WriteToDataSourceV2Exec.scala:457) at org.apache.spark.sql.execution.datasources.v2.V2TableWriteExec.$anonfun$writeWithV2$2(WriteToDataSourceV2Exec.scala:358) at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90) at org.apache.spark.scheduler.Task.run(Task.scala:131) at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:506) at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1491) 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:834) Suppressed: com.mongodb.spark.sql.connector.exceptions.DataException: Write aborted for: PartitionId: 0, TaskId: 13. Manual data clean up may be required. at com.mongodb.spark.sql.connector.write.MongoDataWriter.abort(MongoDataWriter.java:121) at org.apache.spark.sql.execution.datasources.v2.DataWritingSparkTask$.$anonfun$run$6(WriteToDataSourceV2Exec.scala:453) at org.apache.spark.util.Utils$.tryWithSafeFinallyAndFailureCallbacks(Utils.scala:1536) ... 10 more 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$$anon$1.run(EventLoop.scala:49) at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:938) at org.apache.spark.SparkContext.runJob(SparkContext.scala:2214) at org.apache.spark.sql.execution.datasources.v2.V2TableWriteExec.writeWithV2(WriteToDataSourceV2Exec.scala:354) ... 44 more Suppressed: com.mongodb.spark.sql.connector.exceptions.DataException: Write aborted for: 678e70a2-e5a0-4a4d-ac1a-9f46173e8cd2. 0/1 tasks completed. at com.mongodb.spark.sql.connector.write.MongoBatchWrite.abort(MongoBatchWrite.java:101) at org.apache.spark.sql.execution.datasources.v2.V2TableWriteExec.writeWithV2(WriteToDataSourceV2Exec.scala:376) ... 44 more Caused by: java.lang.NullPointerException at org.apache.spark.api.python.SerDeUtil$.$anonfun$toJavaArray$1(SerDeUtil.scala:72) at scala.collection.Iterator$$anon$10.next(Iterator.scala:461) at scala.collection.Iterator$$anon$10.next(Iterator.scala:461) at scala.collection.Iterator$$anon$10.next(Iterator.scala:461) at org.apache.spark.sql.execution.datasources.v2.DataWritingSparkTask$.$anonfun$run$1(WriteToDataSourceV2Exec.scala:419) at org.apache.spark.util.Utils$.tryWithSafeFinallyAndFailureCallbacks(Utils.scala:1525) at org.apache.spark.sql.execution.datasources.v2.DataWritingSparkTask$.run(WriteToDataSourceV2Exec.scala:457) at org.apache.spark.sql.execution.datasources.v2.V2TableWriteExec.$anonfun$writeWithV2$2(WriteToDataSourceV2Exec.scala:358) at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90) at org.apache.spark.scheduler.Task.run(Task.scala:131) at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:506) at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1491) 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) ... 1 more Suppressed: com.mongodb.spark.sql.connector.exceptions.DataException: Write aborted for: PartitionId: 0, TaskId: 13. Manual data clean up may be required. at com.mongodb.spark.sql.connector.write.MongoDataWriter.abort(MongoDataWriter.java:121) at org.apache.spark.sql.execution.datasources.v2.DataWritingSparkTask$.$anonfun$run$6(WriteToDataSourceV2Exec.scala:453) at org.apache.spark.util.Utils$.tryWithSafeFinallyAndFailureCallbacks(Utils.scala:1536) ... 10 more SUCCESS: The process with PID 18700 (child process of PID 26460) has been terminated. SUCCESS: The process with PID 26460 (child process of PID 1880) has been terminated. SUCCESS: The process with PID 1880 (child process of PID 22132) has been terminated. 2024-01-09 11:17:26,865 INFO:Closing down clientserver connection
read 6 min

Hi,

Could you try with the latest version of the connector: 10.2.1 and see if the issue remains? I cant see anything obvious from the stack trace.

Ross

Hi,
Yes, I have tried with the latest version as well and the issue remain the same.
is there anything else i can provide to analyze this issue?

Solved the issue
i was doing a map on rdd

result = df.rdd.map(lambda x: parse(x))

and then creating a spark dataframe out of the result above with a custom schema
the schema had a datatype issue for one of the fields, basically instead of using TimestampType for a date field i was using a StringType.

Closed on Jan 14, 2024

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