使用 mongo-connector 版本 10.0.1 以下是我的配置
.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")
这就是我正在尝试做的事情，但我不确定为什么会发生这种情况
spark_df.write.format("mongodb").mode("append").save()
以下是我遇到的错误
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
我尝试过不同的连接器版本，并确保 Spark 版本位于 mongo-connector 文档指定的版本内。 我查看了其他帖子并尝试了所有解决方案，但没有一个有效。
解决了问题 我正在 rdd 上做一张地图
result = df.rdd.map(lambda x: parse(x))
然后使用自定义模式根据上面的结果创建 Spark 数据框 该模式的其中一个字段存在数据类型问题，基本上我没有使用 TimestampType 作为日期字段，而是使用 StringType。