我正试图将PySpark数据帧写入镶木地板文件，以供项目的后期使用。然而，当我尝试代码
final_basetable.write.parquet(path)
我收到这个错误
Py4JJavaError Traceback (most recent call last)
<ipython-input-47-afce49eef81b> in <module>
----> 1 final_basetable.write.parquet('/Users/feliw/Documents/1e Master + Masterproef/Big Data/Final_Basetable_Parquet')
~/Documents/1e Master + Masterproef/Big Data/spark-3.1.2-bin-hadoop3.2/python/pyspark/sql/readwriter.py in parquet(self, path, mode, partitionBy, compression)
1248 self.partitionBy(partitionBy)
1249 self._set_opts(compression=compression)
-> 1250 self._jwrite.parquet(path)
1251
1252 def text(self, path, compression=None, lineSep=None):
~/Documents/1e Master + Masterproef/Big Data/spark-3.1.2-bin-hadoop3.2/python/lib/py4j-0.10.9-src.zip/py4j/java_gateway.py in __call__(self, *args)
1302
1303 answer = self.gateway_client.send_command(command)
-> 1304 return_value = get_return_value(
1305 answer, self.gateway_client, self.target_id, self.name)
1306
~/Documents/1e Master + Masterproef/Big Data/spark-3.1.2-bin-hadoop3.2/python/pyspark/sql/utils.py in deco(*a, **kw)
109 def deco(*a, **kw):
110 try:
--> 111 return f(*a, **kw)
112 except py4j.protocol.Py4JJavaError as e:
113 converted = convert_exception(e.java_exception)
~/Documents/1e Master + Masterproef/Big Data/spark-3.1.2-bin-hadoop3.2/python/lib/py4j-0.10.9-src.zip/py4j/protocol.py in get_return_value(answer, gateway_client, target_id, name)
324 value = OUTPUT_CONVERTER[type](answer[2:], gateway_client)
325 if answer[1] == REFERENCE_TYPE:
--> 326 raise Py4JJavaError(
327 "An error occurred while calling {0}{1}{2}.n".
328 format(target_id, ".", name), value)
Py4JJavaError: An error occurred while calling o405.parquet.
: org.apache.spark.SparkException: Job aborted.
at org.apache.spark.sql.execution.datasources.FileFormatWriter$.write(FileFormatWriter.scala:231)
at org.apache.spark.sql.execution.datasources.InsertIntoHadoopFsRelationCommand.run(InsertIntoHadoopFsRelationCommand.scala:188)
at org.apache.spark.sql.execution.command.DataWritingCommandExec.sideEffectResult$lzycompute(commands.scala:108)
at org.apache.spark.sql.execution.command.DataWritingCommandExec.sideEffectResult(commands.scala:106)
at org.apache.spark.sql.execution.command.DataWritingCommandExec.doExecute(commands.scala:131)
at org.apache.spark.sql.execution.SparkPlan.$anonfun$execute$1(SparkPlan.scala:180)
at org.apache.spark.sql.execution.SparkPlan.$anonfun$executeQuery$1(SparkPlan.scala:218)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:215)
at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:176)
at org.apache.spark.sql.execution.QueryExecution.toRdd$lzycompute(QueryExecution.scala:132)
at org.apache.spark.sql.execution.QueryExecution.toRdd(QueryExecution.scala:131)
at org.apache.spark.sql.DataFrameWriter.$anonfun$runCommand$1(DataFrameWriter.scala:989)
at org.apache.spark.sql.execution.SQLExecution$.$anonfun$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.DataFrameWriter.runCommand(DataFrameWriter.scala:989)
at org.apache.spark.sql.DataFrameWriter.saveToV1Source(DataFrameWriter.scala:438)
at org.apache.spark.sql.DataFrameWriter.saveInternal(DataFrameWriter.scala:415)
at org.apache.spark.sql.DataFrameWriter.save(DataFrameWriter.scala:293)
at org.apache.spark.sql.DataFrameWriter.parquet(DataFrameWriter.scala:874)
at java.base/jdk.internal.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at java.base/jdk.internal.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:64)
at java.base/jdk.internal.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.base/java.lang.reflect.Method.invoke(Method.java:564)
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:832)
Caused by: org.apache.spark.SparkException: Job aborted due to stage failure: Task 1 in stage 28.0 failed 1 times, most recent failure: Lost task 1.0 in stage 28.0 (TID 1235) (192.168.0.196 executor driver): org.apache.spark.api.python.PythonException: Traceback (most recent call last):
File "/Users/feliw/Documents/1e Master + Masterproef/Big Data/spark-3.1.2-bin-hadoop3.2/python/lib/pyspark.zip/pyspark/worker.py", line 604, in main
process()
File "/Users/feliw/Documents/1e Master + Masterproef/Big Data/spark-3.1.2-bin-hadoop3.2/python/lib/pyspark.zip/pyspark/worker.py", line 596, in process
serializer.dump_stream(out_iter, outfile)
File "/Users/feliw/Documents/1e Master + Masterproef/Big Data/spark-3.1.2-bin-hadoop3.2/python/lib/pyspark.zip/pyspark/serializers.py", line 211, in dump_stream
self.serializer.dump_stream(self._batched(iterator), stream)
File "/Users/feliw/Documents/1e Master + Masterproef/Big Data/spark-3.1.2-bin-hadoop3.2/python/lib/pyspark.zip/pyspark/serializers.py", line 132, in dump_stream
for obj in iterator:
File "/Users/feliw/Documents/1e Master + Masterproef/Big Data/spark-3.1.2-bin-hadoop3.2/python/lib/pyspark.zip/pyspark/serializers.py", line 200, in _batched
for item in iterator:
File "/Users/feliw/Documents/1e Master + Masterproef/Big Data/spark-3.1.2-bin-hadoop3.2/python/lib/pyspark.zip/pyspark/worker.py", line 450, in mapper
result = tuple(f(*[a[o] for o in arg_offsets]) for (arg_offsets, f) in udfs)
File "/Users/feliw/Documents/1e Master + Masterproef/Big Data/spark-3.1.2-bin-hadoop3.2/python/lib/pyspark.zip/pyspark/worker.py", line 450, in <genexpr>
result = tuple(f(*[a[o] for o in arg_offsets]) for (arg_offsets, f) in udfs)
File "/Users/feliw/Documents/1e Master + Masterproef/Big Data/spark-3.1.2-bin-hadoop3.2/python/lib/pyspark.zip/pyspark/worker.py", line 85, in <lambda>
return lambda *a: f(*a)
File "/Users/feliw/Documents/1e Master + Masterproef/Big Data/spark-3.1.2-bin-hadoop3.2/python/lib/pyspark.zip/pyspark/util.py", line 73, in wrapper
return f(*args, **kwargs)
File "/Users/feliw/Documents/1e Master + Masterproef/Big Data/spark-3.1.2-bin-hadoop3.2/python/lib/pyspark.zip/pyspark/worker.py", line 77, in <lambda>
return lambda *a: g(f(*a))
File "/Users/feliw/Documents/1e Master + Masterproef/Big Data/spark-3.1.2-bin-hadoop3.2/python/lib/pyspark.zip/pyspark/worker.py", line 77, in <lambda>
return lambda *a: g(f(*a))
File "<ipython-input-24-db2455f1237f>", line 4, in translate_text
File "/Users/feliw/opt/anaconda3/lib/python3.8/site-packages/deep_translator/google_trans.py", line 120, in translate
raise TooManyRequests()
deep_translator.exceptions.TooManyRequests: Server Error: You made too many requests to the server. According to google, you are allowed to make 5 requests per second and up to 200k requests per day. You can wait and try again later or you can try the translate_batch function
at org.apache.spark.api.python.BasePythonRunner$ReaderIterator.handlePythonException(PythonRunner.scala:517)
at org.apache.spark.sql.execution.python.PythonUDFRunner$$anon$2.read(PythonUDFRunner.scala:84)
at org.apache.spark.sql.execution.python.PythonUDFRunner$$anon$2.read(PythonUDFRunner.scala:67)
at org.apache.spark.api.python.BasePythonRunner$ReaderIterator.hasNext(PythonRunner.scala:470)
at org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:37)
at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:489)
at scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:458)
at scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:458)
at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage4.processNext(Unknown Source)
at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
at org.apache.spark.sql.execution.WholeStageCodegenExec$$anon$1.hasNext(WholeStageCodegenExec.scala:755)
at org.apache.spark.sql.execution.aggregate.ObjectAggregationIterator.processInputs(ObjectAggregationIterator.scala:154)
at org.apache.spark.sql.execution.aggregate.ObjectAggregationIterator.<init>(ObjectAggregationIterator.scala:77)
at org.apache.spark.sql.execution.aggregate.ObjectHashAggregateExec.$anonfun$doExecute$2(ObjectHashAggregateExec.scala:107)
at org.apache.spark.sql.execution.aggregate.ObjectHashAggregateExec.$anonfun$doExecute$2$adapted(ObjectHashAggregateExec.scala:85)
at org.apache.spark.rdd.RDD.$anonfun$mapPartitionsWithIndexInternal$2(RDD.scala:885)
at org.apache.spark.rdd.RDD.$anonfun$mapPartitionsWithIndexInternal$2$adapted(RDD.scala:885)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:373)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:337)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:373)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:337)
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$TaskRunner.run(Executor.scala:500)
at java.base/java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1130)
at java.base/java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:630)
at java.base/java.lang.Thread.run(Thread.java:832)
Driver stacktrace:
at org.apache.spark.scheduler.DAGScheduler.failJobAndIndependentStages(DAGScheduler.scala:2258)
at org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2(DAGScheduler.scala:2207)
at org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2$adapted(DAGScheduler.scala:2206)
at scala.collection.mutable.ResizableArray.foreach(ResizableArray.scala:62)
at scala.collection.mutable.ResizableArray.foreach$(ResizableArray.scala:55)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:49)
at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:2206)
at org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1(DAGScheduler.scala:1079)
at org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1$adapted(DAGScheduler.scala:1079)
at scala.Option.foreach(Option.scala:407)
at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:1079)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:2445)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2387)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2376)
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:2196)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$.write(FileFormatWriter.scala:200)
... 33 more
Caused by: org.apache.spark.api.python.PythonException: Traceback (most recent call last):
File "/Users/feliw/Documents/1e Master + Masterproef/Big Data/spark-3.1.2-bin-hadoop3.2/python/lib/pyspark.zip/pyspark/worker.py", line 604, in main
process()
File "/Users/feliw/Documents/1e Master + Masterproef/Big Data/spark-3.1.2-bin-hadoop3.2/python/lib/pyspark.zip/pyspark/worker.py", line 596, in process
serializer.dump_stream(out_iter, outfile)
File "/Users/feliw/Documents/1e Master + Masterproef/Big Data/spark-3.1.2-bin-hadoop3.2/python/lib/pyspark.zip/pyspark/serializers.py", line 211, in dump_stream
self.serializer.dump_stream(self._batched(iterator), stream)
File "/Users/feliw/Documents/1e Master + Masterproef/Big Data/spark-3.1.2-bin-hadoop3.2/python/lib/pyspark.zip/pyspark/serializers.py", line 132, in dump_stream
for obj in iterator:
File "/Users/feliw/Documents/1e Master + Masterproef/Big Data/spark-3.1.2-bin-hadoop3.2/python/lib/pyspark.zip/pyspark/serializers.py", line 200, in _batched
for item in iterator:
File "/Users/feliw/Documents/1e Master + Masterproef/Big Data/spark-3.1.2-bin-hadoop3.2/python/lib/pyspark.zip/pyspark/worker.py", line 450, in mapper
result = tuple(f(*[a[o] for o in arg_offsets]) for (arg_offsets, f) in udfs)
File "/Users/feliw/Documents/1e Master + Masterproef/Big Data/spark-3.1.2-bin-hadoop3.2/python/lib/pyspark.zip/pyspark/worker.py", line 450, in <genexpr>
result = tuple(f(*[a[o] for o in arg_offsets]) for (arg_offsets, f) in udfs)
File "/Users/feliw/Documents/1e Master + Masterproef/Big Data/spark-3.1.2-bin-hadoop3.2/python/lib/pyspark.zip/pyspark/worker.py", line 85, in <lambda>
return lambda *a: f(*a)
File "/Users/feliw/Documents/1e Master + Masterproef/Big Data/spark-3.1.2-bin-hadoop3.2/python/lib/pyspark.zip/pyspark/util.py", line 73, in wrapper
return f(*args, **kwargs)
File "/Users/feliw/Documents/1e Master + Masterproef/Big Data/spark-3.1.2-bin-hadoop3.2/python/lib/pyspark.zip/pyspark/worker.py", line 77, in <lambda>
return lambda *a: g(f(*a))
File "/Users/feliw/Documents/1e Master + Masterproef/Big Data/spark-3.1.2-bin-hadoop3.2/python/lib/pyspark.zip/pyspark/worker.py", line 77, in <lambda>
return lambda *a: g(f(*a))
File "<ipython-input-24-db2455f1237f>", line 4, in translate_text
File "/Users/feliw/opt/anaconda3/lib/python3.8/site-packages/deep_translator/google_trans.py", line 120, in translate
raise TooManyRequests()
deep_translator.exceptions.TooManyRequests: Server Error: You made too many requests to the server. According to google, you are allowed to make 5 requests per second and up to 200k requests per day. You can wait and try again later or you can try the translate_batch function
at org.apache.spark.api.python.BasePythonRunner$ReaderIterator.handlePythonException(PythonRunner.scala:517)
at org.apache.spark.sql.execution.python.PythonUDFRunner$$anon$2.read(PythonUDFRunner.scala:84)
at org.apache.spark.sql.execution.python.PythonUDFRunner$$anon$2.read(PythonUDFRunner.scala:67)
at org.apache.spark.api.python.BasePythonRunner$ReaderIterator.hasNext(PythonRunner.scala:470)
at org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:37)
at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:489)
at scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:458)
at scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:458)
at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage4.processNext(Unknown Source)
at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
at org.apache.spark.sql.execution.WholeStageCodegenExec$$anon$1.hasNext(WholeStageCodegenExec.scala:755)
at org.apache.spark.sql.execution.aggregate.ObjectAggregationIterator.processInputs(ObjectAggregationIterator.scala:154)
at org.apache.spark.sql.execution.aggregate.ObjectAggregationIterator.<init>(ObjectAggregationIterator.scala:77)
at org.apache.spark.sql.execution.aggregate.ObjectHashAggregateExec.$anonfun$doExecute$2(ObjectHashAggregateExec.scala:107)
at org.apache.spark.sql.execution.aggregate.ObjectHashAggregateExec.$anonfun$doExecute$2$adapted(ObjectHashAggregateExec.scala:85)
at org.apache.spark.rdd.RDD.$anonfun$mapPartitionsWithIndexInternal$2(RDD.scala:885)
at org.apache.spark.rdd.RDD.$anonfun$mapPartitionsWithIndexInternal$2$adapted(RDD.scala:885)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:373)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:337)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:373)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:337)
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$TaskRunner.run(Executor.scala:500)
at java.base/java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1130)
at java.base/java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:630)
... 1 more
我们使用了一个翻译工具，我怀疑这是目前面临问题的罪魁祸首。有没有比我更有技巧的人知道解决这个问题的办法？提前感谢！！
您在该日志中有错误的python回溯：
deep_translator.exceptions.TooManyRequests: Server Error: You made too many requests to the server. According to google, you are allowed to make 5 requests per second and up to 200k requests per day. You can wait and try again later or you can try the translate_batch function
看起来您正在使用带有谷歌翻译的python库deep-translator。因此，您需要遵守谷歌翻译配额。
在Spark方面，您几乎无能为力。例如，您可以尝试减少对Google Translate API的调用次数，方法是将文本连接到pandas UDF中。或者，您可以尝试使用其他具有deep-translator的翻译服务，该服务的配额限制较少。另一种解决方案是在Spark脚本之前或之后移动翻译部分，这样就可以在API调用之间引入延迟。